JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY Volume 10 Contents January - June 2016 Number 1 Page No. Title 1. Design and Development of Underwater Robot for Cleaning Process M.S.M. Aras, M. K.M. Zambri, F.A. Azis, S.S. Abdullah, A.M. Kassim ...................12. The Influence of Extrusion Die Angle During the Hot Extrusion Process of Al Alloys H.R. Rezaei Ashtiani....................................................................................................153. Laser Forming of Metallic Dome‐Shaped Parts Using Spiral and Radial‐Circular Scan Paths S.H., Dehghan, M., Loh‐Mousavi , M., Farzin and M., Safari...................................294. Failure Mode and Effects Analysis of Ship Systems Using an Integrated Dempster Shafer Theory and Electre Method I, Emovon......................................................................................................................455. Wastewater Treatment by Electro‐Oxidation Process With TiO2 Q.J., Rasheed, F., Ghanim and T.A., Abdullah............................................................616. Application of Theory of Inventive Problem Solving for Systematic Innovation: Case Study of Water Dispenser Design M.R., Mansor, H., Rusnandi and W.N., Mohd Isa.....................................................737. Microelectronics Thermal Dissipation Characterization Using Triz M.C., Ong, M.N., Abd Rahman..................................................................................838. Minimizing Number of Defects in Nickel Plating Process Using Factorial Design N. Q. I. Baharuddin, L. Sukarma, E. Mohamad, A. Saptari and M.R. Salleh.............959. Investigation of Forces, Power and Surface Roughness in Hard Turning With Mixed Ceramic Tool B., Varaprasad and R. C., Srinivasa............................................................................107

Chief EditorFirst and foremost, warm greetings to all the readers. I am delightedto announce the 18th issue of the Journal of Advanced ManufacturingTechnology (JAMT). Currently, JAMT addresses three objectives; toprovide a platform for the discussion and knowledge sharing on currentand future issues, practices, innovations and trends of engineeringand information technology amongst the academics, researchers andpractitioners, to promote and encourage exploration and disseminationof knowledge in relation to engineering and information technology, andto publish papers in the areas of engineering and information technologyparticularly green technology, system engineering, human‐technologyinteraction and emerging technology.JAMT will continuously be a great and significant contribution to theFaculty of Manufacturing Engineering and UTeM. JAMT strives to attractand engage an international readership that is primarily academic as well.This move is in line with the mission of university “To Be One of theWorld’s Leading Innovative and Creative Technical Universities” JAMTwelcomes any papers, either written individually or co‐operatively, whichwill make a substantial contribution to the development and success ofthe journal. Please do not hesitate to contact us for any uncertainties orenquiries.I wish to take this opportunity to thank all the individuals involved in thispublication particularly the editorial and technical boards for their tirelessefforts in ensuring the continued success of JAMT. Moreover, my gratitudeis extended to all contributors.Best wishes and thank you for your support. iii

Design and Development of Underwater Robot for Cleaning ProcessDESIGN AND DEVELOPMENT OF UNDERWATER ROBOT FOR CLEANING PROCESS M.S.M. Aras1*, M. K.M. Zambri1, F.A. Azis1, S.S. Abdullah2, A.M. Kassim1 1Underwater Technology Research Group (UTeRG), 1Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia, 2Department of Electric and Electronics, Malaysia‐Japan International Institute of Technology, Universiti Teknologi Malaysia, International Campus, Jalan Semarak, 54100 Kuala Lumpur, Malaysia. Email: [email protected]: This paper shows the conception and growth of an underwaterrobot for cleaning operation that can help human beings to perform cleaningtasks underwater. Unmanned underwater vehicles can cut down the dangerto human life in term of underwater cleaning job where a human can diveand descent at a certain depth and is not able to stay there in a longer periodof time. Underwater Robot for cleaning process was a combination betweenunderwater robot such as Remotely Operated Vehicles (ROV) and cleaningpart called Underwater Cleaning Robot (UCR). The main objective of thisproject was to develop a cleaning tool attached to the ROV to demonstrate theperformance of the cleaning procedure as in water treatment operations. Bythe invention of this UCR, more underwater cleaning job can be done withoutinvolving human life. This project began with a design using Solidworkssoftware to capture the dynamics of a newly fabricated UCR. The UCR canperform the cleaning task and this project can give much benefit to the relatedunderwater business especially for the cleaning process.KEYWORDS: Remotely Operated Vehicle, Underwater Cleaning Robot (UCR),cleaning process.1.0 INTRODUCTIONOver the years, the engineers and scientists have struggled to createa machine or a robot that can help human beings in performing tasksinvolving underwater situations. Furthermore, shipping industry orcatfish pond entrepreneurs face problems in cleaning purposes.Forexample, to clean the bottom of the vessel, a locksmith should diveunder water to do the cleaning. Besides, to collect the rubbish underthe sea, divers should dive to the ocean floor to collect it.. This processISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 1

Journal of Advanced Manufacturing Technologytakes a long time and can endanger humans lives.These projects were focusing on designing and developing anunderwater robot for a cleaning process. An underwater vehicle isa robot which travels underwater without requiring input from anoperator. Underwater vehicle constitutes part of a larger group ofundersea systems known as unmanned underwater vehicles. It iscontrolled and powered from the surface by an operator / pilot throughan umbilical or remote control [1]. Hence, the operator can handle theunderwater vehicle robot easily to move to any direction for cleaningprocess. The Underwater Robot for Cleaning Process (UCR) is a robotthat is designed for cleaning purposes work under the sea. The mainpurpose of the creation of this robot is to perform operations that areharmful to humans as the depth of a high pressure can affect the humanbody. In the current state, most of the underwater cleaning job is doneby human such as cleaning the bottom of the vessel, submarine aswell as swimming pool [2]. Basically, this robot is using thruster asan actuator part and more likely as Remotely Operated Vehicle (ROV)that uses remote as a controller and is able to successfully complete acleaning job. This UCR will use a motor pump to suck dirt in the waterat any pool and transfer it to the filter division, which contains somefiltering material to isolate the impurities and dirt in the water. Thiscleaning process requires two motor pumps in which one motor pumpwill be installed at the intake side of the filter and the rest at the outletside in order to force the water from thr filtering division to come out.Other than that, the underwater vehicles should have installed thecleaning part as this is a major reason for doing this project. ThisUCR should be able to perform some cleaning job in the pool or waterreservoirs in the laboratory in order to fulfil the objective and scopeof this project. By the invention of this underwater vehicle, moreunderwater cleaning job can be done without risking human life and,on the other hand, the number of human casualty in the sea can bereduced.Based on three journals [3‐5], all projects are related to the underwatercleaning task using different ways. Two of them operate in fullyautomated, which requires some programming language while theother one operates manually, which requires a pilot to control thewhole system. The cleaning tools, method and area of cleaning arealso different based on the purpose design and their capability. Fromthe comparison that has been made in [3‐5], the Underwater CleaningRobot (UCR) for cleaning process will be created. This UCR used amanual controller and a pumping system to clean the water. The frame2 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

  Design and Development of Underwater Robot for Cleaning Process design and their capability. From the comparison that has been made  in [3‐5],  the  Underwater  Cleaning  Robot  (UCR)  for  cleaning  process  will  be  created.  bTohdisy UoCf Rth uissepdr ao jmecatnuutaill iczoendtraollulemr ainndiu  ma pmumatpeirniga ls. yTshteemre toa rcele6anth thrue swteartser.  uTsheed  frfaomr et hbeodUyC  oRf  tphrios ppurlosjieocnt  ustyilsizteemd .  aTlhume icnoiunmtr oml abtoerairadl.  uTsheedre waraes  6  PthSrCu2st8eArs fursoemd  fCory ttrhoen  UTCeRch  pnroolpougliseiosnb  seycsatuemse.  tThhies  cboonatrrodl hbaovared buusieldd ‐winas  rPeSqCu2i8reAm  efrnotms t hCatytwroenr e TneecehdneodlofgoiresU  CbRec.ause  this  board  have  build‐in  requirements that were needed for UCR.    2  .0 METHODOLOGY T2h.0is  i s   thMeEfiTrsHt pOhDasOe oLfOimGpYle menting this project. The first design of  UstaoeauTholfanshClefsoitditnihRswwbl g yeeoi asaus SdUp srstoueeyuhiCl n,siletfdleRuhg r frWiaesisnaSr emsto nortatarosde ls kpiktdcoseehh a Wafaoa2rnsesfts0 hieoee1abl‐ eyr3lutdoks hfUiisopsl meodiuCmfm2iettnlaR0wnlpegs1sliaak aie3nhorsmneonausad refoacrdnlaeftbo wthtnvutwitr hnhaiipeealgeredrweer ro‐t mei.hdvepn  iqiBcaigasdmaruyt etphen ise rpruat.n iohprsmaTjseidrelnhi oecwobsgetnvnta . a rsitstaTderohiilcehnfnei tsevgswsp t tittsfhareaahiourrewrlfstlceitsetnbtw . .udadaBaTlersele[yrvohis6e cweioe,]ug r.fssunss yt toi sruhnopeufesftrgaec  wsUUrrt tsutcahCC aorrtiRRnoeesf     also  measure  the  material  strength  in  every  part  of  the  body  frame  of  the  2U.1C R anEdl oetchterro neqicuiPpamrtenCt oinnssttarlulecdt i[o6n].    T2o.1 cEolencttrroolntihc ePealret cCtroonnstircuacntidone lectrical part that were installed on UCR s uch as thruster and cleaning equipment, a control box that contained eTloe cctornotnriocl tchirec euleitctarosnaic barnadi neleocftrtihcael wpahrto tlheaUt wCeRres iynsstteamlledn oeend UeCdRt osubche  ianss  tthalrluesdtere iatnhde rclbeayniDngIY  eqmuieptmhoednt,o  ar  cpolnutrgola  bnodx pthlaaty  comnetathinoedd.  eFleocrtrothniisc  UciCrcRui,tP  aSsC  a2  b8rAainc oonf ttrhoel lwerhboolea  rUdCmR asynsutefamc tnuereeddedb ytoC  byet rionnstaTlelecdh neiothloegr ibeys  wDaIYs  umseetdhoads  oar mplauign  acnodn tprolalyle  rm. eFthoords.m  Fooor tthhios pUeCraRt,i oPnSCo2f8tAh ecosnytsrtoelmler,  tbhoearPdS mCa2n8uAfabctouarredd bsyh oCuyltdrobn eTeucshendoltooggieest hwears wusiethd aPsS a2 mcoainnt rcoolnletrrol[l9e]r..  AFocrc osrmdoinogth tooptehreatdioant aosfh  e  tehtep  sryosvteidme,  bthye CPyStCro28nA,  tbhoisarcdi rschuoitulids dbier eucstelyd  ctoognentehcetre  dwwithi thPSin2 pcuotnatrnodlleoru  [t9p]u. tApcocortrd/iunng ittso. Tthhee  idnaptausthpeeotr  tpirsotvhideeP  Sb2y  cCoynttrroonl,l ethrisa ncidrctuhite iso udtirpeucttlyp coorntsneacrteedt hweitmh ointpour tf oanrdt hoeuttphurtu pstoerrt, / wunatitesr.  pTuhme  ipnpfourt bpaolrlta  isst  tthaen kPSa2n  cdocnlteraonlleinr ganpdu  mthep  o[7u]t.put  ports  are  the  motor  for  the thruster, water pump for ballast tank and cleaning pump [7].  2  .2 PSC28A Controller Board T2h.2e PPSSCC282A8A Coisntaroclilrecru Biot abroda  rd that plays as an interface between PS2 c ontroller and another device that needs to be controlled as shown iTnheF igPuSCre281A.  Iits cao uclidrcubiet  cboonanrde cttheadt epiltahyesr  aths raonu gihntemrfiaccreo cboentwtreoelnle rPoS2r  dcoirnetcrtollyletro aIn/Od adneovtihceer. dTehveicPeS tCh2at8 Anededose ston boet acolsnotrroelqleudi raes ashporwognr ainm Fmigiunrge  l1a.n  Igt ucaogueldt obep  ceorfnonremctebde  ceaituhseer  thhreoupgrho gmraicmrocisonitnrsoellretre dori ndsiridecetlyth  teo PII/OC  mdeivcricoec.o  Tnhtreo  lPleSrC[278]A.   does  not  also  require  a  programming  language  to  perform because the program is inserted inside the PIC microcontroller [7].    FFigiguurere1 1: :P PSSCC2288AAc oconntrtorolllelerrb booaardrda annddP PSS22c oconntrtorolllelerr[ 7[7] ]   2.3 Electronic Wiring ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 3

Journal of Advanced Manufacturing Technology  Jo2u.r3na l of AEdlveanccterdo MniacnuWfacitruirningg Technology F igure 2 showsthe electronic Assembly details which was required for UFiCgRurien 2o srhdoewr tsothme aekleectirtowniocr Ak spsreompbelryl yd.eTtahiels1 w2Vhicbha twtearsy rweqiuthir3eAd fcourr UreCnRt  pino woredresru top pmlyakwe aits wuoserkd ptorospueprlpy.l y Tchuer r1e2nVt baanttdervyo wltaitghe 3tAo c6uDrrCenmt pootworesr  fsourp6pltyh rwusatse  russeadn dtow  sauteprplpyu  mcuprr.eTnht eanredl avyofltoargeH  ‐tBo ri6d  gDeCc  imrcoutiotrsin  fowra  s6  ttrhigrugsetreersd ainndo wrdaeterrt opucmonpt.r Tohl eth reelmayo fvoerm He‐nBrtiodfgteh ceirtchuriut sinte wr ass twrieglglearsedth ien  woradter ptou  cmopnt.rOoln  tlhye 5mVowveams erneqt uoifr  tehde bthyrtuhsetePr SaCs 2w8eAll caosn  tthreo lwleartebro aprudmtpo.  pOonwlye r5Vit uwpa.sT rheqeuPirSeCd2  8bAy tihsea PcSirCc2u8iAt b cooanrtdropllleary baosaradn tion tpeorwfaecre ibt eutpw. eTehne  PPSS2Cc2o8Ant riso lale  criracnudit abnooatrhde  prldaye vaisc eanth  ianttenrefaecdes  btoetwbeeecno nPtSr2o lcloednt.roller  and  another device that needs to be controlled.      FFigiguurere2 :2E: ElelcetcrtoronnicicA AsssesmembblylyD Deteatialisls    TToo imimpplleemmenntt thiss pprojeecctt,,  alll 66 DDCC mmoottoorr ffoorr ththrruusstteerr aalloonngg wwiitthh wwaatteerr  ppuummp ((ffoorr bbaallllaasst ttaannkk) wweerree wwiirreedd totot htheeH  H‐B‐Brirdidggeec  cirirccuuiitt..T  ThheeH  H‐B‐Brriiddggee  cciirrccuuit  boaarrdd  ccoonntatainineded  2 2sisnignlge lpe opleosl e4s  t4hrtohwro  rwelarye liany  winhiwchh  eicahche aocnhe  ofn  iet  owf aist  uwsaesd ueistehder efiothr eforrfwoarrdfo  arwnda rrdevaenrsde  mreovteiorsne  omf  tohteio  tnhroufsttehr eanthdr  uwsatteerr  apnudmwp.a  tWeritphu  mthips.  Wproitphert hcisonpnreocptieorn,c oenvneeryc timono,vemveernyt mlikoev elmefet,n  trilgikhet,  lseuftb,mriegrhget, osru fblomate orgf eUoCrRf wloaast poofsUsibCleR. Twhais Hpo‐Bsrsiidbgle .wTahsi swHire‐dB rtiod PgSeCw28aAs   wasi rtehde troelPayS Cre2q8uAireads t5hVe proewlaeyr.r eAqtu thiree dsa5mVe ptiomwe,e trh. eA itntphuet ssaigmnealt ifmroem,  tthhee  iHnp‐Burtidsgige nwaal sf rcoomnntehcteedH  t‐oB rtihdeg  PeSwC2a8sAc oonuntpeuct etdermtointhale.  TPhSiCs 2is8 Aimopuotrptauntt  tbeercmauinsae lt.hTaht iws aiss  tihme poonrlyta  wntayb ethcea usisgentahl afrtowma  PsSt2h  jeoyosntilcyk wcoanytrtohlleers icgonualdl   fbroe mbe PseSn2t jdoiyrsetcitclyk tcoo tnhter odlelveircec othualdt nbeeedbeeds teon bted ciorenctrtolylletod. the device that n  eeded to be controlled. 2.4 Motor Driver   2 .4 Motor Driver LL229933DD iiss aann HH‐‐BBrriiddggee  mmoototor rddrirvievre rwwhihchic his iussuesde dto tdordivrei vae  DaCD  mComtoor tobyr  buysiunsgi nthget hseigsniagln  tahlatth  aist igsegneenraetreadt ebdyb  ay  aPIPCI Cmmicricorcoocnotrnotlrleorl lears asshsohwonw  inn  iFnigFuigreu 3r.e T3h.iTs hHi‐sBHrid‐Bger imdgoetomr dortiovrerd ernivaberleedn vaobltlaegdev too lbtae gaepptoliebde taop cprolisesd a  tlooacdro  (smsoatolro)a  idn (bmootht odri)reinctiboontsh.  Tdhiere  mctaioinn sp.uTrhpoesme  oafin  upsiunrgp  tohsies  Hof‐Bursiidngge  tdhriisvHer‐ wBraisd tgoe cdonritvroelr DwCa smtootocro nint rboolthD Cdirmecotitoonrsi neitbhoetrh tod riruenc tiino cnlsocekitwhiesre  toor rcuonunitnercclloocckkwwiissee. oTrhec omuonvteemrcelnotc kofw DisCe .mTohteorm coouvledm been atpopfliDedC  umsiontgo ra  ccooumldbinbaetiaopn polife  dtraunssiinstgoras caonmd bminoattoior nino fHtr‐Banrisdigseto  rdsriavnerd  imn owtohricihn  tHhe‐  Btrraidnsgiestodrrsi vweoruilnd  awllohwic hcutrhreenttr  taon  psiasstso  rthsrowuoguhl din aolnloe wdirceuctriroenn  tontloy. pTahsiss  tlherdo tuhge hmiontoorn teo druirne cetiitohner ofonrlwy.aTrdh iosrl beadckthweamrdo atcocrotrodirnugn toe itthhee pr ofosirtwioanr odf  otrrabnascisktowras r[d8].a  ccording to the position of transistors [8].   4 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 

Design and Development of Underwater Robot for Cleaning Process  X1 11 32 12V CRYSTAL R1 R2 U1 R3 47k 47k 13 330R 14 OSC1/CLKIN RB0/INT 33 34 R4 2 OSC2/CLKOUT RB1 35 330R 3 36 4 RB2 37 5 38 6 RA0/AN0 RB3/PGM 39 7 40 RA1/AN1 RB4 Q3 8 15 2N2369 9 RA2/AN2/VREF-/CVREF RB5 16 Q1 10 17 2N2369 RA3/AN3/VREF+ RB6/PGC 18 1 23 RA4/T0CKI/C1OUT RB7/PGD 24 25 RA5/AN4/SS/C2OUT 26 RC0/T1OSO/T1CKI 19 D1 D2 20 1N4001 1N4001 RE0/AN5/RD RC1/T1OSI/CCP2 21 22 RE1/AN6/W R RC2/CCP1 27 28 RE2/AN7/CS RC3/SCK/SCL 29 30 R7 RC4/SDI/SDA 47k MCLR/Vpp/THV RC5/SDO RC6/TX/CK RC7/RX/DT RD0/PSP0 D3 D4 Q4 RD1/PSP1 1N4001 1N4001 RD2/PSP2 RD3/PSP3 RD4/PSP4 RD5/PSP5 RD6/PSP6 RD7/PSP7 PIC16F877A Q2 2N2369 12 31 2N2369   FFigiguurere3 3: :H H‐B‐Brirdidggeec ciricrcuuitit    22..5  CleaCnilnega nPirnogcePssr oSceecstisoSn ection mdeupIupuI fnonmasrassar aiiiorr nnnopttwtrte rggghldtrdtonh  ihiseseyaasaua rra ueltstc tfn dttckniouunoldkitesdbn eefiebiefyngoruniddu . rlgiTgmttsislheldh tdtemarhtheott oet ihhit e dgdbshcoibthiesiohdreussnptp  fo ts iopsfuoscrdioic nroowsdccoutnjgoiuyesjesstem sc.araecToeteictmd,ndfhf,do  tie ooehltsmdothnevneen evdlma.riyc .en ciBcl trro Bueulhaattenaashulsaae snlceemtnyedlo idaidcnp.nny ou Hoogogetonosnarr emneslsmin ln  dipweicsloete.uiettetftadhs,h emHr ttofreoaohiaipredldtfnitt unse uwss smrrcmrheth eaeehvomo,soe,, ee uttuttdahhtrohllhtarpdodereeailsd or swwb.bilw oawaeenaTmllya  tat htteheuaewsheirnr estrseeshai dc mpntcopplo egrlefpdrefriir ailmoalhmftnoneicwwiylairgaeitnneeraareshddgygysssr‐     cpoonwtienreude dvaucnutuiml t hoer pwuamtepr minottohres.p Tohnids p/rpocoeosls c hcoanntgineudeda luintttliel tfhroe mwattheer  pinr etvhieo  puosncdle  /a npionogl .cPhaarntgoedf  tah ilsittcllee afrnoimng  thtoe oplsrewvioouusld  clbeeanininsgta. lPleadrt oonf  tthhies  UclCeaRnianngd toUolCs Rwowuoldu blde ibnestcaollnedtr oolnl etdhet oUCmRo avneda UcrCoRss wthouelpd obned  ctoontsrpoelleedd  utop mthoevec alecaronsisn tghep proocneds sto.  Tspheiesdc ulepa nthine gcletoanoilncgo purlodceaslss.o Thclise acnleatnhiengm tooostl  ocfouthlde ablsoot tcolemans uthref amceosot foft htheep booottloamt stuhrefascaem oef tthiem peo. oIln ato trhdee rsatmoem tiamkee.  tIhni socrldeearn  itno gmmaekteh  othdisp  ecrlefoanrminge fmficeitehnotdly  p, tehrfeorremw  eefrfeicsieenvtelyr,a lthpearret swthearet  nseeveedreadl ptaortbse thsatut dneieedd.ed to be studied.    3.0       RESULTS AND DISCUSSION  3  .0 RESULTS AND DISCUSSION This  section  will  describe  and  discuss  the  results  and  analysis.  First,  the  wrfaTardpsmwrcaroesneho ehaaisadbsomodsdrimsuusrisuaiwhfe egmllmcfsesttl donenshyssteeere w ,UtceirebbatvwnacteanCaebnaeiid rpotsaFialsl R teooedlieniseph  gndppyedRrcoduw es.otaOsoFeiodremFigtinestidVn odlinig i plgo4bg.ti ut dbaofh nueh mn(frrTyfcee aeree eoa hs)uwaerdd cfudciei‐n4  osane r4svnewd( isemsctiis(bteis( eai)aigdtcr e.wmgtip )hbwn)nhFenaeo   ‐ieiv,csauoncsgsrlohtea (fsoiudmecc ftluiocsrirtoni)otadhesw oeo.gchpendl enirl4F  esesef  eRSo ihpicda(ogpogftaOuunr hulfsrui)obiilst tVoedrlnjsarvesa eaj wgean.ceicbpsttne iadthTicrlooa4 mwdeuto ebhrnr( bkbsb(payic raceossuy)m hleh .io)ut sssecita.uTmses hhiuiaas tnisthop niynlbepisgteweb,ngdrse a rcer gocsS.arSodoe  (apeo tnonbSbneFhuedllud o)sfiiniesgiddiwsl es ggaiptuwWfwdh,inunr rrodaeWoioearoofteam owjalhrrel4syioyktfkcety sis(r sst so ucc ik Uta.dtsn)lssonhsd o.oCTei sdmeohmFsssfhhRteioepiaowgpaep rdrftswdnsiewtlranowtie bdorscw,thaspe e ajitaitetu tiheegibheratyncnnlnhyeeesrtl,,       cleaning robot. ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 5

Journal of Advanced Manufacturing Technology  Journal of Advanced Manufacturing Technology  (a) Different view of UCR with dimension    (b)  Hose for cleaning system                               (c) Cleaning system storage  Figure 4: Parameter of design     33..11 C entCere onft eGrroavfiGtyr  avity   Thhee UUCCRR uusesde dtwtwo othrtuhsrtuesrste frosr fsourbmsuebrgmee arngde falonadt mflooavtemmeonvt.e mTheen tth. rTuhsteer  tmhurusts tbeer  pmlaucsetdb  aet pthlaec  ceednatetrt hofe  tcheen  UteCr Ro fstoh  ethUatC  sRubsmoetrhgaet  asnudb mfloeartg emaontidon  fclaona tbme octoinodnuccatendb  eefcfoicniednutlcyt eads esfhfiocwienn tilny aFsigsuhroew  5n.  iInn Foirgduerre  t5o. Ipnlaocred  ethre  tthorupslatecre atth theet hcernutsetre orf atthet hgeracveitnyt,e trheo fUtChRe mgruasvt ibtye ,inth setabUleC cRonmduitisotnb aes itnhe  ssttaabbilleityc ocnand iatfiofencta tsheth veersttiacbali lmityovceamneanftf eocf tththee UvCeRrt. iTcahle mceonvteerm oef ngtraovfittyh eof  UthCe RU.CTRh ceanc ebne tfeorunodf  gbyra uvsiitnyg oSfoltihde WUoCrkR 20c1a3n abs eshfoowunn din bFyiguursei n6g.  Solid W  ork 2013 as shown in Figure 6. Center of mass   X : 423 mm,     Y: 7.45 mm,    Z: ‐467 mm  C  enter of mass X : 423 mm, Y: 7.45 mm, Z: ‐467 mm 6 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 

Design and Development of Underwater Robot for Cleaning Process    Figure 5: Prototype of UCR                            Figure 6: Center of Gravity UCR    33.2.2 W eighWt eEisgthimt aEtsiotinm  ation   TThhee UUCCRR mmuusts bt eb eflfolaotaetde data utnudnedrwerawteart elervleelv teol etonseunrseu irt ecaitnc eaansielays filloyaftl oanadt   saunbdmesurgbem. Ienr ogred.eIrn too rddoe trhtaot, dthoe twheaitg, htht oefw UeCigRh wt aosf cUalCcuRlawteads. Tchaelc buulaotyeadn.t  tThehoeryb sutaotyeas ntht att,h tehoer fyorsctea atcets vtehrtaict,altlyh eupfworacred taoc tthev ecertnitcraolildy ouf UpwCRar adndt oit  ctahne  bcee ndterofiindedo fmUatChRemaantidcailtlyc  abny  buesindge fiAnrecdhimmeadthese’m  partiniccaiplllye  bays  suhsoinwgn  bAelrocwhi [m9]e: des’ principle as shown below [9]: Fb = γ f Vd       (1)   W here,    Fb = γ f Vd (1) Fb =Buoyant force ,γf  = Specific weight of the fluid, Vd =Displaced volume of  tWhe hfleuried,   Fb =Buoyant force ,γf = Specific weight of the fluid, Vd =Displaced volume Ionf ththeeorfylu, widh.en an object is floating, it displaces a sufficient volume of fluid to  balance its height [10]. The application of the equation of static equilibrium in  itsW msstuIefhulhn tqoepuhbaae dutmewivytxhdeniesileta et riihtareirbtnoongnidder cref  ibay.oploduulwa,bTo b mdiilwjdshnjheaieicr  enehtciaaetninc te ncoinf esntldintieu sthof ihuaitltwniedohesnnt,a  er vh[h∑ta o1rbepieeeln1 borroFis]gtdjgbe.sveti , vyiuhc = ctm ae itto0vrloy[oi.e s1dfiIad  tn0dfinerla i]itocs.ernhieyacTn sicttsuhotiii fioncsbebloaungjmneeasi,, ecxdpoeΣit iitp frtta ge dtlFsinhidtesvciade dsaay= pwusttsiisl0hn pohau.ewincemanIennpa ofserolpdftdtuahsho t.iti hissedhtTsiuieathvb[ciftoee1ef aoti nq1shncdd ]ueiee.yiew aurionetttobhitrciofjaestevrnlica ooaebtnvosnl uiusefsoouor msiy bnfmtaeiaj ttreneht eocicdesciftyst    TWo hsuebnmaenrgoeb ajenc ot bisjefclto, aatni negxt,ernal foFrbc e=  iws  r=e qγu f Virde  d   and t(h2)e  force buoyancy is:    T o subm erge a n objec t, an eFFxbb t=e= wrwn +a= lFγef =of  Vrγc dfe V di +s Free    q  uired( 3a) nd the fo(r2c)e Tbhueo wyaeingchyt iess:timation of UCR should be calculated to ensure the UCR can be  ft hlorautsetde r,u  bnoddeyr  far a mwae,t elra ml epv, ealn  ads a F nbcel=eeadwneid+n.gF   Tet=ohoeγl  fwiVs hdaol+rleeFa edp ya rstu  ob fm  UerCgeR d   swuhch(e3n )a ist   isT phleacwedei ignhtot  ethstei mwaatteior nsoo tfhUat CanR esxhtoerunladl fboerccea alccutsl aotne dthteo peanrtssu. re the UCR  can be floated under a water level as needed. The whole part of UCR 3s.2u.c1h Praessstuhrreu Hstuelrl,  body frame, lamp, and a cleaning tool is already Figure 7 shows the free body diagram for pressure hull. The unit is in  millimeter.    ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 7

Journal of Advanced Manufacturing Technology submerged when it is placed into the water so that an external force acts on the parts. 3.2.1 Pressure Hull Figure 7 shows the free body diagram for pressure hull. The unit is in millimeter.  Journal of Advanced Manufacturing Technology   (4)   Figure 7: Pressure Hull free body diagram   (5)  ∑ Fv = 0  (6)      Fb = Fe + w   (7)  W = 2.512 kg      Fb = γf + Vd  ∑V dTotal = Vdi + Vdii + Vdiii  (8)  r = 87 mm  Vdi =   ) +     (9)      =  (873) +   (872) 100      = 3.757 × 106 mm3  Vdii =  l      =   (872) (300)      = 7.133 × 106 mm3  Vdiii = Vdi           = 3.757 × 106 mm3  VdTotal = 3.757 × 106 mm3 + 7.133 × 106 mm3 + 3.757 × 106 mm3             = 14.647 × 106 mm3  Water, γf  = 9.81 × 103 N/m3          = 143.69 N  Fel = Fbl – w1  (10)         = 143.69    ̶ (2.512 × 9.81)       = 119.047 N  3.2.2 B3a.2ll.a2s t TBanalkl ast TankFigure 8 shows the free body diagram for ballast tank. The unit is in millimFeitgeur.r e 8 shows the free body diagram for ballast tank. The unit is in millimeter. 8 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016   (11)  Figure 8: Ballast Tank Free Body Diagram   ∑ Fv = 0 

       = 143.69   ̶ (2.512 × 9.81)       = 119.047 N    3.2.2 Ballast Tank  Design and Development of Underwater Robot for Cleaning Process Figure 8 shows the free body diagram for ballast tank. The unit is in  millimeter.    Figure 8: Ballast Tank Free Body Diagram   ∑ Fv = 0  (11)  Fb = Fe + w  (12)      W = 0.5kg      Fb = γf + Vd  (13)  Vd = l×w×h  (14)        = 140 × 245 × 50      = 1.715 × 106 mm3       = 140 × 245 × 50      = 1.715 × 106 mm3     33.648 N  Fe2 = Fb – w    (15)        3=3 .3634.864 N8    ̶ (0.5 × 9.81)   F  e 2  ==  F28b –.7 w43  N  (15)         = 33.648   ̶ (0.5 × 9.81)  3.2.3T3h.r2u.3st er Thr  u  s =t e2r8.743 N  F  igure 9 shows the free body diagram for the thruster. The unit is in  3m.2il.l3iTmFheirtgueurs.tr eer 9 shows the free body diagram for the thruster. The unit is in Figurem 9i sllhimowest ethr.e free body diagram for the thruster. The unit is in  millimeter.    Figure 9: Thruster Free Body Diagram      ∑ FFvi =g u0r  e 9: Thruster Free Body Diagram     (16)  Fb = Fe + w  (17)   ∑    Fwv  ==  00 .4 kg  (16)  F   b   =F bF =e  +γ wf +  Vd  ((1178))    ∑  V w d T=ot a0l =.4  Vkdgi  + Vdii   (19)          r F =b  =2 5γ mf + mVd   (18)  V∑dVi = d Tot arl 2=l  Vdi + Vdii   ((2109))            r= =   2(52 5m2)m (5 6)   V  d i  ==  10 r92.l9  5 × 103 mm3  (20)            =V di =(2  5 2r)2 (l 56)  (21)             =    1  0 9=. 95(2 ×5 21)0 (33 m3)m  3      I    S   VS N d i  : = 1=  9 68 r452-.l73  195 ×7 106 mVoml.31 0 No. 1 January - June 2016 (21)  9  ∑  V     d T  o ta =l =   1(0295.29) 5( 3×3 1) 03 mm3 + 64.79 × 106 mm3                                  =      6=4 1.7794 .7×4 1 0× 61 m03m m3 m3  33 6 3 

∑∑  FFvv  ==  00   ((1166))   FFbb  ==  FFee  ++  ww   ((1177))           ww  ==  00..44  kkgg   ((1188))   Journal of Adva  n    c    eFFdbb  M==  aγγnff  u++f  aVVctddu   ring Technology ((1199))   ∑∑VV  ddTToottaall  ==  VVddii  ++  VVddiiii     ((2200))           rr  ==  2255  mmmm   VVddii  ==     rr22ll   ((2211))             ==   ((225522))  ((5566))             ==  110099..9955  ××  110033  mmmm33             VVddii  ==     rr22ll                           ==   ((225522))  ((3333))                           ==  6644..7799  ××  110066  mmmm33   ∑∑VV  ddTToottaall  ==  110099..9955  ××  110033  mmmm33  ++  6644..7799  ××  110066  mmmm33                                                     ==  117744..7744  ××  110033  mmmm33   WWaatteerr,,  γγff    ==  99..8811  ××  110033  NN//mm33  66  TThhrruu6ssttTeehrr  ruster           ==  1100..2288  NN      FFee22  ==  FFbb  ––  ww   ((2222))                 ==  1100..2288  ̶  ̶ ((00..44  ××  66  ××  99..8811))                 ==  1133..2266  NN           JJ33FFmmoo..iiuu22ggiirrll..uunnll44iiaa  rrmmFFi3Fllee  siioo  .eei11ll2ffgitt  tt00AA.neeeeu4  rrddrrssr..m  vvhh   CCeaaoonnioo1wwlFccnnl0eeiissddttmlaa    tsttMMeiihhhennraaeetoeenne  Cwffrruurrr  o.ffeesaaeenccttt  tbbuuharrooeiiiddnnnfggyyer  TTerddeeeiiccaahhbggnnorrooaalldoommggyyy  ffdooirra  FFgiirllttaeemrr  ccoofonnrttaaFiinnileetrressr..  TTcohhnee  tuuanniniitte  iirsss  ii.nnT   he unit   ((((22223344))))     ((((22225566))))     FFiigg  FF∑∑ FVFWVW      uu   bbbbdd              FF========rr====  ee  vv        4422  FFγγll11==  ××1166..eeff..  44    ww550000++00++44kk    ::    ××VV  66××wwggFFhh      dd  ××11ii    ll  99tt11ee0000rr  ××66    CCmm  99oo00mmnn   tt33aa   iinneerrss  FFrreeee  BBooddyy  DDiiaaggrraamm      mNN  WT  TW  F  F                eeIoo         22eeSTT        =  tt==        ww  Saa======== ==   N  llFF        2  44tt22112244  WWoo3wwbb:3333884433  ––nn1...11..33..115ee669  6699    ww....7++iitt118112266  ggooNNk  555  335599WWhh  -g  KK33      3NN++  tt     221,,iiNN          ll33  ̶̶5++((oo733    11WWgg....6655rr3344aa    ××88mm++  V    99++WW,,..o    8811l4411.00  1))..  22088  ++N  44o33...6611155Ja   nuary - June 2016    ((2277))   10

   43.615 N  Fe2 = Fb – w  Design and Development of Underwater Robot for Cleaning Pr(o2c7es)s        = 43.615     ̶ (1.5 × 9.81)        = 28.9 N  Total weight,  WT = W1 + W2 + W3 + W4        = 143.69 + 33.648 + 10.28 + 43.615        = 231.233 N  Newton to Kilogram,  m =  23.57kg      (a)                            (b)                                      (c)  FiguFrieg 1u1r:e C1l1e:aCnlienagn PinrgocPersosc TeesstT  est DurinDgu  trhine gprthojeecpt,r  osojemcte,  spormobelempr oobclceumrs owchcuerresbyw  htheer epbryestshuerep  rheuslsl utrheath  ullcontatinheadt  caonn etlaeicntreodniacn pealret cwtraosn bicurpnat rdtuwe atso ba uleranktadgue e otcocuarrledak daugreinogc cthuer redexperdimuerinnt gast hsheowexnp ienr iFmigeunrte 1a1s. sThhoisw dnisaisnteFr ilgeud rteo t1h1e. mThalifsundcitsioanst eorf tlheed  towholeth seysmtemalf oufn UctCioRn. Aosf ath reswulht, othlee swyhsotelem eloecftrUoCniRc .coAmspaonrensut lnte, etdheedw toh  olebe  reepleacetrdo nwicithc o mnepwo noennets.n  Teeod  aevdertto  tbhaet rceaptlaasctreodphwei tfhronme whaopnpesn.inTgo  ianv  ertfutureth, matorcea tgalsuter oanpdh eadfhroesmiveh aanpdp oenthienrg neincesfusatruyr eo,bjmecotsr ewegrleu aepapnlideda. dThiess  ive  and other necessary objects were applied. This project did not cover the effectiveness of the cleaning process ,yet can be proposed on future works. This project focused more on design and development of UCR. 4.0 CONCLUSION The underwater vehicle is one of the important developments in underwater research. This continuous research will guide the human being to know more about underwater lifestyle and based along the knowledge gained, the human can constantly make up new technologies that hold the capabilities in terms of an underwater condition. This technology will enable human to explore, visit as well as exploit place that humans could not otherwise go and replace the human job for cleaning tasks in order to avoid human life risk. The main objective of this project has been achieved where the Underwater Cleaning Robot (UCR) is able to do the cleaning task and some underwater motion as required. The UCR functionality such as forward‐reverse left and right turn, float and submerge along with its cleaning method can be easily controlled by using a PS2 joystick controller where the PS2 joystick controller is wired to the PSC28A main controller board. The ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 11

Journal of Advanced Manufacturing TechnologyUCR can submerge into any condition of the water that is less than 3‐meter depth. The Solidworks software and mathematical analysis forevery part in the UCR are useful in designing the UCR. This designgives more clarification on how to build the cleaning method for UCR.Hence, several ideas are produced in terms of cleaning puddle water,collecting garbage at the bottom surface of a pool or cleaning the sidewall of a pool. In future works, the effectiveness of the cleaning processof the UCR will be tested.ACKNOWLEDGMENTSWe wish to express our gratitude to Universiti Teknikal Malaysia Melaka(UTeM). Special appreciation and gratitude to Underwater TechnologyResearch Group (UTeRG), Centre of Research and InnovationManagement (CRIM) and to Faculty of Electrical Engineering fromUTeM for giving the financial and moral support in completing thisproject successfully.REFERENCES [1] S.W. Moore, H. Bohm, V. Jensen, “Underwater Robotic Science, Design &Fabrication”, Marine Advance Technology Center, MATE”, 2010. [2] M.H. Lee, Y.D. Park, H.G. Park, W.C. Park, S. Hong, K.S. Lee, H.H. Chun, “Hydrodynamic Design of an Underwater Hull Cleaning Robot and its Evaluation”, Pusan National University, Busan Korea. [3] H. Albitar, A. Ananiev, I. Kalaykov, “New Concept of In‐Water Surface Cleaning Robot”, School of Science and Technology Orebro University Sweden, 2013. [4] Y. Li, K.M. Lo, “Novel Underwater Vehicle‐Manipulator for Cleaning Water Pool”, Department of Electromechanical Engineering, University of Macau, 2009. [5] D.M. Kocak, J.W. Neely, J. Holt, M. Miyake, “A Specialized ROV for Cleaning Groundwater Recharge Basins”, Harbor Branch Oceanographic Institution, Engineering Division, 1999. [6] BS SolidWorks “http://www.solidworks.com/”, 2013 [7] Cytron Technologies PS2 I/O Converter PSC28A User Manual. “http:// www.solidworks.com/” November 2013. [8] Z.M. Sani, A. Noordin, A.M. Kassim, A.Z Shukor, “ Microcontroller Technology 2nd Edition”, Universiti Teknikal Malaysia Melaka, UTeM, 2012.12 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Design and Development of Underwater Robot for Cleaning Process[9] M.S.M. Aras, F.L. Sudirman, F.Ashikin Ali, F.A.Azis. SMSSA.Hamid, A.S.M. Nor, L.W. Teck, Faculty of Electrical Engineering, UTeM. ʺUnderwater Technology Research Group (UteRG) Glider for Monitoring and Surveillance Applications”, 2011.[10] Mohd Aras, Mohd Shahrieel and Ab Rashid, Mohd Zamzuri and Azhan, Ab. Rahman (2013) Development And Modeling Of Unmanned Underwater Remotely Operated Vehicle Using System Identification For Depth Control. Journal of Theoretical and Applied Information Technology, Vol 56 (1). pp. 136‐145. ISSN 1992‐8645.[11] Ali, Fara Ashikin and Abdul Azis, Fadilah and Mohd Aras, Mohd Shahrieel and Muhammad Nur, Othman and Shahrum Shah, Abdullah (2013) Design A Magnetic Contactless Thruster of Unmanned Underwater Vehicle. International Review of Mechanical Engineering (I.RE.M.E.), 7 (7). pp. 1413‐1420. ISSN 1970‐8734.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 13

The Influence of Extrusion Die Angle During the Hot Extrusion Process of Al Alloys THE INFLUENCE OF EXTRUSION DIE ANGLE DURING THE HOT EXTRUSION PROCESS OF AL ALLOYS H.R. Rezaei Ashtiani Department of Mechanical Engineering, Arak University of Technology, Arak, Iran. Email: [email protected]: One of the most important parameters for the hot extrusionprocess effecting the deformation force, material flow, microstructural andmechanical properties of the extruded material is the Extrusion Die Angle(EDA). In this investigation, the effects of EDA on load, material flow andmicrostructure of hot extruded commercially pure aluminum has beenstudied. The finite element simulation were carried out using Deform 3D.Finite element modeling shows that the values of the equivalent plastic strainand its distribution, flow material and deformation forces depend extremelyon deformation temperature, reduction and EDA. To estimate the reliabilityof the numerical analysis, the FE model was validated using experimentalresults. The results showed that the lowest extrusion force occurs in anoptimum die angle for each reduction. Optimum EDA obtained 16, 18 and 23degrees at reductions of 50%, 60% and 70%, respectively. Also, material flow,inhomogeneity of microstructure and the equivalent plastic strain increaseswith increasing of EDA.KEYWORDS: Die angle; FEM; Hot extrusion; Material Flow; Microstructure;Reduction.1.0 INTRODUCTIONThe advantages of aluminum and its alloys make it particularlyappropriate for complex extrusion processes. High ductility and theideal ratio of strength to mass density in aluminum alloy preparevarious applications in automotive and aircraft manufacturing, andalso in lightweight construction [1]. Nearly 80% of all metals productsconsisting of aluminum alloy undergo hot forming during somepart of their processing history [2]. Hot deformation processes are afundamental step in the production of engineering parts which requirenot only dimensional accuracy but also suitable microstructural andmechanical properties with minimization of load and energy. Thereforeinvestigation of materials behavior during hot deformation is veryessential.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 15

Journal of Advanced Manufacturing TechnologyHot extrusion is one of the most important processes used to producealuminum alloys. Minimization of load and energy, deformationhomogeneity and controlling of microstructure of the extruded materialare considerable aspects in die design process. It is commonly acceptedthat product properties are strongly correlated to microstructure.So it is of paramount importance to understand the way in whichthe structure is modified and how the forming parameters (i.e. diegeometry, reduction, temperature, etc.) affect these modifications.Simulation of hot forming processes with application of finite elementmethod (FEM) has been the subject of many recent works. Hightemperature and large plastic deformations of the extrusion processeshave led to developments in the microstructure of the material [3‐7].Joun and Hwang [8] applied a finite‐element‐based optimal processdesign technique in steady‐state metal forming to die profile designin forward extrusion. They predicted the die profile for minimizationof forming energy for various process conditions and materials. Leeet al. [9] designed the optimal die profile for hot rod extrusion thatcould yield more uniform microstructure. They applied the flexiblepolyhedron search (FPS) method to obtain the optimal die profile, andto show validity of result of their study, performed a hot extrusionexperiment.Byon and Hwang [10] presented a process optimal design methodologyto minimize the punch force in steady‐state forming process byusing the finite‐element method. The influences of die profile on themicrostructural changes of the hot extruded sample have not beeninvestigated in the previous researches. In the meantime, the effectsof other parameters of hot extrusion process including temperature,friction coefficient, reduction and etc. have been disregarded in theprior investigation.In this paper, the optimum angle of conical die is achieved using finite‐element method for hot extrusion of pure aluminum rod. Also, thesimulation results have been verified by experimental data, and finally,microstructural changes have been investigated for different die anglesand various hot extrusion conditions.16 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

2.0  2  . 0   M    A  MTHAThETeMIHnflEAueMnTceIAoCfTEAxItLCru sAMionLOD MiDe AOEngLDle DEuLri ng the Hot Extrusion Process of Al Alloys  2.1 2.1MecMhaencihcaanl iMcaol dMelo del    Ap22rso.. 10csApeh rssoos wc siehMMsnso  stewAb hciyeTsnh    aHEtsbhnuqyEeim. c  MEs(a 1uoql)Amf.M   tT(th 1hooIe)edCf    teatiAhdlhceteeLu  aaaiMldc l tweuwOaoaloDr l rwkwkE,o ,LoW rWrkki,,a  ,,W t hWtoai,a  t,t c hwotoamo tu cpwolldmeo tubepl eldte h rtbeee qe  te uhrxieetrrq eueudxsi tirforeoundrs   ifoonr   tdthhpsAoeeh rs  roawstdtehphchsdooeheeea usr  ropwksscnewehh ddioa saancuagrpnhtknnahbega tidea yn encoagssghrinEautne a tiuqmf n nriotn.nsihgrcw(ot ee 1t tufi ah)roiantnneihbntcw th est aetbieeahbdoiendesn atdc teewc aebnaetbdeuflecoso etewadfewrn lnemoof erfwwcfroiae ekcfoornt tr,imorri ioWowkckfna tn ,fioiat,,ro WinraWitonkchndnt a ard,ai a ,to [tnnoWt1niwoddon1 rl] a ho csti.[n nuooo,1 dmomhlW1dl] ospi.of mnb,,gl  eaheW eotnornegfedm,ee qt ao nthounhuegeideosre  e eunwftdxlhseoot eofrfwro  luuwkor,ss wotitt oofhhr,ln  keeo wto,                                 UwWr   W   e   no  daa   l  r+ui  Uk kWWn W enadai ligta+ihkanWWWeietn  fioitfs+dhtrWWeefuWa rrinfi lrdc w wte i Waa oo ln nrr    twk  eb  ,  do  e    ttr  h d wk  e  e,  e    f  fteo  hr  nri  e  cm    wt   f i a ro  oi t n  cri  otk     ian  o  an , n   nd W    d   a  r r ne t[ odd 1 o  1u rl ] nes.,ddWuannf,td aaw nnodtr  wtkh oderew kp oedr(ne1kdp)  teoo(n(1n1dd) )  oon  dcdabUoniieneentg  wltlidcdaaaekoeniinc.eeentgAg   nttlalaahaseernntc;e.ie h tggsa iAeilalod seebrs ed;.cew  e ailsaitAeeltowi a tbws ahirew esn oefit adtrwirnc t oklh ciemmet,so hea tananhercF t s l ecideettfgoharrfaiunroienerai r ms tcaldet ftnarc dii1ooenodFe, nmeit cafg mforncau feriodnFarcaeaeitd isg emefgeu1frnrisii,arecvt aet diwfel eoo un1rdnifri,tn te  arhf decfalroo rdi aidcfenrgnu te acfiitcarsovtrwie eneicegsoant,oa  siinw sovrfi,rrkneneiietstgcnh,dd h tw efieud rroipcicnientcoetedhcitannoriua loetid nncnanawt,gco siatoorlitnleneha rn;awkgdre, ess   ioitaenhrkge    dweicthrdeeaacscreeosan  wssethsa inlwet  hcthioleee f  frtihecdeie urnnetddouafnnftdr iawcntoitor  wkn ,otefrrrkimc  tte iiornmncar leinawcsroeesra kwsediste hcw rdeitaihes  eadsniewg lahen.i lgele.  TthheerrTeehfdoeurrenef,d ofaroner,t   wefoaorc rhek artceehdr murceitdnioucnrcet, iaotshnee,s rtweh  ieitsrh ea dniis e oaapnnt giomlepu.timTmh uedrmieef  odarnieeg, lfaeon,r gfeloear,c  hfor    wrmehdi niucwimchht ituiohcmnhe,  tt[toh1ht1eea] rlt. eowtiasolr awkn oiosr pkat  miims ianu mimminudimime au[1nm1g] l.[e 1,1f]o. r which the total work is a FiguFFriegig u1ur: reAe1  1t:y:A Apit cytayplp iccicoaanllci ccoaonln idcicaiaell d dieie  c[Ge1hqc[eGe21haqune]2raua:c[Gene] a1rthaq:reciae2atoaurtnci]elarnoa:tle arelyntsrlicir y,zaso tice,zelnotlcdrehysvotid he ,zev c eebreothdiybhrnvhoi  yenegto bsr g thtitysdrnhtot ederghetsesfe  sesotstfeds,rhsro  eee,mevrssfmsavstoaser,latrt aua rilmvtiouaesinatniosaern,l sn t uav,ibiosevantebnssrar,h tey  arvrhayibiasannvaiteirngrn vihyoag iraiiiroannnrv irtang  ioeowt f oreiwr anif admti noaedmwenf de e tirde aadmatrntlaneaesdetl ng mestr agaemaptlsneanes pesndg mared aeraarpeasnrta  ueeladtgalrulro riglaervyoeati.e veys ul.gl nesroTiaen vyThar.aes heesar n   Teesa harees      JournZal ofZ Adevxapnc(eeRdx HpMT(a)RnuHTfaAc)t(usriinAngh(Tsienchhn)onlo gy)n (2)   (2()2  ) 1  Z 1 n  Z 2 n 1 2    A   A  1    (3)  where     σ  is  the  flow  stress,   T  is 3t h  e 3a bs olute  temper ature,  Z  is  t(h3e)  temperature compensated strain rate and commonly known as Zener‐ Hollomon  parameter,  A  is  a  constant,  n,  ε,  ΔH  and  R  are  the  power  exponent,  the  strain  rate,  the  activation  energy  and  the  universal  gas  constant,  resIpSeSNct:i1v9e8l5y-.3 1T57he  bVehola. v10iouNr oo. f1  aJnan  uaalurym- iJunnuem20 1a6lloy  during1  7 extrusion  as  a  thermomechanical  process  depends  on  temperature,  strain  (reduction)  and  strain  rate  (ram  velocity),  as  described  by  Eqs,  (2) and (3). 

1  Z 1 n  Z  2 n     A   A   1     (3)   wJhouerrnea lσof Aisd vtahncee dfMloawnu  fsatcrtuersisn,g  TTe cihsn otlhogey  absolute  temperature,  Z  is  the  temperature compensated strain rate and commonly known as Zener‐ Hollomon  parameter,  A  is  a  constant,  n,  ε,  ΔH  and  R  are  the  power  expwohneernet,σ thise sthtreaifnlo rwates,t rtheses ,acTtivisattihone eanbesorgluyt eantdem thpee ruantuivreer, sZal igsasth  e contesmtapnet,r arteusrpeeccotimveplyen. sTahteed  bsethraaivniorautre  oafn danc oamlummoinnluymk naollwoyn  adsuZriennge r‐ extHruosllioomn oans paa  rthameremteorm, Aechisanaiccaoln  sptraoncte,sns , dεe, pΔeHndasn  donR  teamreptehreatpuorew, er streaxinp o(nreednut,ctthioens) taranidn srtartaei,nt hraetea c(triavmat ivoenloecnietyrg),y aas nddestchreibuendi vbeyr sEaql sg, as (2)c aonndst a(3n)t.,  respectively. The behaviour of an aluminum alloy during   extrusion as a thermomechanical process depends on temperature, strain 2.2(reducMtioicnr)oasntdrusctrtauirnarla Mte o(rdaeml  velocity), as described by Eqs, (2) and (3).  Ev2o.l2u tionM  oifc  mroisctrrouscttruurcatluMralo dcheal nges  during  hot  extrusion  is  a  very  complicated  operation.  The  distribution  of  microstructure  through  cudrniossnEcdtseoovrescmiro rbtsm ilupeoucnatlntiitliocoioaeoarnnnxmnt edto rodaafuafln o mlsdompieo eneaxincgrclthaorrctoautnohinssognetiin rdoctlu.ehaniTtncle i thog pulcenterorhonsdan.pgolidTsetfcthihrretht iiixoiaobsetfnnurcs ugesa taix.euso ntissnordTeudno shshufdiaiesmori nniennicoc cvgdenara oiu‐mhreussi oetavnertsysaiuf c erocnioxatereuntm srcsr uecneiddsosotsiinehnosirtsrt‐naairoudtbiunbeielsg iyurefhaatoxuibrtconvrmlrnyadeo   roesysrf pomst‐eecxhtarnuisciaolnp  oropperearttiioesnsa nsduchhe nacse  mmaacyhinneincegs saiwtaatey etxhter arepcorsyts‐teaxltlrisuesdio  n layoepre. rations such as machining away the recrystallised layer. The  relationship  between  the  volume  fraction  recrystallised  and  the  hoTldhiengr etliamtieo niss hgiepnebreatlwlye erenptrheesevnoteludm bey tfhraec tJiMonAKre cerqyusatatilolinse cdlaarinfdiedth  e byh Eoqld. (in4)g [1ti3m].e  is generally represented by the JMAK equation clarified   by Eq. (4) [13]. XV  1  exp 0.693 t k   t50                                                                              (4)  (4) Where XV represents the static recrystallized volume fraction achieved at the annealing temperature, t is annealing time, k is the AvramiWat hesttxehapreteio c anXnerVenn rcteerapwylsriinettahsgle lanitzetcasmo ttimphoeenmr .saotTtanuhtlrieycer ,rer eet cparirosye rstattenawdlnloievzaakelldiiunn evdgo sotlfuiom2mf,emet,5  0fokrid asicesttl hisotehnceto ia nmcAsheivsierttioavnmeg5d0i  o%fexpemonpeinritc awliathn da pchoymsmicaolnmlyo rdeeplos rftoerdt hvealcuaelc oufl a2t,i ot5n0 iosf tth5e0 .tTimhe etom 5p0ir%ic alstamtico drelcrbyysptaalsliszeastitohne.  eTvhoelruet iaorne otwf osu  kbisntrdusc  toufr  em, oadnedls rceolantseissttihneg foinf alemmpiicrricoaslt rauncdtu prheywsiictahl smtroadine,lss ftroari nthrea ctaelcaunldattieomn pofe rta5t0u. rTehbey emrepgirreiscsailo  nmoodf etlh ebyexppasesreims ethneta  levdoaltua.tiTohne  oofn  slyubasdtrvuacnttuargee, oafntdh irsemlatoedse  lthise iftisneaal symiucrsoagster.ucture  with  strain,  strain  rate  and  temperature  by  regression oufs att5hg0ee.  eAxpde0aribmZecnetxapl dQRaTtreaax. T he only  advan tage o f this m odel is  its eas((y55) )    A,  a,  bb’’,  c  are  constants,  d0  is  the  initial  grain  size,  � is  the  equivalentt  ssttrraaiinn,, QQrexreixs  tihs etahcet ivaacttiiovnateinoenr geynfeorrgrye cfroyrs tarellcizryastitoanll,izRaitsiothne, uRn ivise rtshael   guansivceornsaslt agnats,  Tcoanisstatnhte,  Taan nise atlhine gantenmeaplienrga ttuerme paenrdatuZrei santhde  ZZ  iesn  tehre‐   Zener‐Hollomon parameter.  For  the  physical  model,  t50  is  calculated  based  on  the  stored  energy 18(PD) and the IdSSeNn:s1it9y85 o-3f1 r5e7crysVtaolll.i1z0atioNno .n1ucJaleniu a(NryV-)J:u  ne 2016   C  1 1 3 (6) 

  ts5t0rainA,d  0QrexZ  ise xtphe RaTcativation  energy  for  recrystallization,  R  is  the     uAn, iva,e rbs’,a lc  gaarse  constant,s ,T da0  iiss  tthhee  ainintieaall ignrga itne msizpee,r a�t uisr eth  aen edq uZi visa ltehnet     AsFZustotr,enr arnaai iv,eint nerhb,‐r ,e’ Hs,Q  aQcpolr e rhlaexlgx yor aeismiss is  cco coatnothlnTh  nesphmes eta atIoaarnancadfnclttumesttiei,v,ln v e,caT deatttea0ot5i fr0io i oE.isn isxn s t t r thuechesenaieno le niceanruDrgniglityenaiyaA te elnfa fdogglolire rnr bDa grauire nrsetice necsrgdmryityz hspoesettn,aeH arl �ollattli hiEztizsuxeaa tr trttiueshiost oeionaon nrn,e ,eP dqdRrRu o c Zi eevsi nissias ose lf etrAtthgnhhleytAee   l  loys   u(ZPneDinv) eearrn‐sHda lot hglleao sdm econonns ispttyaa rnoatfm,  rTeecater yris.s  ttahllei zaantinoena lninugcl etei m(NpVe)r: ature  and  Z  is  the   ZFeonrHe  troh‐Hlel oopmlhlooymnsiocpanal r pamamroaedmteelre,.t et5r0.  is  calculated  based  on  the  stored  energy      (F    wA (P   oP     sDh r  D   )  e aF) sttta rt5n5hoha50en00dnroe dC wdtt hp/ht MnMMtheMheh eyGpeGCGbdGC CsBdBB hBydeiP PcyeiP nDesDanDsEs nliasiq cst imNa.ciytNN 1ty1al1Vy(VooV lm3o idfo)bf1 o1erf1 r3tr e3lda3rh ,ec eteceritclor5y ,r0yrns tyes5ti s0scatcta oirl aslclynillaczlsisizlataztcaaaltauclitnltoiuliioat nzol.tna enent ddn eun d uucgbclbrcael aleasieiisen(i e(Nd  (NdN sVoiVo)zVn:) n)e:  :  ttihhsee   essxt toporrreeedsds eee ndne (e(r(a66rg6s)g))y    ya((  P6)D)  fwunhcetrieo nC /oMf iGnB iitsia al cgarlaiibnr astizioen,  sctoranisnta, nsttr.a  in rate, and temperature.       wAf   wT Afu   u   hsh  nh s  n  e e cedwwAfsdc drsturhrkrtieheresehhinoexoxi ox oCneenacwsnwrrte2h /iee,o nMata ooonaihf2 Ca2cfn2w  dGd2bi ds2b,i/n0B,h0  oynhn0Mh n2yh2ioi2f its2 tf2iEGb,in ,i Ean nnaB2ac2qygn2lq il  i.crta2g sm .mg,aiaEm n(r2a2aicl(r23qadneil3eae)biac.xg)x  i nxmar nnpgpt(rp atlh3ds arih2stQiob)eiQ iQizeanmoz wr22et r2arnehsRre,2RettR , ieeh s icTaczTmsoTcto rretrrnriyerna,ayseastss icmcsitendttcotrnaccarra,yaenl  ,ain ls  lat ssssiliettctnilzttr. zarrar ec,aielianoadsilbdinilttn nezr.  cgsder agrot ardi aarnantbatneiseyginr,ttn ,a rsa a i aa.tsnns esiniotndi,z dsztae .het s nte eieidmzisrmse m tpepeeaixe mxselrp rpapreearteqxteuesuprusrsarseraeetee .tdu .dis o rs ((eane(7a77.sd )s) ) a   asaa(   s7)a  pwrhesTeerhnee taek2d,i  nhine2,t Eincq2s,.  co( 8af)n.g dra min2 agrreo wmtahteirsiadl ecsocnrsibtaendtsb. y isothermal equation as wThheepr reke iasn2ee,n thitc2e,sd n  oi2n,f  cgE arqna.id(n8  m)g. 2r oawret hm aist edriea slc croibnesdta  nbyts .i sothermal  equation  as  Tphree skeinnteetdic isn  oEfq  g. (r8a)i.n    growth  is 1described  by  isothermal  equation  as    p  ow    r  f   h e    t sed,awtdd e,rwgrgngeghwegg htedmehirdlgiesagl ds tditdd dtn0em0dm0gmggred gg0Eing0ad qgoilaeas.sait gns ge(gttct8otshteoe)he txex.ntex ep hpsspgegtrta rahfnaQiieQQnntinsgfg ag,idRlnRdaR iTaagTniTalmrdmageiQr1en1tmamemtg ie r sn i  r is pzspaerizric oiateoirfvar tt eafottrtoe i togrhtnhrgeoe rehwonh owteolhrdltg dhiayninagondg  fpd phgeheorrriaoloidilonddid(n(,i (8g8 n8,ga))r)ag  g o t gaiwtmainmntdehd(e  .8   mo) f mw haere  dmgga dteerniaoltse sc othnes tfainatsl,  garanidn  sQizge   iasf tearc tgivraotwiotnh  aennde rhgoyl doinf gg triamine   wgorfho tew2,r .we3t hhd . ig lgs tdF deinn0goi ittsee tsEh lteeh mger efaininnta Mdl igaormdaeienlti ensrig zper iaofrt etro  gthroe whothld  ainngd  pheorlidoidn,g a gt iamned   o mf t  ,T awhrehe ilmFstia ndtie0tgre iiasEl stlh eecm ogenrnsatiannM dtsioa,d mealenitndeg r Qp(rgFi oEirMs  to)a ctithsiev aohtnoioeldni onfegn tpehreegryiom doo, fsa tgg arpnaridenc  ise  m g  g   rr oowapmfdtwhorratereetoht mhtreg.hm .m,r  io navoadmgamtsercsiretooiotcanouhladsssan itntmuaciioldcooyannydzlssete,cthlaaotsenhnulthedposa,laft evooddaercmanaobndinnedn de5tgQrmn oigpnli pcrvtrirohsoooce lspevatmsorecsussti,ecicvvwdrtouaehrtsraiyitenocrhnurdlae cisrtisegpnuneoutreeansdgrlusgereeaayfvlout loeyrnodlmudfn taeioingtronitrovn‐oalan.iirnnsFi. eoETauMros,    5   Ienxtrthuissiownoprrko, caes3sDfomr aoldueml ihnaus5m beaellnoycsonusstirnugctfeidnitteo simulate the hot element program DEFORMTM. The billet is assumed to behave as a thermo–elastic viscoplastic material with temperature‐dependent elastic modulus and poisson’s ratio. The range of temperatures, strains and strain rates experienced by the material during the extrusion process is large, hence ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 19

DEFORMTM.  The  billet  is  assumed  to  behave  as  a                           thermo–elastic viscoplastic material with temperature‐dependent elastic  modulus  and  poisson’s  ratio.  The  range  of  temperatures,  strains  and  Jousrtnraalinof Aradtveasn ceedxpMearniuefnaccteudri nbgyT etchhen omlogayterial  during  the  extrusion  process  is  large, hence it is necessary to define the plastic behavior of the billet as a  itfuisnncteicoens soafr ytetmopdeerfaintuerteh, estpralainst iacnbde hstarvaionr roaftet.h  eTbhiilsle wt aass adfounnec tuiosinngo fa  tehmyppeerrbaotulirce s,inster aeiqnuaatniodns, tsrhaoinwrna tine. ETqh. i(s3)w, washdicohn reeluasteins gthae hstyepaedryb ostlaicte  sifnloewe qsutraetsiso no,f sthhoew  mnaitneriEaql .to(3  )t,hew  hstircahinr erlaattee santhde  tsetmeapdeyrastutartee  uflnodwer  isastbwsredeahhesirasfciovhgore ifmid tat heisss doea dl. mireIditfga.oiitsdrem rasiloeasdlloitd. oaI.t st sihsue maslsteroda aitnshsaruatmtteheeadn dtdhieateta mnthdpee sdrteaiemt uarnmedau tsnetdreimearl smwbhaetihecarhivaietls  The  geometry  of  the  billet,  stem  and  die  of  hot  extrusion  at  the  Trheedguecotimone trvyaolufeth  oefb  i5ll0e%t, ssthemowan dind ieFiogfuhroet  e2x. trTuhsei odniaet  twhiethre  dau  rcotiuonnd  voaplueenionfg5 h0%ad sah boewanrining Fleignugrthe o2.f T2.h5e mdmie. with a round opening had a bearing length of 2.5 mm. Figure 2: Billet, stem and die in FE model. Figure 2: Billet, stem and die in FE model.  The process was carried out at three initial temperatures of 350 ºC, 450  ºC and 550ºC. Also three reductions of 50%, 60% and 70% have been studied. The density of the billet was assumed to be constant at 2710 kgm‐3. Coefficient of friction depending on applying lubricant comes from test conditions. 20 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

ºC  and  550ºC.  Also  three  reductions  of  50%,  60%  and  70%  have  been  studied.  The  density  of  the  billet  was  assumed  to  be  constant  at  2710  kgm‐3.  CoeffiTchieeInnftl uoenfc efroficEtxitorunsi odn eDpieeAnndglienDgu roinng  thaepHpoltyEixntrgus iloun bPrroicceassnotf AcloAmlloeyss  from test conditions.    33..00 EEXXPPEERRIIMMEENNTTAALLP PRROOCCEDEDUURERE  33..11    MMaatteerriaial l  TThhee cchheemmiiccaallc  coommppoossitiitoionno  of ft hteheA  A1A017007a0l uamluimnuinmumal laolyloeym  epmlopyleodyed  iinn tthhiiss wwoorrkk iiss ggiivveenn iinn TTaabbllee1 1..    Table 1: Chemical composition of AA1070  %Ga  %Ti  %Cu %Fe %Zn %Si %Al 0.010  0.0126  0.0102 0.199 0.0102 0.0788 99.7 AAlluummiinnuumm  bbiilllleettss  wweerree  ccuutt  ffrroomm  aa  bbaarr  ooff AAAA11007700 wwiitthh 1166mmmm iinn  ddiiaammeetteerr aanndd 3300mmmm iinn hheeiigghhtt ((tthhaatt wwaass rreedduucceedd bbyy wwiirree ddrraawwiinngg)) ttoo  bbee uusseeddf ofrorth  teheex  epxepriemriemnetsn.tSs.a mSapmlepslwese rweefrires tfiarnstn eaanlnedeaalted60  a0tº C60w0 itºhC  twwiothh towldoi nhgotldiminegc toinmseis ctionngsoisfti5nagn odf 550 amndin 5a0n md tinh eannadi rthcoenol eadir scooothleadt   tswo othinatit tiwalog rinaiitniasli zgersaionf s4i0zeasn odf 24000 aμnmd 2w0e0r μe mob wtaeinree do.btained.    33..22  EquEiqpumipemnte nant adn EdxEtxrutrsuisoinon ddieie    JoulhdhTFahdFThl aurunioaihninaoihgbegbevdtaevdte,ur,lur e  ee i ccoeriscccrsx cfoboexcob eoacAatnhent nhnenr3nrd3etetuetet.utvat.anaman dma TdiiwTiniwnn cnenhacechaeoaedeotaedrtrdrsirnreirsnce  ,.cu,M.e su eas p apt dnt dnparcuprcundiuodipuoanpuanecnelgcnfcgliractriitrehiecrchee catidda,iadudn,amn mllrll  iofmiio ftmndotdo iwiwogaroiaariaeflTeefn letnst  ershttruhttcu hew eehhaweaamaenmne lnrilroilt delptyldedphdyohddegi eu i ueouyareouarp‐anpc‐an cshstphttpet ueiautieatotehotrlhrrl nfrenuefeue s sass sa oshosh nesnlefulofuidogid gk5rek5erl fl0eseef0iseaina%n  % acFoaFco en.Enfte.Etfsh dTh sdMT1M1i hio0 shro0sr,efi  ,eifpnsp ns 2 2tdtrdtgtr0hgu0houiosisee degead.ga.‐‐  ynrSsybnrSsbaeadae iadiimltmimltsmls l3 ec3ec ..p0sotp0s otAhA hln landeadoe5osn5ssensweiwi dgs gdwgsgwtnrtnlr slsedeaedea  eorisieorisineessnfeessf         7   Figure 3: Schematic diagram of the die‐set, (1) upper shoe, (2) holder Figure 3r:i nSgc,h(e3m) pautnicc hd,i(a4g)rcaomnt aoifn tehr,e( 5d)ied‐iseeatn, d(1()6 u) plopweerr sshhooe,. (2) holder  ring, (3) punch, (4) container, (5) die and (6) lower shoe.   Thebestresolutionofmicrostructures forinvestigationofmicrostructural cThhaen gebseasnt d dreestoerlumtionnat ioonf of mgriacirnostirzuesctoufraens nefaolre d ainnvdehstoitgeaxtitornu deodf  microstructural changes and determination of grain sizes of annealed  and  hot  extruded  samples  is  achieved  by  the  examination  of  electrolyticaISlSlyN : a19n8o5d-3i1z5e7d  saVmolp. 1l0es  Nino . 1a  Jpanoularryiz-eJdun  eli2g0h16t  microscop2e1  (PLM).  Figure  4a  illustrates  the  die  set;  while  Figure  4b  shows  the  specimen before and after the tests. 

Figure 3: Schematic diagram of the die‐set, (1) upper shoe, (2) holder  ring, (3) punch, (4) container, (5) die and (6) lower shoe.     JoTuhrnea l ofbAedsvt ancreedsMoalunutifaocntu rinogfT  ecmhnioclorgoystructures  for  investigation  of  microstructural changes and determination of grain sizes of annealed  and  hot  extruded  samples  is  achieved  by  the  examination  of  esalemctprolelsytiiscaalclyh ieavneoddibzyedt hseamexpalmesi niant ioan  poof laerleizcetrdo lylitgichatl lymiacnrosdciozepde  (sPamLMpl)e. sFiingaurpeo  l4aar izileludsltirgahttesm  tihcreo  sdcioep  see(tP; LwMh)i.leF iFgiugruer4ea  4ilbl usshtroawtess  the  sdpieecsiemt;ewn hbielefoFrieg aunred 4abftsehr othwes ttehsetss. pecimen before and after the tests.           (a)                                         (b)  FigFiugruer e4:4 :EExxttrruussiioonn ccoonndditiitoionn: (:a ()ad) ide‐isee‐tseatn dan(bd) (bbi)ll ebtilalnetd and  ddeeffoorrmmeedds asmamplpele 4.0 RESULTS AND DISCUSSION  T4.h0e   inflRuEenScUe LoTf SdiAe NanDgleD  oInS CmUaxSiSmIuOmN  extrusion  load  illustrated  in   edmFbosFrdtiTtsashoeppxpeiiecihggsieapee occtnetuuutioeerhebacimleddrrjirmrevnotuneeadis uinmgos fssuoa55(lomtcleifuFmune,em,fldt 5uE, enc asah. 0ienftdt Mtd5elfDom a ac0lrrreaiorlsereoe)eumdt mua dd mwhec dodimaduu/o atfithstn.afavnccoFh /efidbgtstted ciecaiiatAegiilhoo.rthileep cut ieAnnl,eti.rtsn r aoya j hosouoeosftnnnApeo i,o.iffsdg m,dt erstf5m55li e  i rieaeid00stxlwait a %%aisatchcotxec irhhenlinem ci esiaapaamicg osa cnnntomutl rhrsuedndgdotlfuc sfaahmold balr.itettxtee rtovnhihhiiaatocemmiceeteeibroanohxe  x ittuuut neltpmeeafrihssm,rmmtuet dre oyiaeressdsippxxm isfieemiForictueexfomh oeaifnrrtlefgepmiaatntr unssrhulutttgoe mutud  irdsaflnsaerreiioe( Fl deotee,,Frci Fde ntd girEooihtxtiaeasihufgfMleteta ncoreruaa44rsauagea) e55redn mn.adlse00 dieiing,sººehobi iCC5dnll laaneeoatacli nhvus naamaas c.eeilsdnnugoomotr utddl.snhpreaemeAua cp atd,ppsi tlltri.lim  euauu sstoDd itd otnncpusith,oeauah ccemiiidnhnhnnaeesrt            (a)  22 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016   (b) 

The Influence of Extrusion Die Angle During the Hot Extrusion Process of Al Alloys   (a)    (b)    (c)  FigFuigruer 5e:5  :InInfflluueennccee ooff ddiieea annggleleo nonth tehme amxaimxiummurmeq rueirqeudireexdtr uesxitornusion  lolaoda dfofor rddififffeerreenntt vvaalluueeo offr reedduuctciotino:n(:a )(a5)0 %50,%(b,) (6b0)% 6,0(%c), 7(0c%) 70%   The influence of reduction on the amount of required maximum load   JouioaiTaTinnrnnpnnhaccdatdbTerrli eml a eoeioaofban .uAspp slfeeedm2lttus.ivis.mm a e2wwnIdn.utuci eiciItmmtdeiethhs M   i oaidiscdnanfnlni cicecegruerlar elfeeeaaerdaaaca n.turnstsughiIcigrtnnlnitahelnigegto ga ar notToterhfe festsoc heutsahtnhuh enml taeoelteltame horedrmgeedeo ycd dfouoaruufumonnrccnmodttot timiiouo tootinfnnoh ftt neraha re o,mmeesdfdit ouomhsruueuicecmuqtnntiluiototuao..pint lnriat eoitcdmcniaoa  nmunnis m aaaipxsfsffrfiemeepdccsrituetee nmsooteanne nnl dottgt ehahliddeene    optimum  die  angle.  In  a  same  condition,  the  optimums  die  angle   TaTbalbel e22: :RReedduuccttiioonn eeffffoeoepcpctttstismiom onuunmt mht9ehd   deiree irqeae unqaginurleegidrleemd   amxiamxuimmuloma dloaandd and  Amount of reduction  50%  60%  70% Required maximum load (kN)  30.62  42.19  55.25 Optimum die angle (deg)  16  18  23 Figure  6  shows  distribution  of  the  effective  strain  at  different  regions of  deformation  in  the  half  cross‐section  of  hot  extruded  billet.  As illustrated  in  this  Figure,  the  effective  strain  has  a  non‐uniform distribution in the deformation zone.  23 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Optimum die angle (deg)  16  18  23 Journal of Advanced Manufacturing TechnologyFigure  6  shows  distribution  of  the  effective  strain  at  different  regions oFf igduerfeor6mshatoiwons dinis ttrhibeu  htiaolnf ocfrothses‐esfefcetciotinv eosft rhaiont aetxdtirfufedreedn tbrielgleiot.n  As os fildluefsotrramteadti oinni nththise hFailgfucroes, s‐tsheec tieofnfeoctfihvoet  esxtrtrauind ehdabsi llae t.nAosni‐lulunsitfroartmed diinsttrhibisuFtiognu rien, tthhee defeffeocrtmivaetsiotrna iznonhea.s  a non‐uniform distribution in the deformation zone.    (a)  (b)  (c)    Figure 6: Distribution of effective strain for die angle of (a) 10º, (b) Figure 6: Distrib16uºtiaonnd o(cf) e3f0feº cintivthee sdtreafoinrm foatri odniez oanegle of (a) 10º, (b)  16º and (c) 30º in the deformation zone  As can be seen from Figure 7, the a mount of EDA can strongly controlAths ecamna bnen seereonf fsrtoramin Fdigisutreib 7u,t tihone amndoustnrta ionf iEnDhAom coange sntreoitnyg. ly control the manner of strain distribution and strain inhomogeneity.       Figure 7: Effects of EDA on the distribution of effective strain at the Figure 7: Effects ofe xEiDt pAo soitnio tnhoe fddiesftorirbmuattiioonn ozof neeffective strain at the  exit position of deformation zone   The amount of effective strain inc reases with increasing dies angle. TAhles oa, minohuonmt oogfe  nefefietyctiovfet hsetreafifne citnivceresatsreasin  winitchre  ianscersewasiitnhgi ndcireesa sainnggleo.f  Adlissota, nicnehformomogtehneeciteyn toefr  tthoet heeffseuctrifvaec estorfatihne  inexctrreuadseesd  wmiathte riniaclr.easing  of distance from the center to the surface of the extruded material.  TThhee  eeffffeeccttss  ooff  ddeeffoorrmmaattiioonn  tteemmppeerraattuurreess  oonn  tthhee  mmaaxxiimmuumm  rreeqquuiirreedd  llooaadd  ffoorr  ddiiffffeerreenntt  rreedduuccttiioonnss  dduurriinngg  tthhee  hhoott  eexxttrruussiioonn  pprroocceessss  aarree  iilllluussttrraatteedd iinn FFiigguurree.. 88.. IItt iiss oobbvviioouuss tthhaatt tthhee aalltteerrnnaattiioonnss aanndd vvaalluueess ooff  the  hot  extrusion  load  increases  with  increasing  of  reduction  values.  2M4 eanwhile thISeS Nv:a1l9u8e5s-3 o15f 7hot eVxotlr. u10sioNn ol.o1adJ adnuecarryea- sJuense w20i1th6  increasing  of deformation temperature values.  

Also,  inhomogeneity  of  the  effective  strain  increases  with  increasing  of distance from the center to the surface of the extruded material.  The  effects  of  deformation  temperatures  on  the  maximum  required  load  for  diffTehreeInnftlu  ernecedouf Ecxttirounsiosn  Ddiue rAinnggle Dtuhrein ghthoetH  oetxEtxrtruussiioonnP ropcersos cofeAslsA  laloryes   illustrated in Figure. 8. It is obvious that the alternations and values of  the  hot  extrusion  load  increases  with  increasing  of  reduction  values.  tMheeahnowt heixlter uthseio vnalouaeds oinf chroeta seexstrwusiitohni nlocardea dsiencgreoafserse dwuicthti oinncrveaalusiensg.   Mofe daenfworhmilaettihone  vteamlupeesroaftuhroet veaxlturuesi. o n load decreases with increasing of deformation temperature values.  Journal oFf Aigduvraenc8e:d TMhaenvufaarcitautriionng Toefcehnxotrlougsyion load at different deformation   Figure 8: The variatetmiopne oraf teuxretrsuasnidonre ldouacdt iaotn sd.ifferent deformation  The influences of diete amnpgelersa taunrdes f arincdti orned cuocetfifoincise.n  ts on the extrusion  Tlohaedi naflrue enshceoswonf  dinie  aFniggulerseuarned  9fr. icItti oins ccolefafric  ifernotms  onthtihs eFeixgturruesuioren;  leoxatdruasrieonsh  loowadn ignraFdiguuarlelyu rdee9c.rIetaissecsl eaanrdfr  oamftetrh  tihs aFti giunrcereuarsee; se xwtriuthsi oann   tliiohnnaeccdrrdeegaaiessreeaa sdn iungwa lleitlth.yheA d  ildenscoicer,re eaiatsnseigissnlegao. nb  o dvAfi oaluffstrosei1c,r 1thii totha nati ste bixonetbctrwurveiseoaieosunens s  twhaitth  eaxntriunsciroena sleoaind  ldoiaed  ainndcr  ewasoerskpwieitche  isnucrrfeaacsei.n  g of friction between die and workpiece surface.   Figure 9: The variation of extrusion load at different friction Figure 9: The varcioaetifofinci eonft es xatnrdusdiioena nlogaleds .at different friction  coefficients and die angles.  2fMrM2rie0er0sis0si0cpctp rreeoaμoμccnsmstmttintirvrve uueebabclcllyetyeteufu.f.do orTrTrereaoesoest   ioio6hnhnf0fovov 0ttettehh ssºeeteCetixi xggtttwtwawrartutuioeoetssh  itistoshohaatnenwmem  iiopinpinllllilliheuteutiso issasal tltwldrwr mamaiinitttteiehighccddr rtio ioninismisninittttreri iuauasFFlclcio itgtggguufururrr5araereieie,n,ans stnt h hssd1e1ieiz0z0 5seaseaa0a  momoamaffnpnp i4d4ldnle0e0, ss 1aa1a a0ann0nrbrbddede,,    first  annealed  at  600  ºC  with  two  holding  times  of  5  and  50  min,  and  then  air  cooled,  so  the  grain  size  of  samples  obtained  are    about  40  and 200 μmI,S SreNs:p1e98c5ti-3v1e5l7y.  Vol. 10 No. 1 January - June 2016 25  

coefficients and die angles.    Microstructures  of  the  two  samples  with  initial  grain  size  of  40  and Journ2al0o0f Aμdvman cbedeMfoarneu fahctoutr inegxTtrecuhsnioolong y illustrated  in  Figures  10a  and  10b,  respectively. To investigate the initial microstructure, the samples are  first  annealed  at  600  ºC  with  two  holding  times  of  5  and  50  min,  and  thenthaeinr caoiro lceodo,lseod,t hseo gtrhaei ngsriazien osfizsea mofp lseasmopblteasin  oebdtairneeadb oauret 4  a0baonudt  40  200aμnmd ,2r0e0s pμemct, irveeslpye. ctively.       (a)                                                 (b)  FiFgiugruer1e0 1: M0: iMcroicsrtrousctrtuurcetsuorfessa omf pslaems bpelfeosr ebehfootreex htrouts ieoxntraut sion at  anannenaelianlgintge mtepmerpaeturaretuorfe6 o00f 6ºC00a nºCd haonldd ihnogltdiminego tfim(a)e 5omf (ian)a 5n dmin and  Microstructures  of  sample(sb )h5o(0bt m)e 5xin0tr. mudined.    at  the  temperature  of  450ºC   Micarroes tsrhuocwtunre  isno  Ffigsaumrep  1le1s.  Ahost  sehxotwrund eind  tahtitsh  Feigteumrep, esreavtuerreelyo fe4lo5n0ºgCated  aregsrhaoinwsn  arine  oFbigsuerrvee1d1 .aAt  hs osth  oexwtrnudinedth  sisamFipgluer  we,isthev  ienrietilayl eglroanigna  steizde  of  gra2in0s0 aμrme o, bwshericvhe dsuagt gheostt etxhtartu  ddyednasmamic poler  swtaitthic irneictioavl egrrya ibne stihzee omfain  200reμsmto,rawtihoinch prsoucgegses sdt utrhiantgd oyrn aafmteric thoer hsotat teicxtrreucsoiovner. y be the main resto ration process during or after the hot extrusion.    (a)                                                  (b)  FiFgiugruer1e1 1: 1M: iMcroicsrtorusctrtuurcetsuoref s aomf psalems apflteesr hafotteerx htrouts eioxntrwusitihond iwe ith die  anagnlgeloef o2f0 2º 0foº rfotwr otwinoit ianlitgiraali ngrsaizines soizfe(as) o4f0 (μa)m 4a0n μdm(b a) n20d0 (μbm) 2. 00 μm.  In FiIgnu Freigu12re,  t1h2e, tihnefl uinefnlucenocfe doife daine galnegolen omni cmroicsrtorustcrtuucrteureev aelvuaaltuioatnion  is illuiss tirlalutesdtr.aDteedta. ilDedetmailiecrdo smtriuccrtousrtarul cotbusrearlv  aotbiosnerivnadtiocant eisntdhiactatmeso rtehat  hommogoerneo  huosmstorguecntuorues instrFuigctuurree 1i2n( bF)igisurdeu 1e2t(ob)t hise  deuxetr utos itohne perxotcreusssion  withpdrioeceasnsg lwe iotfh2  d0ºiew  ahnicghlei socfl o2s0eº two thhiceho pist imcluosme dtoie  tahneg  loepotibmtauinme ddie  fromasnigmleu olabttiaoinn.ed from simulation.     26 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

In Figure 12, the influence of die angle on microstructure evaluation  is  illustrated.  Detailed  microstructural  observation  indicates  that  more  homogenous  structure  in  Figure 12(b)  is  due  to  the  extrusion  process  wThietIhn fludeinece  oafnEgxtlreu sioonf D2ie0Aº nwglehDiucrhin gisth ecHlootsEex trtuos iotnhPer ocoepsstoifmAluAmllo ysdie  angle obtained from simulation.                   (a)                                                       (b)  FiFgiugruer1e2 1: 2M: iMcroicsrtorusctrtuurcetsuoref ss aomf psalems apflteesr hafotteerx htrouts eioxntrautstihoen at the  tetmempepreartuartue roef 5o5f 05º5C0 wºCit hwtiwtho tdwieoa dnigel easnogfl(eas) o20f º(an) d20(ºb )a3n0dº. (b) 30º.  5.0 CONCLUSIONS In this work, a mathematical model based on the finite element  eaxntarluyssiiosnwparsopcreosspoofseadlutmo ipnruemdicatlltohye.o1Dp3e tfiomrummatdioine angle during the hot forces, material flow and microstructural evaluation of the hot extruded material affected by Extrusion Die Angle (EDA), were investigated. The results show that at each reduction, there is an optimum die angle providing minimum extrusion load. In the same conditions, optimum die angle increases with increasing the amount of reduction and decreasing friction of die. The results also show that the values of the equivalent plastic strain and its distribution depend extremely on EDA. The equivalent plastic strain increases with increasing of EDA. Investigations show that temperature is one of the most prominent parameters that controls the process. Finally, microstructural investigations show that EDA and the other processing parameters of hot extrusion have efficient effects on the microstructure of hot extruded sample, as the optimum die angle prepares more homogenous microstructure. REFERENCES [1] J. G. Kaufman, Introduction to Aluminum Alloys and Tempers, ASM International, Materials Park, OH 44073‐0002; 2000. [2] Brown, K.H. Kim, L. Anand, An internal variable constitutive model for hot working of metals, Int. J. Plasticity, 5 (1989) 95–130. ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 27

Journal of Advanced Manufacturing Technology [3] HR. Shercliff, A. M. Lovatt ER, ʺModelling of microstructure evolution in hot deformation.ʺ Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 357, pp. 1621–1643, 1999. [4] Furu, H.R. Shercliff, C. Sellars, M. Ashby, ʺPhysically‐based modelling of strength, microstructure and recrystallisation during thermomechanical processing of Al–Mg alloys.ʺ Material Science Forum 217–222, pp. 453–458, 1996. [5] M. Sellars, Q. Zhu, ʺMicrostructural modelling of aluminium alloys during thermomechanical processing.ʺ Materials Science and Engineering A 280 (1), pp. 1–7, 2000. [6] Sheppard, ʺPrediction of structure during shaped extrusion and subsequent static recrystallisation during the solution soaking operation. Journal of Materials Processing Technology 177 (1–3), pp. 26–35, 2006. [7] Chanda, J. Zhou, J. Duszczyk, ʺA comparative study on iso‐speed extrusion and isothermal extrusion of 6061 Al alloy using 3D FEM simulationʺ Journal of Materials Processing Technology 114 (2), pp. 145– 153, 2001. [8] M.S. Joun, S.M. Hwang, “Optimal process design in steady state metal forming by finite‐element method. I. theoretical consideration”, Int. J. Mach. Tools Manuf. 33 (1993) 51–61. [9] S.K. Lee, D.C. Koo, B.M. Kim, “Optimal die profile design for uniform microstructure in hot extrusion”, Int. J. Mach. Tools Manufact. 40 (2000) 1457–1478. [10] S.M. Byon, S.M. Hwang, “FEM‐based optimal design in steady‐state metal forming”, J. Comp. Struct. 79 (2001) 1363–1375. [11] W.F. Hosford, R.M. Caddel, “Metal Forming, Mechanics and Metallurgy”, Prentice‐Hall, 1983. [12] T. Sheppard, “Extrusion of Aluminium Alloys”, Kluwer Academic Publishers, Dordrecht, 1999, p. 127. [13] E. S. Puchi‐Cabrera, C. J. Villalobos‐Gutiérrez, A. Carrillo, F. DiSimone “Non‐isothermal annealing of a cold rolled commercial twin roll cast 3003 aluminum alloy”, JMEPEG 12 (2003) 261‐271.28 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Laser Forming of Metallic Dome‐Shaped Parts Using Spiral and Radial‐Circular Scan Paths LASER FORMING OF METALLIC DOME‐SHAPED PARTS USING SPIRAL AND RADIAL‐CIRCULAR SCAN PATHS S.H., Dehghan1, M., Loh‐Mousavi2 , M., Farzin3 and M., Safari4* 1Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, 43400 Selangor, Malaysia. 2Faculty of Mechanical Engineering, Khomeinishahr Branch, Islamic Azad University, Khomeinishahr, Isfahan, Iran. 3Faculty of Mechanical Engineering, Isfahan University of Technology, Isfahan, Iran. 4Department of Mechanical Engineering, Arak University of Technology, Arak 38181‐41167, Iran. Email: [email protected]: Laser forming process is a new flexible forming process withoutany contact between rigid tools and sheet metal, in which the form of a sheetmetal is changed permanently by high thermal stresses caused by laser. Ingeneral, laser forming of spatial shapes and laser forming of two dimensionalsimple shapes are different. On one hand, heating path and pattern of thermalstress are increasingly being used in a laser forming process, which areespecially important in forming three dimensional complicated parts. In a laserforming technique, a desired final shape can be achieved by a control of the laserscan path and other process parameters such as laser irradiation pattern, laserpower, speed of laser scan and laser beam diameter. A new application of thelaser forming process is production of dome‐shaped parts as a prototype. Forthe production of curved parts, especially for the dome ‐shaped ones, differentstrategies have been developed which are mostly based on curved irradiationpaths. In this paper, a circular‐radial strategy of scanning path to form domeshapes by using laser is investigated. Experiments have been carried out tovalidate the numerical results. As a result, a new scanning pattern is presentedas a spiral strategy. It was shown that the stress distribution is more uniform inlaser forming with the use of spiral scanning path. In addition, the deformedparts with spiral scanning path are more uniform compared to other scanningpaths investigated. Furthermore, it was found that laser forming withradialcircular scan paths will result in buckling mechanism whereas spiralirradiation will lead to gradient mechanism. The study also shows that radialand circular irradiations lead to occurrence of low thermal gradient andbuckling mechanism. Additionally, low thermal gradient and bucklingmechanism is happened by spiral irradiation. Finally, thickness distributionand temperature gradient of the deformed parts caused by different laserpaths have been investigated.KEYWORDS: Laser Forming, Finite Element, Dome Shaped, Spiral Path.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 29

Journal of Advanced Manufacturing Technology1.0 INTRODUCTIONLaser Forming is an advanced technology that has been developed inorder to shape metal parts. The process is obtained by thermal stressto steel sheet by controlled radiation from a focused laser beam. Laserforming is a combination of mechanical heat process in which heat isapplied by a laser beam on one side of the sheet metal in a specificdirection [1]. Stress‐strain relation on the sheet is not only nonlinear,but also is temperature dependent. In the laser forming process, theshape and position of a bend are determined by radiation exposurerate, beam size, and the position of the laser beam, all of which areconsidered process variables. In traditional forming techniques suchas bending, stretching and pressing, heavy‐duty tools are required forthe applied external forces to transform a flat piece of sheet metal bydevices or the form in which the deformation process can be completed.The biggest advantage of the laser forming technique compared to thetraditional method is production flexibility and cost reduction as wellas production time. Various applications of the laser forming processhave been identified to shape the macro aspects of rapid prototypingand proofing industries like automobile, aerospace and ship building.Aspects of laser forming of micro‐industry microelectronic componentsto precisely adjust the shape of laser applications and several newmethods of laser forming are under review and development. Featuresof this process include extremely high reliability, flexibility, productionof complex shapes, capability of rapid prototyping, production of high‐precision, low recalculation and access to the detailed form of the slightreturn spring. Types of mechanisms that are produced by laser are asfollows:• Thermal gradient process• Buckling process• Upsetting processAs the gradient heat process suggests, the process depends on thecreation of high slope heat in sheet thickness and it is caused as a resultof bending the sheet towards the laser beam. Process buckling is createdwhen the slope of heat in sheet width is small and due to low thicknessof sheets, the diameter of heated region is bigger than sheet thickness.The result of the process is sheet bending towards laser beam and awayfrom the laser beam. In the upsetting process, the heating conditionsare the same as the other two mechanisms, but due to geometricalconstraints, it is not possible to do sheet bending and, for this reason,deformation leads to an increase in the thickness or the upsetting ofthe sheet. In the general states, because of high thickness of sheets, a30 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Laser Forming of Metallic Dome‐Shaped Parts Using Spiral and Radial‐Circular Scan Pathsdiameter of heated region is equal to sheet thickness, a mechanism thatcauses reduction in the length of the sheet, but bending does not occur[2].A new application of forming process using laser is called controlledirradiation as the specific pattern on the metal plates to create specificpieces for quick prototyping and production of small parts. Forming thecircular plates as bowl‐shaped or dome‐shaped requires a contractionwithin a sheet and a bend outward of the sheet.To manufacture complex curved space components (such as adomeshaped), somewhat different irradiation patterns on curvedlines and curved radiation are to be discussed. In general, if curvedlines of radiation are used instead of straight lines, collections ofthreedimensional laser forming will be created and thereby a significantchange in the nature of the process and its dependence on the geometryof the components can be created [3‐4].Since 2000, Laser research group at the University of Liverpool hasconducted extensive research in the field of laser forming alloys andcomposite materials used in aerospace industries, as well as forminga complex three‐dimensional laser body and parts of the ship [5‐8].Edwardson offered radiation pattern to form a saddle‐shaped surfaceand proposed an alternative model for the formation of a surface whichis presented as a pillow [9]. Li and Yao presented a process based on thefinite element method to determine the path of irradiation, irradiationstep, exposure rate and exposure to form a curve in two dimensions[10]. On the other hand, Maggie and her colleagues studied concentriclines with upsetting mechanism in a laser forming of a domed surface[11]. Through experimentation on the circular ring segment of steelSAE1008 with 2‐mm diameter, Hennige showed that the requiredamount of exposure of laser for circular plates and annular plates islower in comparison with rectangular plate. Moreover, in the circularsections, aberration and distortion are more than that of ring sections[12‐13]. Following the research done by Hennige et al, a radiation patternconsisting of radial radiations under upsetting mechanism and circularradiations under a temperature gradient mechanism for producingdomeshaped surfaces are proposed. In the previous researches, twodifferent irradiating schemes were used to produce double curvatureshapes with laser beam. In the first irradiating scheme, circular pathswere used. Also, in this irradiating scheme, thermal gradient mechanismwas considered to be dominant. In the second irradiating scheme, theradial straight lines were used and the dominant mechanism was UM.Both of these irradiating schemes have their own advantages andISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 31

rnal of Advance d Manufacturing Technology mechanism was considered to be dominant. In the second irradiating  mssnImogpwtpsdDapFahnuctsfweioraruruaogheei yoocottesesccnterute cmdvm s he ehoh emt rpsiturmoenmasaedoe anac se a nndlt et 1tet,ysiert,dht iidiiv hn eytss eso[cveare cc emmt1 ttrnoi o air oahwn o5compd ifnn  nne ]b,po nwi oi.wtte  sJdtbu sefchaeoassdpIdpcaDodseshwha ssonmIgpwtpsdDaaFpa unionrtadguuhodie hnnaraiiinuct asisfacdwieriutorarulsn sss re unooacc aroghn egtii  lyieposaoocsdo tatatdevteostyecnriscccdpnadsccnteruudterhe cmthemrdvemUdda sio l eheeanie eoheeii oee srtmatu rrcepg.csseoidotbunssnnvvromoaen asanMm.sanedbmlcoea afeacacessnanu i ct aa rstse dsat nedAltid,ntt eTsaiiuntstr o1ate tr,iysi eTnyrnntt,e.sivvdshhiset iid didivtb  vihoinhd grefyat casc ‐essomaaittthee[coccvve[e avBroee seccnanaareuemte 1t it tr1attnooein o vaihpira oaahelrrfllwnoins gghrnmo5gcdrn4oniminoirp d ioeafnndm iene ndaocenv natn]teeb,pe ]eo imgnegfdied dnhoi.aw fettep s. ssdsssis eetbebuefd sewf ochrhae a asgta shrwhrii yoc edseaasb aooniordtrattaMdgaraatise idaoehndw arm dioniardiytd  ereltfsnt a cdde edoo rers aiifepvahesaiisrdo t ,   dvhorbinbriscpade  orlnn,vnmbiriuiadhmrptaarc em Uewiaia aeroatnerietdeoueinaeoaen dsraanlceg.shtlhaodetntnmeafn a astanuedMair hnmsleceaaneieiiolatedenhauedt im t arootda,csie.teadr‐sidsettarn  sfreonasetl ei Tyassdae.sodetnnTes gisyu  iraa stibi e vtldgif heela ctc‐ sgfmnditmhairbs ih ysnhel[ ti Boieewswena cdrasueai mti sawn1i.ntyedgnseemevghiieada lfoanlnoslhbmoigip r4rnsdeigmir e a insnmie indaTimnrm vigrtonrto e a ]2esmgmenlrgesunTahsa aeaaap.blilh senbl ueamfe0doa  h ca  esydetgitd rrdrd nodcpeedeess nba0eocnb lrtrhpaitoaatns toehupshire  dtiec nitenayesdn0  etdehacdaderadruar.rrneortsacfthaheeprldt t . g had eeidatytmar  et toal,vr tIirsiiimrcp oevce ib eweiisyldareannodTeetdeeetaooannhtamipdcntldehneceeertotu amnhg idr gntiehdairhnneineg iiinnarta,ea oyaued oftracoiso,rees tie rhiuaiseyte   lntdtetlsstcltwescirfatsdiadeinn   ohtt  steaienid sseh  neufaep u eletha gaf2litiws  sd cila iiei tiepegawwne  eigdamalaarnlslwnslrr0.enyeshohnb aiaaa dl ltoan,lbdoearb eth trg0sgeim e ena ereeoctrspbbaTiatnm ticspsro  ib 2e0see dlrs s imn hhslaluodaebp yoboltlhn uamaeiy0u.ihro ap  tydthi iednzdpaitan rieanTpv nt0egshnbe sta pmtoloai ctiiueres e  itH eitrdrse0rers hdarenseaawrtruarertzeetacpteaaeeapr aeecr.is etta  e dhatnir gt er eptsnnissdcsi ythdreshvec tnerisydmnhdTerrteee en escrudonh,dgh upndeipenecai,ier atiyih drgerhniha naricbmg lom ihuanaer sasvsar dr notnb trprs col eeltisuyieueuem dmloottt letseascefatsneiic usmpw lohtpesdd ossF ntre afcpt li liu dadenchsgliietinidas cicoepiatepfin, tigmtatd.atnrnnenlbrid sehtg.h  uonth iahetrshaa aln,dur  th.ittae uttgetmba tfuesf elneterspnbateaeiehhIbasabdos sInaeie. tyaia  m tsniroddbr n nygofptneeeeeenahurrrsruratpll etonhnaia ri                nhpetgrhteae tleaHirtiitr,r1o H isers earanseahetsazeetbaietv eciee tn hn[mcdg seioetnnessteh 1tinshhydtue en sucdudscdg u5pae,tnteh ermha snahmleo h]p [nsvrcrnbmi tecou.e1sldieemenoi eteamsneidcumrw4sisdosr cegi t ccohoge,]iintswctpeef,tadunn.ewrenp et  uhiastnlteu f.rital uttmraehefs lneoataoihshnbiosInai.dthnaaeicssdrrn nteeeeee,rrrtll                                             ( a(A) )                                               ( b ()B)            F  Fi g i(guAur)er  e  1  1:   :( a ( a)   )P  P a a t tt e t er  rn n   o  o f  f c c o o n n c  ce e n n t r t ri c i c (cBciri)rc  cleless (b(b) )PPaattteterrnn ooff rraaddiaial llilnineess  Figure 1: (a) Pattern of concentric circles (b) Pattern   of radial lines    FFigiguurree 22: :RRaaddiaial l‐ ‐ccirirccuulalarr ppaattt eterrnn [1[122] ]   Figure 2: Radial ‐ circular pattern [12]       32 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Laser Forming of Metallic Dome‐Shaped Parts Using Spiral and Radial‐Circular Scan PathsIn this paper, a new irradiating scheme is proposed for the productionoInf  tahids opuabpler,c au rnveawtu irreradoiamtien‐gs hsacphemd ep iast tperronpofrsoemd foar ctihrec uplraordbulcatniokn.  Aoft  afi rdsot,uobnlee  coufrvthaetuirrer addoimatien‐sghascpheedm  peastttehrant  fhroamve  ab  ceierncuplaror pbolasnedk. bAyt ofitrhset,r orneese oafr cthe risrriasduiasteidngi nscthheemeexsp tehraimt heanvtea lbaenend pnruompoesriecda lbyw orthkes.r Irnestehairschsetargs ei,s nuusemde rinic athl es iemxpuelartiimonens talr eanvde rnifuiemderwiciathl wexoprkersi. mIne nthtails osbtasgeerv, atniounms.erAicfatel r tshimisuvlaetriiofincsa tioanr,e nuvmereirfiecadl  swimituhl atieoxnpseroifmleanstearl foobrsmeirnvgatoiofnas.d  oAuftbelre  cthuirsv avteurrieficdaotmione,s  hnaupmeearriceapl esrifmorumlaetdioanlso nogf  wlaistehr sfpoirrmalinirgr aodf ia tdinogusbcleh ecmurev. aFtiunrael ldy,oamceo smhpaparei saorne ipsemrfoadrme eodn athloenrge swulitsh osfpitrhael iprroadiuacteindgd socmheem‐leik. eFisnhaallpye, aw ciothmsppairiasloinr riasd miaatdineg osnc htheem reesaunldts tohfe  tshceh epmroedcuocnetda idnosmcier‐cluiklaer  sphaatphes .wThiteh rsepsiurlatls  iwrrialldbiaetisnhgo wscnheinmtee ramnds  othf ed sicshtreibmuet icoonntoafinrse scidrcuuallars ptraetshsse.s T, haec hrieesvuelmts ewnitllo bfe tshheowdonm ine dte‐lrimkes sohfa  pdeis,traibteutoiof ned  ogfe sressyimdumael trsytreasnsdesf,o  ramchiniegvecmonednit ioonf  othfee ddgoems.eSdp‐ilrikael  pshatatperen, riastme oufc hedbgeettse srytmhamn etthrey cairncdu lfaorr‐mraidniga lcopnatdteitrino.n of edges. Spiral pattern is much better than the circular‐radial pattern.  22..00     EMMPPIIRRICICAAL AL NAANLAYSLIYSSIS  IInn tthhiiss ssttuuddyy,, aa ssoouurrccee ooff ccaarrbboonn ddiiooxxiiddee llaasseerr aalloonngg wwiitthh aa ppoowweerr ooff 115500 WWaatttss wwaass uusseedd.. IInn oorrddeerr ttoo mmoovvee tthhee ssaammpplleess ttoo ccrreeaattee nneecceessssaarryy eexxppoossuurree ppatahtwhwayasy,sa, tha reteh‐raexei‐saCxiNs CCwNoCr kswtaotrikosntawtiaosnu  sweda.sA  ucsirecdu. laAr  bcliarcnuklaorf  b1l0a0nmk mof d10ia0m  metmer  dainadmae‐te1r manmd an‐ d1 2mmmm  anthdi c2k  mnemss  twhiecrkenceusts fwroemre tchuet afsr‐ormec etihvee dasl‐orwececiavrebdo nloswte eclarabnodn wsteereel uasnedd  waserae supseecdim  aesn  a.  IsnpeFciigmueren.3 I,ne Fxipgeurrime 3e,n etaxlpseertimupenotfall asseetrupfo ormf liansgero fforcmircinugla or fb cliarnckulaisr sbhlaonwkn i.s shown.      FFigiguurere 33: :CCoonnfifgiguuraratitoionn aanndd ininsstatalllalatitoionn oof fththee wwoorkrk ppieieccee foformrmeedd bbyy   raraddiaial l‐ ‐cciricrcuulalar rppaathth wwitihth aa ththicickknneessss oof f11 mmmm steIIt esentxentxrmrmp apatoiptoiphghgseseehuehurrt artare fteftloluoui ilnnrollroleoeeevov w ewaedadrlriiiloin snostntgtntgirirgmmig ib beteeeuhmutm htetaipaiep oroprieinrenrapi i tccaeaheaaatxnxn lhlaoda dmfama o ntentifhihnxanaepleeeleyy dxodesesps..iffiu sfosfAe,Aer,s cecussta,tar    aeiooinc ,ncfftldl hdoaoiiiisnicnsrcetaetdtahreertt re irbermdemdeedxxai iatiatmitbnmtnmeee n niaiiFnrtFntmri aiagaagattudniuniioorridrdanernea t  pipdo4o4aoainf rafri  aitanwnitltlolhlh eaenaeaelsl    investigated.  Initially,  the  temperature  begins  to  rise  due  to  the convective IeSfSfNec: t1 9o8f5 -t3h1e57 tempVeolr.a1t0ureN, ob.u1t Jwanhueanry f-oJcuunese2d01 6beam of lase3r3 

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Laser Forming of Metallic Dome‐Shaped Parts Using Spiral and Radial‐Circular Scan Paths a thickness of 1 mm were modeled in ABAQUS software model. In order to compare the numerical results with the experimental ones, this paper is attempting to provide identical conditions with the eesseixxixmmpppeeueurrlrliiaiammmttiioeeoennnnnttt aaaaarllrl e eaaa nnanasddsd ff nnonouululllmomomwweeerrsrsii.i.ccc aaalll  rrreeesssuuullltttsss...  PPPrrrooopppeeerrrtttiiieeesss  ooofff  ttthhheee  sssttteeeeeelll  uuussseeeddd  iiinnn  ttthhheee    s imulation arTeTa aabbslel ef 1o1:l :lPoPhwhyysssi.ci caal lpprrooppeerrtiteiess oof fththee wwoorrkk‐ ‐ppieieccee  Table 1: PhYysouicnag'ls pmroodupluesrGtipeas of the wo1r5k4‐ piece  YoDunegn'ssitmy okdgulu/smG3pa 154 DYeienlsditsytrkesgs /Mmp3a 7700 7700 243 Yield stress Mpa 243 550 Specific heat J / kg k   Specific heat J / kg k 550   IInn tthhee ssiimmuullaattiioonn ooff ththee pprorocecsess,s ,thtrheree edidmimenesniosinoanla slosliodl ideleemleemnetsn tosf  Iotnhf ett hhteye psteiym pDueCla3DtDiCo8n3 D wo8hf itwchheh  hipcahrso c8he‐anssso,d 8t‐ehn rtoerdie‐e ldintimeria‐erlin ndseisoaprnlaadlc iessmopllieadnc ete mlweemenret n  uwtse eordef.   tuThsoee dtby. epT eop DrbeCec3ipsDree8, c wi2s eh,liac2yhel arhsya esro 8sf‐ onefoledemlee emtrniet‐nsli tnstehtarhro rudogiushgp hlathctheeem  ttehhniitcc kkwnneeerssess uwwseeedrree.   Tggeoen neberreaa ttepeddre icninsteh ,e thw2e o lrawky‐eoprriske c‐poeifae  nceedl etmahneednm tset shtheh orofmuthegsehh w  tohorefk  ‐tphiieecc kewnceoosrnsk ta‐wpinieeercdee   g1c5eo1nn2et0araientleeeddm  e1inn5t1 s2.t0hIn ee aledwmdoietrnikot‐snp., ieDIncFe  La  dUadnXidtsi ountbh,r eoD uFtmiLneUesXhh assoubfb eretohnueut isnweed ohtroaks‐a ppbipecelyen   ctuhosenethdae itanote fdalpu  1px5.l1yT2 ht0he ea lnheamelayets nfitlssui.x sI.p nTe harfedo darmintiaeoldyns,i insD tiFwsL opUemXrfo osdruembsre:odthu eitnifn itrews thoaa nms aoblydeseeinss:    uwthsaesd  ft ihtroes rta mpanaplalyaly ntsdhiset  hwheeanas,t  ttfhhleuerxdm.e Tfaohl ream naadnt aiotlhynesanisn,  aitslh ypes eidsrfeoofformtrhmeedast hionen et twamnoea mtlyaolsidwse aoss:f   tdthhoeen  efsihrbseyte tra emnsaueltlytassli osw fwatsha edsr omtnhaee lrbmayn aralel ysausnildst.s  tohfe tnh,e  trhmea  dl aenfoarlmysaisti.o  n  analysis  of  the sheet metal was done by results of thermal analysis.    FFiFiggiugurureer e 55:5:  F:FiFinniinitteiet e eeleleelmemmeenentnt  mtmmeeseshsh h oofof  sfshsheheeeetet  t     4.0    RESULTS AND DISCUSSION  4  .  0    RESULTS A ND DISCUSSIO N      4  .1       Deformation by circular‐radial radiation on the sheet    4I.n1 F   i g  uDref 6o,r mthaet rioesnu blty o cfi rlacsuelra rf‐orramdianlg r a dciiarctiuolnar o bnl athnke swhiethet  circular –  Irna dFiaglu irrer a6d, itahteio rne spualtth osf i sla ssheor wfonrm. Ains gil lau csitrrcauteladr, bthlaen tko twali tdhe fcoircmualatiro –n   roafd  tihale  ierrdagdei ainti otnh ep  zaethros ids esghroewe np.a Aths  iisl lpuostsriatitveed.,  Othne  tthoeta  ol tdheefro  rhmanadti,o  inn   othf eth  9e0 e‐ ddgeeg riene t hpea tzhe rtho ed teogtrael ed peafothrm isa tpionsi toivf et.h Oe ned tghe  iost hneerg ahtaivned.,  Ains   tshuec h90, ‐t hdee gvrIaSelSeuN ep:sa1 9toh8f5 -ta3hn1e5  7etdotgaelV  odlie.s1flo0orcmaNtaioot.ino1 niJ nao nfbu otahrtyhe -epJudangtehe2s 0i s1w 6neerge adtiivffee.r  Aen3st5   sauncdh ,w  tihlle  bvea dluisecsu  ossf eadn b  edlogwe . dislocation  in  both  paths  were  different  and will be discussed below. 

Journal of Advanced Manufacturing Technology 4.0 RESULTS AND DISCUSSION 4.1 Deformation by circular‐radial radiation on the sheet In Figure 6, the result of laser forming a circular blank with circular – radial irradiation paths is shown. As illustrated, the total deformation of the edge in the zero degree path is positive. On the other hand, in theJournal of Advan9c0e‐d dMeagnruefaectpurainthg Ttehcehntoolotgayl deformation of the edge is negative. As such,  the values of an edge dislocation in both paths were different and will be discussed below. 90 degree path  0 degree path  Figure 6: Status of sheet metal forming by circular‐radial pattern  Figure 6: Status of sheet metal forming by rcaidrciautliaorn‐radial pattern radiation   4.2        4E.2va luarEtaivodanila uolafrt airodenmiaootivfoanrbemle oevdagbelse oefd sgheeseotsf fsohremetisngfo irnm ciinrgcuilnarc  i rcular radial radiation    In Figure7, the status of the edge dislocation and profile of the dome In Figuwrei7t,h thae csitractuulsa ro‐f rtahde iaedl grea ddiiastlioocnataiorne ashnodw pnro. fAiles ocfa ntheb edosmeeen  along with a cbiorcthuladri‐r ercatdioianls r,atdhieatidoinsp alraec esmhoewntn.a lAosn gcatnh beee sdegeens ailnonag zbeortoh degree directiodnisr,e  ctthioen  disisppolsaicteivmeewnti thaltohnegv atlhuee oefdagreosu nidn 8am  mze.rFou  rdthegerrmeeo  re, the directiodni sisp lpaocseimtivene twoiftthh teheed vgaelualeo onfg atrhoeu9n0d‐ d8e mgrmee. dFuirretchteiormn iosrne,e tghaeti ve and displacethmeevnat luoef itshne eeadrlgye 8amlomng.   the  90‐  degree  direction  is  negative  and the value is nearly 8 mm.   Figure 7: Diagram of the dome‐shaped profile with a circular‐radial pattern   36 ISSN: 1985-3157 Vol. 10 No. 1 January - June 20164.3          Distribution of stress in the laser forming process by  circular‐radial radiation  

In  Figure7,  the  status  of  the  edge  dislocation  and  profile  of  the  dome with a circular‐ radial radiation are shown. As can be seen along both directions,  the  displacement  along  the  edges  in  a  zero  degree directioLna siesr FpoormsiintgivofeM wetaitllhic Dthomee ‐vSahalpueed Poafr tsaUrosiungnSdp ir8a lmanmd R.a dFiaul‐rCtihrceurlamr SocarneP, atthhse displacement  of  the  edge  along  the  90‐  degree  direction  is  negative and the value is nearly 8 mm.    FigurFei g7u: rDei7a:gDraimag oraf mtheo fdtohme ed‐osmhaep‐sehda ppreodfipler owfiilteh wa ictihrcauclairrc‐uraladri‐arla pdaiattlern   pattern4.3          Distribution of stress in the laser forming process by 4.3 Dracidisritcaruilblrauardt‐irioaantdiiooanfl srtardesiastiinonth  e laser forming process by circular‐   vtrFtrvFheaiheiagmalgmaluutuutoe rorerrveesveesemo e m8do8dnan.a .isI t isnhttnhhhIioe itsoien wnwfo fii asbisnasn s sa tsaeotolholhrlbg elvigeidseed eeeodeo mrfmmffvmtfeaheeeacetcdatttetrtet rr yrotyiotihafoh afole lfavf avpatw ofw ofatntoenttoehtrr rermkem tkrth nhip ipsepseioeieea mesfmcstcret aseeea.sit.srintR rnniRredee c secussassoaisaueiduefdsls usssue reaatsaaerslnlnes o sdoissdftdfstr  treurethreeshsaeessseilssis es idesdstsssturotura eraaemraserlseslsees ess tewststhesthrsroha eo aesrsasrseeisteess      nsonm‐uewnihfoartm noann‐dunthifeoarrmea asnodf tthhee palraetaest hoaf ttharee palfafetec ttehdatb yarteh eafsftercetsesda rbey etxhpea sntrdeesds. aTrhe eeyxparaendroeodt.e Tdhienyl argee ronoutmedb einr  olafrrgaed niautimonbebre oafm rsadoinattihoen sbuerafamcse  ofnt hthees hseuertf,atchee  oimf  tmhe nssheeveat,r itehtey  oimf pmoesnssibel eveaxripeotys uorfe  panodsstibhlee oetxhpeorseuffrec atinvde tphaer aomtheetre ersff.ective parameters.     FFigiguurree 88: :RReessididuuaal lsstrtreessseess inin ccirirccuulalarr‐r‐raaddiaial lrraaddiaiatitoionn ppaatteterrnn   44..44         TTeemmppeerraattuurree ddiissttrriibbuutitoionn uunnddere rcicricruclualra‐rra‐rdaidali airlriardraiadtiiaotnio  n   IInn tthhiiss sseeccttiioonn,, tthhee tteemmppeerraattuurree ddiissttrriibbuuttiioonn ooff tthhee uuppppeerr aanndd lloowweerr  ssuurrffaaccee ooff sshheeeett mmeettaall uunnddeerr llaasseerr rraaddiiaattiioonn ooff cciirrccuullaarr‐‐rraaddiiaall ppaatthh iiss  iinnvveessttiiggaatteedd.. Using tthhiiss tetemmppeerraatuturree pprorofifliel,e d, odmominiannatn mt emcehcahnaisnmissm isn  itnheth  leaslaers erfofromrminign gprporcoecsess saraer efofouunndd. . IInn  ffiigguurree  9,  tthhee tteemmppeerraattuurree  distribution  has  been  studied  under  radial  irradiation.  The  buckling  mechanismI SShNa:s1 9o85c-c3u15r7red  Vdoul.e1 0to Ntoh.e1  vJaenruya rylo-wJu neth2e01r6mal  gradien3t7  between layers of the upper and lower plate by the radial irradiation.  In  figure  10,  the  temperature  changes  under  circular  irradiation  have  been  studied.  According  to  figure  10,  a  small  thermal  gradient 

Figure 8: Residual stresses in circular‐radial radiation pattern   4.4        Temperature distribution under circular‐radial irradiation  JoI  unr ntahl iosf Asdevcatnicoend,M  tahneu fatectmurpinegrTaetcuhnreol odgyistribution  of  the  upper  and  lower  surface  of  sheet  metal  under  laser  radiation  of  circular‐radial  path  is  dinisvtersibtiugtaitoend.h Uas inbege tnhist utedmiepderuantudreer prraodfialel , idrroamdiantainont .mTehcehabnuiscmklsin ign  mthec hlaasneirs mfohramsioncgc uprrroecdedssu eatroe thfoeuvnedry.  lIonw  fitghuerem  a9l, gtrhaed iteenmt bpetrwateuerne  ldaiysetrisbouftitohne uhpasp ebreaend  stlouwdieerdp  ulantde ebry  rtahdeiaral diriraal diriraatdioinat. ioTnh.e  buckling  mechanism  has  occurred  due  to  the  very  low  thermal  gradient  Ibnetfwigeuerne l1a0y,etrhs eoft etmhep uerpaptuerr eancdh alnowgeesr upnladter bcyi rtchuel arradiriraal diriraatidoinatihoanv.e  bIne efnigsutured  i1e0d, .tAhec ctoermdpinegrattoufrieg ucrhean10g,eas sumnadlel rt hceirrcmualal rg  rirardaideinattiboent wheaevne  tbheeenu pspteurdiaendd.  lAowcceorrdsuinrfga cteos  hfiagvuereo cc1u0r, read  .sTmhaelrl eftohreer,mloawl  gthraedrmienalt  gbreatwdieennt ltehaed us ptopebru caknldin lgowmeerc hsuanrfiasmcesi nhtahvee wococrukr‐preidec. eT. herefore, low  thermal gradient leads to buckling mechanism in the work‐piece.   Journal of FAFidiggvuuarnrecee 9d9: :M TTeaemnmupfpaecertruaartltiulonuorwgrweeTeed erdrci lishlastnatryoyrielibeobrugrsusyto tioiofofn rnrai ainddnit iatahlhle rerae aedxdxipipaaototisiosuounrnreeo offt thheeu uppppeerra anndd      FFigiguurree1 100: :T Teemmppeeraratuturered disitsrtirbibuutitoionni nint htheee exxppoosusurereo of ft htheeu uppppeerra anndd   lolowweerrl alayyeresrso of fc icricruculalarrr araddiaiatitoionn    44..55         D Disistrtirbibuutitoionno of ft hthicikcks hseheetemt meteatlawl iwthitchi rcciurcluarl‐arra‐draidaliaral diation T  o investriagdaitaettihoen f ormation of dome‐shaped pattern by circularradial rTaod iaintivoensptiagtateter nt,hine crfeoarmsinagtiothne  tohfi cdkonmeses‐nshuampeerdi caplalyttaertn9 pboyi nctsiracluolnagr‐ trhaeddiaila mraedteiartdioirne cptiaotnteartna,  zinecrroedaseignrge etahneg  ltehiicskmneesass unruedm. erically  at  9  points  along  the  diameter  direction  at  a  zero  degree  angle  is  measured.  38As  it  can  IbSeS Ns: e19e8n5 -3i1n5 7 FiguVroel. 1101, Nvoa. l1ueJa  ntuhaircyk-eJnuinneg2 01t6erms  are  in  micrometers.  It  should  be  noted  that  due  to  the  fact  that  small  thickness  is  increased,  the  amount  of  increase  will  have  negligible  effects on the nature of the sheet metal forming. 

4.5         Distribution of thick sheet metal with circular‐radial  radiation    To  investigate  the  formation  of  dome‐shaped  pattern  by  circular‐radial  rLaadseiraFtoiromnin gpofaMtteetarlnlic, Dionmcer‐SehaaspeidnPga rttshUes intghSipcikranl aensdsR  andiualm‐Ciercruilcaar lSlcyan  Paatt hs9 points  along  the  diameter  direction  at  a  zero  degree  angle  is Amseiat scuanrebde. seen in Figure 11, value thickening terms are in micrometers.IAt ssh  oitu  ldcabne  nboe tesdeethna  tind uFeitgoutrhee  f1a1c,t  tvhaaltusem  tahllictkheicnkinnges  steisrminsc reaarsee  din,  tmheicarmomouetnetros.f  iInt crsehaosueldw ilbleh anvoetende gltihgaibt leduefef ectots  othnet hfeacnta  ttuhraet osfmthaell sthheicekt nmeestsa  lisf oirnmcrineags.ed,  the  amount  of  increase  will  have  negligible effects on the nature of the sheet metal forming. FFigiguurere1 111: :T Thhicickknneessssd disistrtirbibuutitoionnb byyc ciricrcuulalar‐rr‐araddiaial li rirraraddiaiatitoionn     5.0  FORMING  A  BOW  L  SHAPE  BY  SPIRAL  5 .0 FEOXRPMOISNUGRAEB  OWL SHAPE BY SPIRAL EXPOSURE    iIs  nnhrsInauectd rehofcitinaaosmtctniepenetd aiutin panoaule tniraitno ,htsinatihoseoenn refpm ettwoa hsmpfe oepetsfrahtt,saut ephlad  i irsyhnnatau aeltsbdwpeobrya muet ptetaesanlbr taonhopsfu ea rhsrotsp afpsolishoarr aossmbleew erdipen n.angfTtio tnohpremfrFirsbnoiigo pnauwogasrts  lehse‐oshd1fiho2 s. aw.brTpHoanhedwed iiisnlna s‐ct supeeFhra,difattgahhpouc ienersides     p1a2th.  Hweanscien,v  tehsitsi gpaatethd  bwyasth  ienevxepsteirgiamteedn tbayl a  tnhde FeExMperainmaelynstiasl.  and  FEM  analysis.  FFigiguurere1 122: :S Sppiriaral lp paatttetrenrno obbsesrevrvededi nint hthees tsutu ddyy tFh tFihgeigeul uarlaebrebo1 or13ar3ats ohtsohroyrowywu sunstn dhtdheeereir an ianss tspsatpialrlilaarlaaltiltpo ipoananttot etoferfnsr nhs.h.e eeet tm meetatal la annddl alaseserri rirraraddiaiatitoionni nin   ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 39  

  Figure 12: Spiral pattern observed in the study    JouFringaul orfeA 1d3v asnhceodwMsa nthufea citnursitnaglTlaetcihonnol oogfy sheet metal and laser irradiation in  the laboratory under a spiral pattern.      FFigiguurree1 133: :S Sppiriraal le exxppoossuurereo onns shheeeettm meetatal l     5 5.1.1        Deformation caused by helix radiation on the sheet    DDeefoforrmmaatitoionn ccaauusseedd bbyy nnuummeerricicaall aannaalylyssisis frfroomm ththee ssppiriraall ppaatteterrnn isis  ssppeeccifiifeiedd inin fifgiguurree 1144. . BBaasseedd oonn ththee ililulusstrtraatitoionn, , ththee ddisispplalacceemmeenntt ooff  eeddggeea alolonnggt htheez zeerrood deeggrreeeed dirireeccttioionni sisp poossititivivee..A Alslsoo, ,d disispplalacceemmeenntto off  eeddggeea  loanlogntgh e t9h0ed  e9g0r eeddeigrreeceti ondiirsebcteitotner  tihsa  nbtehteteerd  gtehadnis ptlahcee meedngte  bdyiscpirlaccuelamre‐rnatd biayl cpiracttuelranr‐raanddiailt pcatntebrne asenedn it hcaatn sbpeir sael epna tharte spuilrtasl  inpadtho mredsu‐llitkse  isnh  adpoem. Oedf‐lciokue rsseh,atphee. vOalfu  ecsouorfse,d  gtheed  ivsaplluaecse moefn  tedbgye  cdiricsuplarc‐ermadeinatl bpya tchiracnudlasrp‐riaradliapla pthatwh earnedd sipffierraeln pta. th were different.  It can be noted that, the spiral pattern is better than the circular‐radial JournalI otofn cAaedn vianbn ecaecdnh Moietaevnduinfatgcht uadrtoi,nmtghTeee scshhpnaiorploaeglydp faotrtemrns. is better than the circular‐radial  one in achieving dome shaped forms.   FFiigguurree 1144: :SSttaattuuss ooff sshheeeett mmeettaall bbyy ffoorrmmiinngg aa ssppiirraall ppaattteerrnn    55.2.2         TThhee eeddggee ssyymmmmeetrtyry bbyy ssppiriaral lirirraraddiaiatitoionn    InIn  ththee  fofolllolowwiningg  ddiaiaggrraamm, ,ththee  sstatatutuss  oof fththee  ddoommee‐s‐shhaappeedd  pprroofifliele  oof f eeddggeess isis sshhoowwnn bbyy ssppiriraal lirirrraaddiaiatitoionn. . In  addition,  the  symmetry  of  the  dome‐shaped  surface  that  was  foInrmadeddi tbiyo ns,ptihreals ypmatmterentr yiso afltshoe sdhoomwen‐.s Ahasp iet dcasnu rbfae cseetehna tfrwomas fFoigrmureed  1b5y  aslponirga ltphaet tzeerrno isdeaglsroees haonwdn  9.0A  ds eitgcreaen  dbieresceteinonfr, otmhe Fvigauluree  1o5f  eadlogneg  dtihseplzaecreomdeengtr eaeloanngd  9th0ed  edgirreecetidoinre  octfi ozne,roth  edevgarlueee oisf epdogseitdiviesp  alancde mit eins t aabloountg  3t hme mdi.r eLcitkioenwoisfe,z etrhoe dveaglrueee  oisf  peodsgieti vdeisapnldaceitmisenatb  oaulotn3g mthme . direction  of  90  degree  is  positive.  In  terms  of  edge  symmetry,  formation  made  by  spiral  pattern  to  achieve  dome  shape  is  a40ppropriate. IFSuSNrt:h1e9r8m5-3o1r5e7,  forVmoli.n1g0  a Nboo. w1 lJ asnhuaaprye - aJunnde 2m01o6tion  of  the  positive edge by spiral radiation pattern is remarkably improved and  is better than circular‐radial pattern.   

edges is shown by spiral irradiation.  In  addition,  the  symmetry  of  the  dome‐shaped  surface  that  was  formed by spiral pattern is also shown. As it can be seen from Figure  15  alonLga setrhFeo rmzeinrgoo fdMeegtarlleiceD  oamned‐S h9ap0e ddPeargtsrUeesi ndg iSrpeircatliaonnd R, atdhiael‐ Cviracululaer  Socafn  ePadthgse  displacement  along  the  direction  of  zero  degree  is  positive  and  it  is  about  3  mm.  Likewise,  the  value  of  edge  displacement  along  the  Ldikireewctiisoen,  thoef  v9a0l udeeogfreeed  gise  dpiosspitlaivce.m  Ienn t taelromnsg  othf e eddigrec  tsioynmmofet9r0y,  dfeogrrmeeatiisopno  simtivade.eI nbteyr msspoirfaeld  gpeastytemrnm  ettory  ,afochrmievatei ondmomade e bshyaspeir alis  paapttperonptroiaatceh. iFevuertdhoermmeosrhea, pfoerims ianpgp rao pbroiwatle .sFhuaprteh earnmdo  mreo, tfioornm  oinf gthae  bpoowslitsihvaep eedagned bmy osptiiornal orfatdhieatpioons iptiavteteerdng ies bryemspairrkaal bralyd iamtipornovpeadtt earnnd  isisr ebmetaterrk athbalyn icmirpcurolavre‐draadniadl ipsabtetettrenr. than circular‐radial pattern.     FiFgiugruere1 51:5D: Diaigargarmamo fotfh tehed odmome‐es‐hsahpaepdedp rporfoilfeilew withitha as psipriarlapl aptatettrenrn   55 ..33         Evaluation of the stress distribution in the forming process of   laEsvear liunastipoinra ol fi rtrhaed isattrieosns distribution in the forming process  F  igure 16ofs lhaoswers inth sepierfafel citrroafditahteiovno  n mises stress and the residual sF trigesusrev a1lu6 esshoonwgse othmee  etrfyfeocft wofo rtkhep iveocen. Imt iisseosb ssetrevsesd  athnadt  the rreessiidduuaall  ssttrreesssse svaarleuems ooren ugneifoomrmetrtyh aonf thweodrkis trpiibeuctei.o  nIt oifsr eosbidseuravlesdtr  etshsaets  tohne   criersciudluara‐lr asdtrieaslspeast taerren .mTohreer  euansiofonrsma rethtahna tt,hfier sdtliyst,rtihbeustipoinra  lopf artetseirdnuiasl  nsotrtecsosmesp  olenx  coirmcuplar‐erdadtoiacli rpcuatltaerr‐nra. dTiahlep  raettaesronnas nadres etchoantd, lfyi,rstlayr,t itnhge  psopiinratsl apnadtternnd ins gnpoot icnotms opflespx icraolmrapdairaetdio tno pcairttceurlnasr‐arraedmiaul cphatlteesrsnt haannd  tsheactoonfdcliyr,c usltaarr‐triandgi alproaidnitast ioanndp atetnerdnisn.g  points  of  spiral  radiation  patterns are much less than that of circular‐radial radiation patterns.    FFigiguurere1 166: :R Reessididuuaal ls strteresssseessi ninc ciricrcuulalarrs sppiriaral lp paattteternrn   5.5          Examining  the  temperature  distribution  of  the  spiral  beam  path     Temperature  distribution  of  the  upper  and  lower  surfaces  of  sheet  metal  undIeSrS N:th19e8 5-s3p15i7ral  Virorla. d10iatiNono. 1inJadniucaartyed- J unheo2w01 6 the  proces4s1  happened in the sheet.  In Figure 17, the status of temperature changes under spiral radiation 

Journal of Advanced Manufacturing Technology   Figure 16: Residual stresses in circular spiral pattern   5.5 Examining the temperature distribution of the spiral beam5.5         pEaxtahmining  the  temperature  distribution  of  the  spiral  beam T  emperaptuarteh  distribution of the upper and lower surfaces of sheetmTeemtapl uernadtueret hdeisptriirbaul tiirornad  oiaf titohne inudpipceart eadnhdo wlowtheer psruorcfeascsehs aopfp  eshneedt imn ethtael shuenedt.er  the  spiral  irradiation  indicated  how  the  process happened in the sheet. IInn FFiigguurree 1177,, tthhee ssttaattuuss ooff tteemmppeerraattuurree cchhaannggeess uunnddeerr ssppiirraall rraaddiiaattiioonn iiss  iinnvveessttiiggaatteedd.. AAccccoorrddiinngg  ttoo  FFiigguurree  1177,,  tthhee  lleessss  hheeaatt  ggrraaddiieenntt  hhaass ooccccuurrrreedd bbeettwweeeenn uuppppeerr ssuurrffaaccee aanndd lloowweerr ssuurrffaaccee sshhoowweedd tthhaatt tthhee bbuucckklliinngg mmeecchhaanniissmm uunnddeerr ssppiirraall rraaddiiaattiioonn hhaass ooccccuurrrreedd..     FFiigguurree1 177::T Teemmppeerraatuturreed disistrtribibuutitoionni nint htheee exxppoossuurreeo offt htheeu uppppeerra anndd   lolowweerrl alayyeerrsso offt hthees sppiriraallr raaddiaiatitoionn 6.0 CONCLUSIONIn this paper, the effects of circular‐radial radiation to form domeshapedprofile/pattern by laser were investigated experimentally andnumerically.In the laser forming process, domed steel parts produced by circularradialpattern have no axial symmetry and the final form produced by circular‐radial irradiation pattern along an axis has positive displacement valuewhile the other axis has negative displacement value. In other words,the final shape is saddled‐like one.In the final form, which is irradiated by circular‐radial pattern, it doesnot lead to uniform displacement. Therefore, this irradiating patternhas not been industrially applied. Furthermore, the edges condition ofthe formed plate has no adequate quality as compared with the spiralpattern.42 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Laser Forming of Metallic Dome‐Shaped Parts Using Spiral and Radial‐Circular Scan PathsIn a circular‐radial radiation pattern, buckling mechanism undercircular‐radial radiation was created.In terms of the distribution of residual stresses, due to an immensevariety of the circular‐radial irradiation and the exposure pathparameters, the final form does not have any appropriate conditions.Precisely, residual stress is very high and it has bad effect on microstructure of work‐piece.For the proposed spiral radiation pattern, in terms of shaping sheetmetal into a bowl, the symmetry boundary conditions are better thancircular‐radial radiation patterns.In terms of the distribution of residual stresses, multiplicity andcomplexity of the spiral radiation pattern on the metal blank is simplerthan circular‐radial radiation. Likewise, because of the starting pointsand end points of laser radiation on work piece that result in an increasein stress on the blank, work piece under spiral irradiation has betterforming condition than that under circularradial irradiation. Moreover,stress distribution in work piece under spiral pattern is more uniformthan that of circular‐radial pattern.According to the influential parameters of buckling mechanism whichrooted in low temperature gradient along the thickness, spiral radiationpattern contributes to thermal buckling mechanism.REFERENCES[1] H. C. Jung, “A study on laser forming processes with finite element analysis“, PhD thesis in Mechanical Engineering at the University of Canterbury Christchurch, New Zealand, pp. 27‐31, April, 2006.[2] F. Vollertson, “Mechanisms and models for laser forming”, Proceedings of Laser Assisted Net shape Engineering Conference, pp. 345‐359, 1994.[3] J. Kim and S. J. Na, “Development of irradiation strategies for free curve laser forming“, Opt. Laser. Technol. Vol. 35, pp. 605‐611, 2003.[4] J. Kim and S. J. Na, “3D laser‐forming strategies for sheet metal by geometrical information“, Opt. Laser. Technol. Vol. 41, pp. 843‐852, 2009.[5] K. G. Watkins, S. P. Edwardson, J. Magge and G. Dearden, “Laser forming of aerospace alloys“, Conference, Washington, US, 2001.[6] S. P. Edwardson , G. Dearden, P. Frenchl and K. G. Watkins , “Laser forming of metal laminate composite materials“, ICALEO2003 Laser institute of Orlando, pp. 225‐339, 2003.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 43

Journal of Advanced Manufacturing Technology [7] S. P. Edwardson, K. G. Watkins, G. Dearden, P. French and J. Magee, “Strain gauge analysis of laser forming“, Journal of Laser Applications ,Vol. 15, pp. 225‐ 232, 2003. [8] Edwardson, S. P., Moore,S. A., Abed, E., McBride ., Dearden, G., Jones, J. DC., Watkins ICALEO 2004 Conference Laser Institute of Orlando, pp. 682‐693, 2004. [9] S. P. Edwardson, E. Abed, P. French, G. Dearden, K. G. Watkins and R. McBride, “Development towards controlled three‐dimensional laser forming of continuous surfaces“, J Laser Appl, pp.17, 2005. [10] C. Liu and Y. L. Yao, “Fem‐based process design for laser forming of double curved shapes“. Journal of Manufacturing Process, Vol. 7(2), pp. 109–121, 2005. [11] K.G. Watkins, S.P. Edwardson, J. Magee, G. Dearden, P. French, R.L. Cook, et al. “Laser forming of aerospace alloys“, Society of Automotive Engineers; (2001). [12] T. Hennige, “Development of irradiation strategies for 3D‐laser forming“, Journal of Materials Processing Technology, Vol. 103, pp. 102‐108, 2000. [13] H. Shen and Z. Yao, “Study on mechanical properties after laser forming“, Opt. Lasers. Eng. Vol. 47, pp. 111‐117, 2009. [14] S. S. Chakraborty, V. Racherla, and A. K. Nath, “Parametric study on bending and thickening in laser forming of a bowl shaped surface“, Opt. Lasers. Eng. Vol. 50, pp. 1548‐1558, 2012. [15] K. Masubushi and W.H. Luebke, “Laser forming of plates for ship construction“, submitted from Massachusetts Institute of Technology, pp. 189‐ 196, 1995. [16] ABAQUS software, 2012, Version 6.0, ABAQUS Inc., USA.44 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Failure Mode and Effects Analysis of Ship Systems Using an Integrated Dempster Shafer Theory and Electre Method FAILURE MODE AND EFFECTS ANALYSIS OF SHIP SYSTEMS USING AN INTEGRATED DEMPSTER SHAFER THEORY AND ELECTRE METHOD I, Emovon School of Marine Science and Technology, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK Email: [email protected] ABSTRACT: Failure Mode and Effects Analysis (FMEA) is a risk analysis tool which is used to define, identify, and eliminate known and/or potential failures from a system. The task is generally performed by a team of experts. Each of the team of experts can express diverse opinions in rating of failure modes of systems which may be in the form of precise data and imprecise distribution ratings. However the RPN of FMEA is incapable of using these various forms of information in the prioritisation of risk of failure modes. This is one of the main limitations of FMEA. Furthermore the technique is limited to the use of three decision criteria thereby excluding other important decision criteria such as production loss in prioritising risk. To address these problems a novel FMEA tool was proposed which combines Dempster Shafer Theory with the ELECTRE method to provide a more efficient failure mode prioritisation method. The Dempster Shafer Theory was used in aggregating different failure mode ratings from experts and the ELECTRE method was applied in the ranking of failure modes. The applicability of the proposed technique was demonstrated with a case study of a marine diesel engine. The results showed that the proposed method could be applied in addressing risk prioritisation problem more efficiently than the FMEA and its variants. KEYWORDS: Dempster Shafer Theory, ELECTRE method, FMEA, ship system.1.0 INTRODUCTIONShip system operation requires high levels of safety and reliability andthese can only be accomplished by having an effective maintenancesystem in place. Basically, maintenance system consists of three majorelements that must perform optimally in order to attain high levelof the ship system safety and reliability. The three main elements ofmaintenance management system are risk assessment, maintenancestrategy selection and maintenance task interval determination. Thefocus in this paper is the risk assessment component and it is verycentral to the operation and maintenance of ship system because themaintenance task to be performed on each of the equipment item ofthe system is a function of the assessed risk. Failure Mode Effect andISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 45

Journal of Advanced Manufacturing TechnologyAnalysis (FMEA) is one of the most popular and powerful tools forassessing risk of ship systems [1, 2]. The technique was first proposedby NASA in the 1960s as a tool to identify and eliminate complex systemfailures in order for the system to achieve desirable levels of safety andreliability [3]. In analysing risk, FMEA puts into consideration howequipment items fail, the effect of an individual failure on the entiresystem and possible means of failure detection. Traditionally, FMEAuses Risk Priority Number (RPN) in evaluating and prioritising risk.FMEA is defined as the product of three risk criteria; probability ofOccurrence (O), resulting level of Severity (S) and the inverse of theability to Detect (D) the failure before it occurs. In assigning values tothese three risk decision criteria an ordinal scale of 1‐10 is generallyapplied by most researchers and industries [1,4,5]. Despite thepopularity of the FMEA it has some limitations which has affected theefficiency of the tool in prioritising the risk of failure modes of mostcomplex system of which the ship system is not excluded. Some ofthese limitations are: (1) the inability of the tool to utilise more thanthree decision criteria in prioritising risk of failure mode (2) the inabilityof the tool to consider the relative importance of decision criteria inthe risk decision making process (3) the inability of the technique toutilise imprecise information from experts and (4) the questionable anddebatable mathematical formula use in aggregating risk criteria[4, 6].To overcome the limitations of the traditional FMEA, differenttechniques based on the Multi‐Criteria Decision Making (MCDM) havebeen developed in literature. Braglia [7] presents a technique based onAnalytical Hierarchy Process (AHP). The AHP is used as an alternativeto the RPN in aggregating four risk criteria; O, S, D and expected cost,for the prioritisation of causes of failure for an Italian refrigeratormanufacturing firm. Zammori and Gabbrielli [8] propose AnalyticalNetwork Process (ANP) approach for prioritising failures in FMEAsystem. The authors consider three risk criteria, O, S and D in prioritisingrisk of failure mode. The use of the ANP allows the interrelationshipbetween risk criteria to be considered in the decision making process.Maheswaran and Loganathan [9] present a methodology based onPreference Ranking Organisation Method for Enrichment Evaluation(PROMETHEE as an alternative for the RPN used in the traditionalFMEA, for ranking risk of failure modes of a boiler system.All of the aforementioned papers have improved the efficiency of thetraditional FMEA system, as it is possible to utilise more than threedecision criteria in the ranking of risk of failure mode. Furthermore,the risk of different failure modes is better distinguished with variousMCDM tools than the RPN of the FMEA system. However, the MCDM46 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Failure Mode and Effects Analysis of Ship Systems Using an Integrated Dempster Shafer Theory and Electre Method tools applied increases the evaluation process complexity as the number of decision criteria increases. Furthermore, the techniques only allow the use of precise information from the experts in the decision making process whereas in real life situation the data may be precise or imprecise or a combination of both. There is a need to develop a more systematic approach for prioritising risk of failure modes of ship systems. In order to overcome the challenges of the traditional FMEA and its variants in literature this study proposed a novel FMEA tool which combined Dempster Shafer Theory with the ELECTRE method. The Dempster Shafer theory technique was applied in aggregating different assessment which may be precise or imprecise from the experts that make up the FMEA team. The ELECTRE method is applied in the ranking of risk of failure modes of the ship system. 2.0 METHODOLOGY 2.1 Dempster Shafer Combination theory The origin of Dempster Shafer Theory (DST) can be traced to Dempster [10] who develops the theory of upper and lower probabilities and Shafer [11] who further improves on the technique. The tool has been used in different fields in modelling and aggregating empirical evidence in individual’s mind. DST has been integrated with the RCM logic tree in the selection of optimum maintenance strategy for different complex systems [12]. The technique has been applied in solving data inconsistency in reliability decision problem. Due to its remarkable success in addressing problem of data uncertainty in different domain, it is combined with the ELECTRE method in this paper to address the problem of data imprecision in risk prioritisation problem of ship system. The basics of the DST are presented in this section and are as follows [12, 13]: Let be a finite set of mutually exclusive and exhaustive hypothesis. The set generally refers to the frame of discernment. A function m(Y) is defined as the Basic Belief Assignment (BBA) if the following conditions are satisfied.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 47

   Let L�e tb  �e   ba ef ian iftien isteet  soeft  mofu  mtuuatlluya lelyxc  eluxscilvues ivane da nedxh  eaxuhsatiuvset ivhey phoytphoesthise. sis.  TheT  sheet  sgeetn  geernalelrya lrleyf erresf etros  tthoe  tfhrea mfrea mofe  doifs cdeirsncemrnenmt.e nAt .f  Aun  fcutinocnt iomn( Ym) (iYs )  is  adreefJ iadosnureareeftnd iisans lafaeoitsdefis Ad tfahd.i seve ad tnBh.c aeeds BiMca asBnieuclf aiBectefu lrAiiensfg sATigescnshimngonelonmgyt e(nBtB (AB)B iAf )t hife  tfhoel lfoowllionwgi cnogn cdointidointsio  ns    m:2  [0,1]                                                 m(Ø )  =   0                                                  A nAew nn eBewwB ABB,B BmAA(,C, mm),( (CcCa)),n ,c bcaaenn  fbobere mfoferodmrm ferdeod mfrfo rtmhoem  tchotehm ecobcmionmbatibinoiannta iootifno t nowfoo tf wBtBow ABosB BA  BsA  s m1(Ym)11 (aYn)d a nmd2( Zm)22 ( (ZY)  a (nYd a nZd b Zel obneglo tnog s teot  s�e)t,  a�s), f aosll foowllso:w  s:    Journal of Advanced Manufacturing Technology (1)             But But     Yw hawYinchadhin c Zddh.e Zdn.eonteost etsheth deedgreeger eoef ocfoncoflnicflti cbtetbwetewenee tnwtow boobdoiedsi eosf oefveidveidnecen,c e,  ThTeh  aepapplipcalitciaotnio  nof otfhitsh icsomcobminbaintiaotnio  nrulreu lfeorf oargaggreggraegtiantgin  gdifdfeifrfeenret nt opoinpiionnios nosf oefxpexeprtesr atss aits ciot ncocnercnesr nrsisrki sokf ofafiflauirleu rme omdoeds epsriporriiotirsitaitsiaotnio ins is dedscersicbreibde ads afos lfloolwlosw [4s,[ 64],.6  ].  � = [=1,[21,,32,,43,,54,,65,,76,,87,,98,,190,1] 0i.]ei.. eo.rdorindainl aslcaslcea l1e t1o t1o01 r0atriantgin fgorf orrisrki sdkedciescioisnio  n cricterirtiear;i a; m(Y )rreepprreesseennttss  the pprroobbaabbiliiltityyr  artaitninggg iv  egnivbeyn ebxyp eertxspwerhtsic  h whsiucphp sourpt porortp posroitpioonsiYti.oYn iYs .t hYe issp tehceif iscpveacliufiec fvraolmuet hfreosmet thteo saedt e�c  itsoio  n a dcercitiesrioionn c. riterion.   ExEamxapmlep:l eT:hTeh cerictreirtieornio Dn ,D r,atreadte bdyb tywtow eoxpexeprtesr tfsorf ofraiflauirleu rme omdoed 1e i1n in TaTbaleb le33  isisu  suedsetdo dteom  odnesmtroantestrhaeteD emthpe stDereSmhpafseterrT hSehoaryfecro  mTbhienoartyio  n comrubleinaaptpiolnic arutiloen a. pFprolimcaTtiaobnl.e F3r,otmhe Traisbkler a3t,i nthgeo rfisckri treartiionng Dof, bcryiteexrpioenrt  1 D,i sby4: 7e0x%pearnt d1 3is:3  40:%70a%n danthda t3:o3f0e%x paenrdt  2thisat4 :o4f0 %exapnedrt 52:6  i0s%  4.:40%  and  5:60%.    The discernment frame for this problem is formed as = [3, 4, 5] and the ThBeB dAissciesrnasmfeonllto fwrasm: e for this problem is formed as � = [3, 4, 5] and  the BBAs is as follows:   m1(3) = 0.3, m1(4) = 0.7, m2(4) = 0.4 and m2(5) = 0.6    48 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016  

D,  by  expert  1  is  4:70%  and  3:30%  and  that  of  expert  2  is  4:40%  and Failure Mode andD5 TtT5 thE:hh6,:efh 6fe0eeb eB0c % ydtB %Bsd .iBA eAs.icxn Asseapc lrsiyeesns rr iimastsn so 1meaf f Snsoihe tslif n lpofo4rtSlw:a yl7fmos0srtwe:%aem m  ssfao:Ue nrs  difntoh g3ria:s n3t p0hIn%ritose g barpalnetredmod bD tihlesema mfpto stor eimfrs Se ehfxdaopf eraremsrTt he� e2od r= y i sa[a 3sn4,d  :�44E ,0l =e%5c t]r[  e3aaM,nn 4eddt,h   o5d] and     m1m(31)( 3=) 0 =.3 0, .m31, (m4)1 =(4 0). 7=, 0m.72(,4 m) =2 (04.4)  =a n0d.4 m a2n(5d)  =m 02.(65 ) = 0.6                  For this problem, expert 1 and 2 combine rating for criterion, D,  =3×0+4×1+5×0=4  2.2 ELECTRE METHODThe ELECTRE method development and origin can be traced to Royand Vincke [14] and the acronym, ELECTRE, stand for, Eliminationand Et Choice Translating Reality. The basic concept of the multicriteria technique is based on paired comparisons of alternatives withreference to some certain decision criteria. The technique has been usedby different researchers in solving multi‐criteria decision problems indifferent domain. Shanian, Milani, Carson and Abeyaratne [15] utilisethe technique in solving a material selection problem and Sevkli [16]integrated ELECTRE with a fuzzy logic technique in addressing asupplier selection problem. The method is applied in this paper, toaddress the challenge of risk prioritisation of ship system. The stepsinvolved in the ELECTRE method are as follows [17]:Step 1: Decision matrix formation: ELECTRE method process beginswith the construction of a decision matrix with alternatives, j withrespect to criteria, i. Since the Dempster Shafer theory is integrated withthe method, the evaluated data from the Dempster Shafer combinationrule is used to form the decision matrix. An example of such a decisionmatrix with element xij is presented in Table 1.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 49

the  construction  of  a  decision  matrix  with  alternatives,  j  with  respect  to  criteria,  i.  Since  the  Dempster  Shafer  theory  is  integrated  with  the  method,  the  evaluated  data  from  the  Dempster  Shafer  combination  rule  is uJsoeudrn taol o ffoArdmva ntcheed Mdeancuisfaioctnur mingaTtreicxhn. oAlongy example of such a decision matrix  with element xij is presented in Table 1.    TabTlea b1l e: I1n:sIpnescpteicotnio innitnetrevravla laaltleterrnnaattiivveess ddeecciissioionnt atbalbele  Failure modes (Aj)  Decision criteria (Bi)  O  S  D  A1  x11  x12  x13  A2  x21  x22  x23  A3  x31  x32  x33  Journal of Advanc…ed Manufacturing Technology …  …  …  Jo  urnal of AdvAanmc ed Manufacturing Technology xm1  xm2  xm3 Journal of A  dSvta   eSnpctee d2p:M 2Na:noNurfaomcrtuamrliinasglaiTtsieaocthnino oonlof ogtyfheth deedciesciiosnio mn amtraitxr:i xT:hTeh neonromramliaslaitsiaotnio onf otfheth  e     dedcSietsceiiposn i2o :mn Namotrarimtxr ixaxilji xissiaj tpiisoernpf eoorrffm othremed  edades cafiosslifloonwll omsw:a  str:ix: The normalisation of the  S  tep 2: Ndeocrimsioanli smataiotrnix o xf ijt hise p deercfoisrimone dm aast rfioxl:l oTwhes : normalisation of the  dec  ision matrix xij is performed as follows:   (2) Where pij is the normalised decision matrix  Wher Set eWpW pij hh3ise:e rWtrehee pp iingijj oihsrt methdae ln insooerdrmm daaleilcsisiesedido m nd aemtcraiistxiro ifxno r mmaattriioxn  :     T Sdi sthe epce pir s eTdi3iwsso:he e TSdinpWecTSdienstsi eihr theetsgc peeceeepicprwehsirpiodiirsg eettsn 3eie eewn3shiaows: iorde:ttsgcne WeienneWe  ranhifddi itgc oentttgcew re eeehliranodhilgirddittsoegorttieeh   aiaemewhrafdrgtsrd omnitsewhisaael  fado:lftoadn oe oiswrnlswln iom,wilnoeg sleoorwoedorehsaimwrimgwd:jr ltmg, i mshsa shwmsam,:alte :ltiasw liidssaa,ilste,sitjh te ,wsrde rwd eiwmidjtx,xdj h, i  awmm etfwmmthov riaaniir taijat tthtxmothhrtrr ririi etiasxximthxvx  thn iife jaeoo fovoovl nnbriiirnjirsmsjtom: mo ea  irdairisamoasnmt l btideiaoiosatdooelenablinbc idsi:tsint:eabs  eadde iiydinoden  dnec dedmi edebsmcic yuioiabs lbsnittyioyrim opimn xnlum ym amalmittunnuriapalidglttxttlri  r iypipaixixlnnly yadgaiinnn  ndgdg        Step 4: Concordance interval matrix fo rmat ion:  Give n a p air of failur(e3 )      moSSdtteeepps, 4 4(:a: ClCtoeonrnnccaootrridvdaeansn)cc eAe iji nnattneerdrvv aAallk ,m mtahatetr ricixxo fnfoocrormmrdaaattinioocnne::  GiGnidivveeexnn   aa ppaaiirr ocofaf nffaa ibillueu rree  mSteopd ete4hss:, teem Cmei (smswaoototildnaimtedmetceieegarosasdnt,hrt,ea d e(tda(aetdaaisdlvn lt ata etecsenhsrser noet) nth i rahnAasmetetutijei v asmvasreuluevnis mssamd)oe)lf  Ad   AAomoa jfskjfl aa,lc  aa ntaotnwlrhldrildex eww  A ifAcogeokoefh,ikr i,ngt tgAmshhcthh jota eftsiertosscdi  r focofgao onotnnrrhnr:ec c otcGaoethoshtr ioeerdivondr saesd edaentnehne d ccdaxaceie e nespci ic inoiaoisnsndiirrido  eo ecneoxnqrxf ic uc tccfr1eaar(irijitlnt1il e,aeut robr kriwia )eeaA  c hwcwkae,a nharnhese eb  rbreeee   te hstei mwfaoetlitfeltfghoohodhlewle ltoa oweswwsdw:e e stisnh:ig:go ehh rtsmteeuddaml nin soooerfdrm ma  salalcl loiwisrseeeed diog sfhsc ctAosor jr efieos or ogf  ftr AheAojajs itsieesr g d gtrehreceaaiantseti eorornrt  h  tehcaqraniunteao rolri rate o eqw quAuhakea,l  arlt esot  oA  Ak,k, aass  foll ows:       Where vi(j) and vi(k) are the weighted no rmali sed s cores  of the jth an(d4 )  Wkt hthe h anel rkttueheths re auWveWktnanlhsdtit(halhe ee jth ut)dteerani eosnvrral ret tneuaenfoeedoasstv dri  vfetrnitv (oimrdoivvj(aeer)j  ites)m(f stait koospvharn) r ee etnfemdrahocss edrctp erv sie otmrepvivhc( enctkieeo(e shct)tklcnp ihyoec)atvce ir .oereav owcd enlTrcteryaieceotdlhvn.hyo inaegteTcer.hcn  lhdehyoweTcc tameor .eeh wendndTecmiacagce o htennoihrcan egiomcrottcx hdreernoc iam dtaaxcmoretnsodrndnaa aicrfalcos xdoetinnosr r flaaioemrcloexnsodedrlv  awlmcafa oaeoelsnsilvswac l suc:lfoalee ooesialvrds: wulteealieoassodlsv cutwn: oia osao flsrct run:eiote oahsrsrnteeueoi s osflj rtunttohseh l  fsat reausnterhjldasettheusr   a eljntathstr dh aeaen krntdhe    50 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016        Step 4: Discordance interval matrix formation: The discordance in dex 

  Where vi(j) and vi(k) are the weighted normalised scores of the jth and  Failurke tMh oadeltaenrdnEaffetcitvs eAsn alryesispofeSchtipivSeysltyem. sTUhsieng  canoInntceogrradtedanDecmep setevr aShluafeartTihoenor yraensduElletcstr eaMreet hod then used to form the concordance matrix as follows:      (5 )Journal of AdvaSnJJ  ootceuuedSdrrpJ  nn1Mto(aa euj4llarp  ,oonn:ff ku,a  AAD 4lf)i a,odd:scifvvti  sDAuaa scennrdiioccevvnseeavgrddacn d  aTloMMcueelardcaauadnhnn Mantuucaeofftaeaalnendocc guttdci uuyfnaearr aciistnntie:suggn :rr  TTitvneeegccarhh Tlvnn eooamcllhoolnggamoyytl  orgaiyxt r  ifxorfmoramtiaotnio: nT:hTe hdeisdciosrcdoardncaen cine dinexd ex       f Tohrem  i tnhfeo rdmisa  ffT  TcootohhirrfToreemmo fT dnho  rha ii  remttnnneomhh ffcbieeooi netttn  rra hddhfmmmfioeiieonss aaarreccddmmtttoodriiiisoorri asaxcddnnftco triaap  oioornnooordrmneccbbnda eestt noaaae  tommcbniinhnnbetteaacaee et mtteiadddrrdnii   amxxieanffstd  srrrceppa ooi ofdxrrtmmofreer rdlpissofl  xeeorramttennohhnwpstt meeceesrte  n:ddhe  ddtset  iiieaanhe ssdssdccdne   ooffeiatoosrrdxescddll  dlliofooaasiorsnnwwcadl loccstoasseehr::nwf    deociinsnnael: l ddn ouieecnwsxxede  sdeiii:ssnx    tdttoihhse  eextnnh  iesuun sst eehuddes  nettdoou   tsoe d(6  t)o   Trm  S etweseppaose  5uicn:tr iDdivnieecgtle eysrp T  T  S S  mrmr,a  m eettewwsneesseemrSTr ippppT  S  rmeaaeffoontw eoottsseees  ew  a 55eserluuiiccppaostlpnnp::maottiorr  useiioDDsedd ii 5wivv5upanncincniiee:nee:ntccetggrs  dttlliiDoDdeeirc:  eeyyvvn nissfeirrppeo  e ece,,g aammgt  tlreeethl sseynno yerrss  iirepv fpeeffffnn,ra,m   oooottaeapmeaasn  nfllrrls isstteralluemmffneiioouuifriooootfenlatowwf ppaaolrunnsostlarmsnn,eeiolssr  ur mootulrrecc::mwCpoai  iinffee pooon  aaew  sa ttm,nrroe rchh:nnoo   aiferseeovvocffc oni :t    edaaeropphdfoff  lleireeaavuuf tnos rr niihaeevp lldffffeuulssooea(eauet,,afrrrr  il xeapeellmmufCCi:utson  i eeeaa,laarrfmm,, rur  seemnnCnfaa, rroooccaanniaemC,eeddort ddn  iamreeaiivmoc  , nnn ssnneedv  addado seeaei((nnee) ttndaasl n  xxudc lldiiea::ettenne(   eeesrtansff xrrei,eelinnen  (:tnrr Deataaeiidfroolttveiantiie  rrnrvvaeua  xilfeervvotsu:essniaarevar))   lla  itevuuf oetaaosaeeid)rrrrvlss eeu  ,,vea    eDDsarees e)lvv,aa u  aaaDuueellrssvuuase eeaa,u    lttDeffsueeooevddaarr  at    fueoldusr  ea(t7feo)dr       (8)         (9)     brT  aehn eak vtiwnergoas g.p eTedhr  bbrrT T fetoaaeeohh nnTbtrt   eeaawwm br Tgkkoh  avveetthiiotanowwenee neha nkrrggre oovtraatcaissrcww  naeggena..ppa  r ngeetTTkoioeeaneddnski hhrrg .npd  ffo pbieeettToogneooiv  deecrrtths  gewwmm erggf etarcosfoee aooavoaa r.tnn flwnm  nngerloTrree  meccaarrroerraheenaa nnaai np  treanegttkkiihcareennrnkiieienet  anddoioocwd rtnkggiriivve enccbiigssot eentdeeo  e.oiirrcc gsssn iv aaraaac  isgeffalldnnnep lloorcen  gs  iprrarreeac n kaa  flliifnppeliottennai e hhsrrrnierkkdiila eeaioougpiif tnrrnitorrhrr  snekbbiiggeirettodieec.. iiron  mssrp  ia  aavbiigvnnntroppei.iei dggsd pp oraei  uellnaffrpiiaasatieelgp tiilhddw lllilfuuyresi  aeiiia irrrnnliodneellndd urb   gykmm iiirbneivveieofoodnii laaddmtdddighpivuuee l.o tiupcssaadwd  allrlwwullenioeyyesa ii    lldloomwlll  yrryy  iio bblniioleedoo rdlly tteddbhhiisev  o  ttlcc wwtidwaahd nnoo tuicw    laalnolyl  yieoldr  ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 51

JoJouurnr nalaol foAf dAvdavnacnedceMdaMnuafnacutfuarcitnugrTinecghTnoeclohgnyology   3.03 .0    C CAASSEES STTUUDDY   In tIhn itshsise csteicotnio,nt,h tehem marairnineed dieiesseell eennggiinne is coonnssiiddeerreedd toto ddememonosntsratrtea te thethsue istuaibtailbitiylitoyf otfh tehein itnetgegrarateteddD Deemmppsstteerr SShhaaffeerr tthheeoorryy aanndd EELELCETCRTER E memtheotdho. dT.h Tehme marainriened ideiseeslele ennggininee wwaass cchhoosseenn bbeeccaauussee iti tisi sonoen eofo tfhteh  e keykeshy ipshmipa chminacehryinseyryst esmyssteams ist parso viitd  epsrothveidpeos wtehre foprotwheerp  rfoopr utlhsieo n fsooohffrittapeocphhoancbrpeevcrogviriepeeinidinorennugeeudttl4n siis ia5trri on coeetupscchnssuoltea a hhurrotbiii amcnfppyt enth stsnsscaeh  yyetf  oeoSmsso fCrttw ef eeaotnommirhtvstmhieisne.re  arepeIse c n t4ahndcos5niotahitp ieyapdrirpspdeledei[  rcin1lisncs otg8yheeigm o]snni.iptntntgpeoI  ,isomtensuttfnyhieh .rst s saeheItiantnseemsht c m iutceeoaoaer  ndnrtnvCaaidtencolfori coytbecamoirolvocmr pmnafidtoaaora,ip nuu nritetinyglshhent  edeets[at  h1naocmoo8tag cipu]toaiti.enhd trntIrieebhe tanf  nyetoaeisistr couam  mccnfrtSoalhv,aaa uwueeroiilnnyinmtfin     stesss dienseolt  eonnglyin  ethies  cmeancthrainletroy tshyestoepmesr, atbiuont ,oof f tnhoe t eonntilrye thsheipm  asychstienmer y syspteomwse,rebdu tboyf  tthhies etnyptier eosfh  eipngsiynset. eAm  tpootawl eorfe d23b yfatihluirset ympoedoefs ewngerine e. A tiodteanl toiffie2d3 fiani lubrites mfroodmes  cwoemrbeiindaetinotnifsi eodf indibffietsrefnrot msocuormcebs insuatciho nasso  f difflietreernattusroesu, rcdeastas ulcohggaesdl itreercaotrudrse  sa,ndda teaxlpoegrgtse’ dorpeicnoiorndss. aCnaduesexsp eorft s’ opifnailounrse., Ctaougesethseor f fwaitlhu ree,ffteocgtse thfoer weaitchh efoffe ctshef orfaeialucrhe omf tohdeef aailruer  emopdreesaernetepdr einse Tnatbedle i2n.  Table 2.  Taabbllee 22:: FFMMEEAAf foorrm maarrinineed dieiesesel le nenggininee[ 2[,25, ,52, 02‐02‐42]4] S/  Failure   Failure cause    Local effects    Global effects  N   modes  1  Hole in the  Dripping of fuel valve  Escape of  Reduced engine piston crown  combustion gas  performance,  into the crankcase  engine damage  and stoppage 2  Piston ring  Lack of lubrication,  Oil smoke from  Reduced engine scuffing  liner roundness fault  exhaust, blow‐by  performance 3  Piston ring  Excessive gap  Oil smoke from  Reduced engine  cracked  pressure, worn‐out  exhaust, loss of  performance  ring groove  power 4  Piston ring  Liquid fuel degrading  Loss of power  Reduced engine  /groove side  lubricant in ring  performance,  face wear  grooves   Excessive  engine stop  Insufficient clearance  clearance, fire  Reduce engine 5  Piston ring  during installation,  blow  output, Stop  stuck in  deposits  ‐‐‐  engine  grooves  ‐‐‐  Allow air escape  ‐‐‐  into crankcase ‐‐‐  ‐‐‐  Not seated properly  Reduce engine  performance, 23  Crankcase  explosion  relief valve  probable  inoperable In this paper, it is assumed that the FMEA team consists of two expertswith equal expertise. Each of the expert ranks each of the 23 failuremodes based on 3 decision criteria; O, S and D on an ordinal scale of1‐10. Table 3 represents the failure modes rating by two experts of which52 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

    In  this  paper,  it  is  assumed that the  FMEA  team  consists  of  two  experts FailurewMiothde aenqd uEfafelc tseAxnpaelyrstisisoef S. hEipaScyhst emosf Utshineg aenxInpteegrrta terdaDnekmsp steeraSchha feor Tf hetohrey an2d3E  lfeactirleuMreet hod modes based on 3 decision criteria; O, S and D on an ordinal scale of 1‐10.   Tamraeemsbt olheepmo tr3hdee oorcaeildrsopoeegr leypoas rgenueyndcttii ulssi eotstiehtlahdiense  efdrdadseio lcdutaihresreeieco r imnssii maoocrdnrpeiertcsieerm rcriitiapasete rrin weiagcreia wisbtgeiyehn rittggaws.th  ioitnBns eg eix.tcnhpaBeuete hrsctdeeas e udoctsifhese cweioti shhnpieio crmnpohpr amsookopsaimneokdgesin   edg propcreoscse, stsh, etshee swe ewigehigtsh  tws ewree reeveavluaaluteadt eudsuinsgin  tgheth  Ae nAanlyatliyctailc aHl iHeriaerrcahrych  y ProPcreoscse s(As (HAPH) Pse)es[e1e9[]1 f9o]rf odredscersicprtiiponti oonf othfet hAeHAPH. PT.hTeh weewigehigtsh tosbotabitnaeidn ed forf oOr, OS ,aSnda nDd, uDs,inugs iAngHAP HarPe 0a.r4e, 00..44 ,a0n.d4 a0n.2d re0s.2percetsivpeelcyt.i vely.   TTaabbllee 33:: EExxppeerrtt 11 aanndd2 2i mimpprerecicsiesed deceicsiisoinonc rcitreitreiariraa rtiantging  Risk criteria rating  Failure  Expert 1    Expert 2  modes  O  S  D  O  S  D  4:70%  4:40%  1  7:30%  3  3:30%    7:30%  4  5:60%  8  7  8:70%        8:70%    5: 100%    2  7  6:50%  3: 80%    6  6  6    5:50%  2: 20%  4  5: 50%    5  8  3  5  6  4:50%    7:70%  4      6:30%    5:80%  4  7  3  …    6  7  6:20%      9:90%     …  8:10%    …    9  5  7: 100%  6    7:60%  …       5:40%  3      …  …  …  23  7:80%  2  6:20%        The Dempster Shafer combination technique was applied to the Thiem  pDreemcispestrear tinSghsafoerf  dceocmisbioinnatcirointe  ritaecbhyniqeuxpe erwt a1s anadpp2lieind Ttaob leth3e to imopbretaciinse argagtirneggsa toefd  dreactiinsigosn.  Tcrhiteeraiga gbreyg  eaxtepderrt a1ti nagnsd w2e  rine uTsaebdlet o3 ftoor mJ  ouodtrhbeneiaactn aliEsdoitniLofeoA EcntadiCh gvsmeaTigonRraEcneteELrgdmi EatxMotC aea(otrnTdlreu  RifffxroaeEacrr(tt  uritttnerhooifgn oeeTg slrra.Taf btoeTnoclrhkehT ntei4nhoa  lgaeb)o g glworeygafhr 4nfeiakcg)ihialwnu twegrhedaio  cmsfrh atfohtawdieinelnaugss su.r  te shwemeden roaedus  eusisens.depdua tst odi naftpoaru mitn tdoaa  ta  TTaabbllee 44:: DDeeccisiisoionnm mataritxrix  Failure mode  O  S  D  1  7.84  3.5  4  2  6.5  5.89  5.5  3  5  7  5.5  4  6.95  3.5  3  5  6.5  6.5  5  …  …  …  …  23  7  2.5  8.99    In  applyingIS  tShNe: 1E98L5E-3C15T7RE  mVoelt.h10od Ntoo .r1anJkan uriasrky -oJfu nfeai2l0u1r6e  modes,  th5e3  decision  matrix  in  Table  4  was  normalised  using  Eq.  2.  Then,  weighted  normalised  decision  matrix  was  obtained  which  is  a  product  of  the  normalised  decision  matrix  and  the  weights  of  the 

Journal of Advanced Manufacturing TechnologyIn applying the ELECTRE method to rank risk of failure modes, thedecision matrix in Table 4 was normalised using Eq. 2. Then, weightednormalised decision matrix was obtained which is a product of thenormalised decision matrix and the weights of the decision criteria.The formation of the concordance interval matrix and the discordanceinterval matrix using Eq. 4 and 6 respectively was then performed.Based on the concordance matrix and the discordance matrix, thenet superior, Ca, and net inferior, Da, values of the different failuremodes were calculated using Eq. 8 and 9 and the results are presentedin Table 5. Finally, the different failure modes were ranked using theirnet superior and inferior values and the rankings generated are alsopresented in Table 5. The performance of the different failure modescould be determined by applying either the net superior index or netinferior index or an average of both. For the net superior index, thegreater the value the higher the risk possess by the failure mode. Inapplying the net inferior value index in determining performance ofthe different failure modes, the lower the net inferior value the higherthe risk the failure mode possess to the system.From Table 5, the two ranking indices produce quite dissimilar rankingsfor all the 23 failure modes. The net superior index ranked failure mode 10 in the first position and as such was the most critical failure mode ofJournatlh oef Amdavarninceed dMiaensueflacetnurgining eT.ecThhnoelongey t inferior index ranked the same failuremode in the second position.     TaTbablele 55: :EELLEECCTTRREE IIIIr raannkkininggo foffa filauilrue rme omdeosdes Failure modes  Ca  Rank  Da  Rank 1  ‐0.4000  14  0.9508  14 2  1.6000  9  ‐9.4283  5 3  2.4000  7  ‐7.8602  7 4  ‐8.6000  23  12.9899  20 5  4.2000  6  ‐13.3375  3 6  0.2000  13  ‐5.1153  10 7  ‐6.6000  19  17.5393  23 8  7.2000  3  ‐17.5729  1 9  2.4000  7  ‐11.5548  4 10  11.2000  1  ‐16.3682  2 11  ‐3.0000  16  12.7088  19 12  ‐7.2000  21  14.2723  21 13  ‐1.4000  15  9.1666  16 14  1.2000  10  ‐3.8566  12 54 15  ISSN: 1985-31557.6000V  ol. 10 5 No. 1 Jan‐5u.a8r2y5-4 June 20168 16  0.6000  11  4.0543  15 17  0.2000  12  0.6266  13 

9  2.4000  7  ‐11.5548  4  10  11.2000  1  ‐16.3682  2  11  ‐3.0000  16  12.7088  19 Failure Mode and Effects Analysis of Ship Systems Using an Integrated Dempster Shafer Theory and Electre Method 12  ‐7.2000  21  14.2723  21  13  ‐1.4000  15  9.1666  16  14  1.2000  10  ‐3.8566  12  15  5.6000  5  ‐5.8254  8  16  0.6000  11  4.0543  15  17  0.2000  12  0.6266  13  18  8.4000  2  ‐5.3497  9  19  ‐5.2000  18  10.3197  17  20  6.4000  4  ‐9.0052  6  21  ‐6.8000  20  12.4422  18  22  ‐8.4000  22  14.3962  22  23  ‐4.0000  17  ‐4.1927  11  For  Fthoer  tnheet nseutpseurpioerr ioinrdienxd efxaiflauirleu rme modoed  e4 4rarnankkeded  inin  tthhee  llaasstt ppoossiittiioonn,, indicinatdinicga ttihneg ltehaest lceraistticcarli tfiacialul rfea imluoredem oofd teheo fmtahreinme adriienseeld einesgeinl ee nwghinilee failuwreh  mileofdaei lu7 reramnkoedde  i7n rtahnek eladsti nptohseitiloasnt  bpyo stihtieo ninbfeyrtiohre  iinndfeerxio. rTihned  enxe.t supeTrihoer ninetdesxu piesr icoorminmdoenxlyis  ucsoemdm  aosn  ltyheu  soepdtimasumth eroanpktiimngu mtecrhannikqiunge. Howteevchern isqoume.e rHesoewarecvheerrs shoamvee coremsbeainrcehde trhse thwavoe pecrofomrmbiannecde itnhdeicetsw too obtapine rfoovrmeraanllc  erianndkiicnegs toofo bataltienrnovateirvaelsl.r  aTnkhien  gnoeft alstuerpneartiiovre s.inTdheexn  eits recomsumpeernidoredin  fdoerx  riisskr epcorimormitiesnadtieodn foofr  srhisikp psryisotreimtis abteiocanuosfe siht ipgesnyesrtaetmes the  sbaemcaeu  rseesuitltgse  anse rtahtee s  PtRheOMsamETeHrEesEu  tlteschans itqhuee PaRpOplMieEdT  bHyE  ME athecehswniaqruaen and aLpopglainedathbayn M[9]a.h Tehswis aisr ainlluasntrdateLdo gina nsaecthtiaonn 3[9.1]..2T. his is illustrated in s ection 3.1.2. From Table 5, the two ranking indices produce quite dissimilar rankings for all the 23 failure modes. The net superior index ranked failure mode 10 in the first position and as such was the most critical failure mode of the marine diesel engine. The net inferior index ranked the same failure mode in the second position. For the net superior index failure mode 4 ranked in the last position, indicating the least critical failure mode of the marine diesel engine while failure mode 7 ranked in the last position by the inferior index. The net superior index is commonly used as the optimum ranking technique. However some researchers have combined the two performance indices to obtain overall ranking of alternatives. The net superior index is recommended for risk prioritisation of ship system because it generates the same results as the PROMETHEE technique applied by Maheswaran and Loganathan [9]. This is illustrated in section 3.1.2. ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 55

Journal of Advanced Manufacturing Technology3.1 Comparison of ELECTRE method with other methods3.1.1 Comparison of the ELECTRE method with the conventional FMEAAs stated in the introduction section, one of the challenges of theconventional FMEA, is its inability to utilise imprecise informationfrom experts. To overcome this challenge and for unbiased comparisonwith the proposed technique, the aggregated data shown in Table 4 wasalso used as an input into the conventional FMEA. The ranking of riskof failure modes produced by the two methods are shown in Figure 1.From Figure 1, it is obvious that the rankings produced by theconventional FMEA differ considerably from that of the ELECTREmethod as the majority of the failure modes are ranked differently.The variation is as a result of the limitations of the conventional FMEAwhich are as follows:• The inability of the FMEA to consider decision criteria weights in the decision making process whereas in the ELECTRE methodology, the decision criteria weights are put into consideration.J•ou rnalT ohf Aedvmancuedl tMipanluicfaacttuiorinng ToecfhnOolo,gyS  and D in evaluating RPN of the  conventional FMEA is not rational.   FFigiguurere1 1: :C Coommppaarrisisoonnw witithhc coonnvveennttiioonnaall FFMMEEAA  TThheessee  aarree  ssoomme eoof fththe ereraesaosnosn  swhwyh  yaltaerltneartnivaet ivaepparpoapcrhoeasc  hsuecshs  uasc h asMMCCDDMM babsaesde dmemtheotdhooldogoylo igs yreicsomremcoemndmede nind ethde ilnitetrhateurleit e[7r,a 9tu]. rTeh[e7  , 9].p ltTihmrhoeeipsteaoptslireoiomdnp simo toasefte ttidhhooenmd scooeolnotfhvgteoyhnd etdoicoilsonocnauglvsy FseeMdnditE siioAcnun.  tas hslieFsd MpiaEnpAetrh. iosvperacpomereso vaellr coof mtheessea ll of 536.1.2  CompariIsSoSNn :o1f9 t8h5e-3 E15L7ECTRVEol .m10ethoNdo .w1ithJa nPuRaOryM- JEuTnHe 2E0E1 6method   In  order  to  validate  the  novel  technique,  it  was  compared  with  the PROMETHEE  method  applied  by  Maheswaran  and  Loganathan  [9]. 

Failure Mode and Effects Analysis of Ship Systems Using an Integrated Dempster Shafer Theory and Electre Method 3.1.2 Comparison of the ELECTRE method with PROMETHEE method In order to validate the novel technique, it was compared with the PROMETHEE method applied by Maheswaran and Loganathan [9]. Maheswaran and Loganathan [9]do not consider imprecise information from experts but use crisp values in the decision making process. However, in order to allow the use of both precise and imprecise information from experts, the data in Table 5 evaluated with the Dempster Shafer theory’s combination technique was used as an input in the PROMETHEE methodology. The results of a comparative Jouarnnaalloyf sAidsvaoncfedbMotahnuftahceturEinLg TEeCchTnoRloEgEy and the PROMETHEE technique are   presented in Figure 2.     FFiigguurree 22:: CCoommppaarriissoonn wwiitthhP PRROOMMEETTHHEEEEm metehthodod    FrFormomF  iFgiguurere 22, , ththee EELLEECCTRE  mmeetthhoodd  ((nneet t ssuuppereiroiro r(C(Ca)a) ))anadn dthteh  e PRPOROMMEETTHHEEEE pprroodduucceess tthhee  ssaammee  rraannkkiinnggss  fofor rththe e232 3fafialuilruer emmodoedse. s. HHowoweveverert htheeE  ELLEECCTTRREE mmeetthhoodd  ((nneett  iinnffeerriioorr  ((DDaa))) )pprorodducuecse sdidffieffreernetn  t rarnaknikninggf oforr mmoosstt ooff tthhee ffaaiilluurree  mmooddeess..  OOnn  tthhisis  bbaasissi,s ,thteh eELEELCETCRTER E mfawannMrfmiieaedltutuhiseahlmutruLhoheltrebotdohessmegd w ara(  mtonanow(drnfoeoaa ieetdtftdnshhtee s  taosacsuh nfniuptseosdhpi[ehof ae9 PrLnitr]ips Roi ,ohocgrOsirroitaypi ftM(ni s( eCsCatrsEetatiayeahhmT))sa )ea)tuHs s neyit.im sEisA[Pl 9itEsRsrrol].etee, O hdcctaiAetooMo p iclmiumntpshEhg  mlnemTpoyhaiHrue,qesiingoCyEnrudhrr Edaetiee,to,  esdi psadCpa tiprnepeafoofpcc,gp odhrt ll iprirynuvepir iscedpiqorkreidurr oosieobeuroftsf yichr pttefiiheeaastsMiiecpi ssnltauptiiagnnhvmrlh uieeegeree   mdiomsssrr fwkbaie ost mesabdhkourryeeefal     ootnsff deacsi soiopnpocsreitde rtioa uPtRilOisMedEiTnHpErEio  rwithisoisneg  ervisakluoaftifoanil uprreomceossd  ecoams opplepxoitsye d toinPcrReOasMesE aTsH thEeE nuwmhboesre oef vdaelcuisaitoino ncripterroicae isnscrceoamseps.l eFxuirttyheirnmcroeraes, ethsea  s thEeLnEuCmTRbEer  mofetdheocdi sdioonesc  rniotet rrieaqiunicrree  athsee sm. Fauinrttehnearnmceo rper,atchtietiEonLeErCs TtoR E mdeethteordmidnoe esthne opt rreefqerueinrceet hfuenmctaioin tefonra necaechp roafc ttihtieo ndeercsistiond  ectreitremriain  e which  is  one  of  the  drawbacks  of  the  PROMETHEE  technique.    The  PROMETHEE  technique  as  applied  by  Maheswaran  and  Loganathan  [9]  for  risIkS SNof:  19f8a5il-u31r5e7  moVdeo l. p10riorNitois. a1tioJann uoarnyly-  Jucnoen2s0i1d6ers  precise  57 information  from  experts  and  in  most  real  life  situation,  information  may  be  precise  and  imprecise.  The  integration  of  the  Dempster  Shafer  combination  technique  with  the  ELECTRE  method  and  PROMETHEE 

Journal of Advanced Manufacturing Technologythe preference function for each of the decision criteria which is oneof the drawbacks of the PROMETHEE technique. The PROMETHEEtechnique as applied by Maheswaran and Loganathan [9] for risk offailure mode prioritisation only considers precise information fromexperts and in most real life situation, information may be preciseand imprecise. The integration of the Dempster Shafer combinationtechnique with the ELECTRE method and PROMETHEE method makeit possible for both techniques to utilise both precise and imprecise datafrom experts.4.0 CONCLUSIONThe purpose of this paper was to develop a systematic approach forrisk prioritisation which avoids the limitations of the traditional FMEAand its variant in order for risk to be prioritised more effectively. Toachieve this objective a novel FMEA tool which combines the DempsterShafer Theory with the ELECTRE method is presented. The DempsterShafer Theory is used to aggregate imprecise failures modes ratingfrom experts while the ELECTRE method is used in the ranking offailure modes. In demonstrating the applicability and validity of theproposed method, a case study of marine diesel engine is applied. Theresults of the case study analysis reveal the following:• The proposed method distinguishes failure mode from each other than the traditional FMEA approach whilst avoiding the limitations of the traditional FMEA such as inability to utilise imprecise information from experts.• The proposed method produces almost completely the same results as that of the PROMETHEE technique used by Maheswaran and Loganathan [9] thereby validating the proposed approach.• The proposed technique is easy to apply irrespective of number of decision criteria used in prioritising risk of failure mode unlike the PROMETHEE technique whose analysis difficulty increases as the number of decision criteria increases.• The proposed technique does not require maintenance practitioners to define preference function for each decision criteria which is an additional burden created by PROMETHEE approach.In conclusion, it is evident from this research that the proposed methodis capable of solving risk prioritisation problem more effectivelythan the traditional FMEA approach and its variants. Further workcan be performed by incorporating other decision criteria such asenvironmental impact and expected revenue into the risk prioritisationprocess.58 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Failure Mode and Effects Analysis of Ship Systems Using an Integrated Dempster Shafer Theory and Electre Method REFERENCES [1] A. Pillay, and J. Wang, “Modified failure mode and effects analysis using approximate reasoning,” Reliability Engineering and System Safety, vol. 79, no. 1, pp. 69‐85, 2003. [2] I. Emovon, R. A. Norman, and A. J. Murphy, ʺA new Tool for Prioritising the Risk of Failure Modes for Marine Machinery Systems.ʺIn: Proceeding of the 33rd International conference on ocean, offshore and Artic engineering OMAE14. American Society of Mechanical Engineers, California, United States, 2014. [3] Y. Du, H. Mo, X. Deng, R. Sadiq, and Y. Deng, “A new method in failure mode and effects analysis based on evidential reasoning,” International Journal of System Assurance Engineering and Management, vol. 5, no. 1, pp. 1‐10, 2014. [4] J. Yang, H.‐Z. Huang, L.‐P. He, S.‐P. Zhu, and D. Wen, “Risk evaluation in failure mode and effects analysis of aircraft turbine rotor blades using Dempster–Shafer evidence theory under uncertainty,” Engineering Failure Analysis, vol. 18, no. 8, pp. 2084‐ 2092, 2011. [5] K. Cicek, and M. Celik, “Application of failure modes and effects analysis to main engine crankcase explosion failure on‐board ship,” Safety Science, vol. 51, no. 1, pp. 6‐10, 2013. [6] X. Su, Y. Deng, S. Mahadevan, and Q. Bao, “An improved method for risk evaluation in failure modes and effects analysis of aircraft engine rotor blades,” Engineering Failure Analysis, vol. 26, no. 0, pp. 164‐174, 2012. [7] M. Braglia, “MAFMA: Multi‐attribute failure mode analysis,” International Journal of Quality and Reliability Management, vol. 17, no. 9, pp. 1017‐1034., 2000. [8] F. Zammori, and R. Gabbrielli, “ANP/RPN: A multi criteria evaluation of the risk priority number,” Quality and Reliability Engineering International, vol. 28, no. 1, pp. 85‐104, 2012. [9] K. Maheswaran, and T. Loganathan, “A Novel Approach for Prioritisation of Failure modes in FMEA using MCDM,” International Journal of Engineering Research and Application, vol. 3, no. 4, pp. 733‐739, 2013. [10] A. P. Dempster, “Upper and lower probabilities induced by a multivalued mapping,” The annals of mathematical statistics, pp. 325‐339, 1967. [11] G. Shafer, ʺMathematical theory of evidence.,ʺ Princeton University, 1976. [12] U. K. Rakowsky, and U. Gocht, “Reasoning in reliability‐centred maintenance based on a Dempster—Shafer approach,” Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, vol. 222, no. 4, pp. 605‐612, 2008. [13] D. D. Wu, “Supplier selection in a fuzzy group setting: A method usingISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 59

Journal of Advanced Manufacturing Technology grey related analysis and Dempster–Shafer theory,” Expert Systems with Applications, vol. 36, no. 5, pp. 8892‐8899, 2009. [14] B. Roy, and P. Vincke, “Multicriteria analysis: survey and new directions,” European Journal of Operational Research, vol. 8, no. 3, pp. 207‐218, 1981. [15] A. Shanian, A. S. Milani, C. Carson, and R. C. Abeyaratne, “A new application of ELECTRE III and revised Simos’ procedure for group material selection under weighting uncertainty,” Knowledge‐Based Systems, vol. 21, no. 7, pp. 709‐720, 2008. [16] M. Sevkli, “An application of the fuzzy ELECTRE method for supplier selection,” International Journal of Production Research, vol. 48, no. 12, pp. 3393‐3405, 2010. [17] L. Anojkumar, M. Ilangkumaran, and V. Sasirekha, “Comparative analysis of MCDM methods for pipe material selection in sugar industry,” Expert Systems with Applications, vol. 41, no. 6, pp. 2964‐ 2980, 2014. [18] C. Dong, C. Yuan, Z. Liu, and X. Yan, “Marine Propulsion System Reliability Research Based on Fault Tree Analysis,” Advanced Shipping and Ocean Engineering, vol. 2, no. 1, pp. 27‐33, 2013. [19] I. Emovon, R. A. Norman, and A. J. Murphy, “Hybrid MCDM based methodology for selecting the optimum maintenance strategy for ship machinery systems,” Journal of Intelligent Manufacturing, pp. 1‐13, 2015. [20] K. Cicek, H. H. Turan, Y. I. Topcu, and M. N. Searslan, ʺRisk‐based preventive maintenance planning using Failure Mode and Effect Analysis (FMEA) for marine engine systems.ʺ [21] America Bureau of Shipping, ʺGuidance note on Reliability‐Centered Maintence,ʺ America Bureau of Shipping, 2004. [22] A. Bejger, “An analysis of chosen engine failures of the ʺSeismic Researchʺ type ship,” Journal of Polish CIMAC, vol. 6, no. 2, pp. 9‐14, 2011. [23] C. Dunford, “Crankshaft purpose, design and modes of failure,” CSL Technical focus, no. 2, pp. 1‐5, 2011. [24] A. J. Mokashi, J. Wang, and A. K. Vermar, “A study of reliabilitycentred maintenance in maritime operations,” Marine Policy, vol. 26, no. 5, pp. 325‐335, 2002.60 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Wastewater Treatment by Electro‐Oxidation Process With TiO2 WASTEWATER TREATMENT BY ELECTRO‐OXIDATION PROCESS WITH TiO2 Q.J., Rasheed1, F., Ghanim2 and T.A., Abdullah3 1Production Engineering & Metallurgy Department, 2, 3Applied Science Department, University of Technology, Baghdad, Iraq. Email: *[email protected]: The environment of wastewater containing toxic organiccompounds by the industrial community has the environment of wastewatercontaining toxic organic compounds by the industrial community has increasedsignificantly in the recent past. So, the treatment of such wastes generatedfrom the industries is considered necessary. Untreated wastewater, if allowedto accumulate will result in the decomposition of organic material that leadsto the production of toxic gases. For wastewater, the objective is to remove orreduce the concentration of organic and inorganic compounds. Some of theconstituents and compounds present in wastewater lead to serious problem tothe environment. This study presents the treatment of petroleum wastewaterusing nano scale TiO2 in the presence of electro‐oxidation process. TiO2 physio‐chemical characterization of sol‐gel method analyzed using Ultraviolet light(which is an electromagnetic radiation), Scanning Electron Microgram (SEM),Fourier Transform Infrared Spectroscopy (FTIR) and X‐ray Diffraction (XRD).The influence of TiO2 dosage and initial pH on % COD reduction was studied.The results indicated that using TiO2 in combination with electrocoagulationat a dosage of 0.15 g/l and a pH 10 in Current Density (CD) respectively is anefficient method for the treatment of petroleum wastewaterKEYWORDS: TiO2, nano, electrocoagulation, petroleum refinery effluent; CODreduction1.0 INTRODUCTIONPetroleum effluent contains free hydrocarbons, suspended solids,phenol, benzene, sulphides, ammonia, heavy metals, cyanide,mercaptans, solvents, inorganic elements having high concentrationof salts, and organic carbon [1]. The current regulation of dischargelimits for petroleum effluents prior to discharge into water bodies isin accordance with the Presidency of Meteorology and Environment(PME). The most toxic compounds present in petroleum effluent,according to the cooperative survey by the Environmental ProtectionAgency (EPA) and the American Petroleum Institute (API), are:methylene chloride, benzene, carbon tetrachloride, trichloroethane,ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 61

Journal of Advanced Manufacturing Technologyphenol, toluene, chloroform, trichloroethylene, ethyl benzene, pyrene,di‐n‐butyl phthalate, and bis (2‐ ethylhexyl) phthalate. These compoundscause major environmental impacts such as oxygen depletion and toxiceffects on aquatic life tainting the water, and making it unsuitable forhuman use. Also, many studies have shown that oily effluents oftenhave an impact on the fauna, fish, crustaceans, plankton, and algae,especially in the areas around the outfalls.Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand(COD) values are in the range of 150‐200 ppm and 300‐600 ppm [1].Typical cyanide, oil, phenols, benzene, sulfide, ammonia and heavymetals can be found in refinery effluents. Dependent of the source(surface water, ground water, re‐used water) the make‐up water willneed a specific treatment such as sand filtration, iron removal, and(partial) softening. In addition, chemicals are dosed to control corrosionand biofouling. For boiler feed water the water is desalinated (reverseosmosis, ion exchange).Nanoparticles are materials having a size in the range of 1–100 nm.Iron oxide, titanium dioxide, fullerenes and carbon nanotubes havebeen made into nanoparticles [2]. Titanium dioxide is an effectivereducing agent and catalyst for various applications in environmentalremediation [3]. The heterogeneous reaction using TiO2 involves fivesteps: (i) mass transfer of the reactant to the TiO2 surface from the bulksolution; (ii) adsorption of the reactant on the TiO2 surface; (iii) chemicalreaction at the TiO2 surface; (iv) desorption of the reaction productfrom the TiO2 surface; and (v) mass transfer of the product into the bulksolution [4]. Treatment of wastewater using nano‐scale iron particlesrepresents a new generation of environmental remediation and thisprovides cost‐effective solutions to some important environmentalproblems [5]. The scope of the present study is the treatment ofpetroleum refinery wastewater sonochemically in the presence ofTiO2. TiO2 particles were synthesized from ferrous sulfate, and werecharacterized using Ultraviolet light is electromagnetic radiation(UV), scanning electron microgram (SEM), Fourier transform infraredspectroscopy (FTIR) and X‐ray diffraction (XRD). According to theirfinding, the removal observed with venturi was higher than with theorifice plate in combination with Fenton chemistry.The degradation experiments on p‐chlorophenol using bothelectrocoagulation and hypervalent iron and concluded that theelectroassisted ferrate degradation method was more effective than thesimple ferrate method [6]. Afzal et al [7] studied the combined action ofsonochemical and UV irradiation for the treatment of carbaryl62 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Wastewater Treatment by Electro‐Oxidation Process With TiO2(Carcinogenic compound). The sample was treated in anelectrocoagulation reactor with three different current densities. Thehighest degradation of carbaryl was achieved at 130 KHz comparedto 35 KHz. The combination of ultrasound and UV irradiation wasconsiderably more effective than when UV or electrocoagulation wasoperated individually. Based on the sonochemical degradation ofCongo red, the results showed that the initial dye concentration andpH of the dye solution influenced the decolorization and low initialvalues resulted in high decolorization [8]. Basiri [9] reported on thereduction of nitrite by electrocoagulation dispersed nanoscale TiO2 andshowed that TiO2 could be an efficient reductant. Ther using of TiO2 isto reduce nitrobenzene in aqueous solutions [10].The scope of the present study is to treat petroleum refinery wastewatersonochemically in the presence of TiO2. TiO2 particles were synthesizedfrom ferrous sulfate, and were characterized using scanning electronmicrogram (SEM) and X‐ray diffraction (XRD) and Fourier TransformInfrared Spectroscopy (FTIER).2.0 METHOD2.1 ApparatusThe electro‐oxidation process was carried out in a batch electrochemicalreactor. Iron was used as anode and ruthenium oxide coating titaniumas cathode with surface area of 45cm2, working volume of 500 milliliterand sonication time of 10 min.Chemical oxygen demand measurements were performed using CODdigester (Open reflux method). All pH measurements were made usinga digital pH meter.2.2 Wastewater characteristicsThe petroleum effluent was collected from a professional automobileservice station in Baghdad, Iraq. Oily effluent is considered as one ofthe most serious polluting sources, as it contains toxic substances suchas phenols, petroleum hydrocarbons, oil and grease, high biologicaloxygen demand (BOD) and chemical oxygen demand (COD) loads. Thistype of effluent comes from different sources, such as water producedfrom crude oil production, petroleum refinery, petrochemical, metalprocessing and car washing. The professional automobile servicestations include all services like automobile maintenance, washing,and change of engine oil.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 63

Journal of Advanced Manufacturing Technology Petroleum wastewater from an automobile service station is caused by mixing of automotive oil, such as lubricant oil with emulsifiers and wash water. The initial characteristics of the petroleum effluent are as  Jousrhnoawl ofn AidnvaTnacebdl Me 1an. ufacturing Technology TTaabblele 11: :CChhaararaccteterirsitsitcics so of fththee PPeetrtoroleleuumm EEffflfulueennt tS. No. Parameters Values1 pH 72 Oil and grease 570mg/L3 Total solids (TS) 1750mg/L4 Total dissolved solids (TDS) 1610mg/L5 Total suspended solids (TSS) 110mg/L6 Chemical oxygen demand (COD) 3000mg/L7 Biological oxygen Demand 370mg/L    2  .3 Preparation of TiO2  T2.h3e maPtereripaalruasteiodnis oafs TpieOci2a l grade reagents Titanium (IV) isopropoxide T(Aheld  mriachterCiahl eumseicda lis  aL tsdp.e,ciUalS Agr)a, dGe larecaiaglenatcse tTicitaanciiudm.  A(IlVl ) cihseompriocpalosxide (wAeldrericrhea  gCehnetmgircaadlse  aLntd.,u  sUeSdAw),i tGholauctiaful rathceetricp  uarcifdic. aAtiolln  .chUelmtraicaplus rewere rdeeaigoennitz egdrawdea taenr dw uaseuds ewditinhoaullt tfhuertphreerp paurartiifoicnast.ion. Ultra pure deionized water was used in all the preparations.  The typical synthesis procedure for the preparation of TiO2 nanoparticlesbTyhes otyl‐pgieclalm syetnhtohdesiiss parsocfeodlluorwes f.oIrn tihtiea lplyr,ep1a8r.6atimonl  of TTiiOta2n niuamnop(IaVrt)icles ibsyo psrolp‐goexli dme wetahsodh ydisr oalys zefodllboyw3s.5 .8Inmitilaglllya,c i1a8l .a6c emticl  aocfi dTaita0niºuCmin  (IV) wisohpicrhop3o9x5idme l wofasw  haytedrrowlyaszeadd dbeyd  3d5r.8o pmwl  igsleactioalt haicsetsiocl uatciiodn  autn  0d eºrC  in vwighoicrho u3s9s5t irmriln  goff owr 1athera  nwdatsh  eadsdtierrdi ndgrwopa swcoisnet intou etdhifso rsaolfuutritohne ru5nder hv.igTohreoupsr esptiarreindgs foolru t1i ohn awnads tkhep sttirnritnhge wdarsk cofonrti2n4uhedf ofor rn au cflueratthioenr 5 h. pTrhoec epsrse. pAafrtedr  thsoelpuetiroinod  w, tahse  skoelputt ioinn  wthaes  dplaarcke dfoirn  a2n4  ohv efnora tn7u0cl°eCation fporro1c2eshs.f oArfgteerl atthioe npaenridodag, itnhge psorolucteisosn.  Twhaesg pelawceads tihne nand oriveedna tat1 0700 °°CC for a1n2 dh sfuobr sgeeqluaetinotnly atnhde apgriondgu pctrowcaes sc.r  Tuhshee gdeiln wtoasfi ntheepno dwrdieedr .at 100 °C and subsequently the product was crushed into fine powder. D  uring the sol‐gel synthesis of TiO2 nanoparticles, high water ratiowDausriknegp  thteo  seonlh‐gaenlc  esytnhtehnesuicsl eoof pThiiOli2c  naattnaockpaorftiwclaetse, rhoignht iwtaantieurm  ra(tIiVo )was ikseopptr otpoo  xeindheaanncde  ttohes upnpurcelesospthielicfa  satttcaocnkd  eonfs awtioantero fotnit antiituamniu(mIV )(IV) isopropoxide sapnedci etsot osyuipepldreTsisO  t2hnea nfoasctr ycsotanlds.ensation  of  titanium  (IV) isopropoxide species to yield TiO2 nanocrystals. 2 .4 Degradation experiments  D2.e4gradDaetigornadeaxtpioenri emxepnetrsimweenrtes  performed in an electro oxidation rDeeagctroard.aAtinoond eexpueseridmwenatss rwheenreiu pmerofoxridmeecdo iant eadn teitlaenctiruom oxaniddatciaotnh oredaector.  uAsneoddwe aussierdo nw, awsh  rihleenthiuemar eoaxiodfet hceoaatneodd  teitwanaisu4m5 camn2d.  Acabtohuotd2e0  0u0semd lwas iron,  while  the  area  of  the  anode  was  45cm2.  About  2000  ml  of  the 6wb4 aatsht etwo amteari nIsSatSamNin:p 1lc9e8o 5wn-3sa1tsa5 7nptl atecVemodlp . ie1n0r aat uNbroee.a 1dkeuJrar nitnuhgaar tyE  -wleJuacnstre oc2o 0ov16xeirdeadt iboyn .a  T  wo attheer  beaker  was  added  about  0.05  g  of  TiO2,  and  Electro‐oxidation  was performed  for  120  min.  1  ml  samples  were  withdrawn  at  5  min  intervals 

Wastewater Treatment by Electro‐Oxidation Process With TiO2 of the wastewater sample was placed in a beaker that was covered by a water bath to maintain constant temperature during Electro oxidation. To the beaker was added about 0.05 g of TiO2, and Electro‐oxidation was performed for 120 min. 1 ml samples were withdrawn at 5 min intervals and centrifuged for 10 min at 6000 rpm. The supernatant was subjected to COD determination. The pH optimization studies were pvearfroiormuse dinuitniadle  rpvHa rciounsdintiiotniasl, piHnccluodndinigti opnHs, i=n c4lu, d6i,n  7g, p8H  a=nd4,  61,07. ,A8 t  the  anopdt1im0.uAmt  tphHe ,o pntainmoupmartpicHle, ndaonsoagpea rwticalse  tdhoesna gvearwieads t0h.0e5n  gv/aLr,i e0d.10  g.0/5L  and  g0/L.1,50 .g1/Lg./ L and 0.15 g/L.   2.25.5 AAnnaallyyttiiccaall mmeetthhooddss   CChhememiciaclalo xoyxgyegnend edmeamnadn(dC  O(CDO)Dw)a  swdaest edremteinrmedinbeyd thbey Othpee nORpeefnlu  xReflux  mmetehthoodd. .     3.30.0     R  REESUSULTLSTS& &D IDSICSUCSUSSIOSINON   3.31.1      AAppppaarraattuuss   TThhee%  %CCOODDr ermemainainigngw  iwthithre srpeescptectot  tiom  teimofe eoxfp  oesxuproesutoreE  ftfoe cEt fofefct  of  OOxxididataitoionnt itmimeei siss hsohwownni ninF iFgi.g1.1T. hTeher erseuslutslts hsohwowc lecalerlayrlyth  atht atth  ethe  %  %dedgergardaadtaiotino nofo wf wasatestwewataetre irnicnrceraesaesse ws withit hana nincinrecaresaes ien itnimtiem aenadn adlmost  al6m0%os ot f6 0d%egorafddaetgiorand wataiso nacwhaiesvaecdh inev 1e2d0 imn i1n2.0   min.     FigFuigruer1e: 1E: fEfefcfetcotf oOf xOidxiadtiaotniotnim time oen o%n %C OCDODre rmemovoavl al  Generally,  prolonged  exposure  of  wastewater  to  electro‐oxidation  may enhance the  generation of oxidative  species  in  water.  This  is  initiated by the  hemolytic  cleavage  of  water  molecules  by  pyrolytic  reactions,  which may be represented as follows:                      H2O                             OH + H                       (1)                    2 OH   + 2H                H2O2 + H2          (2)   ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 65The OH and H2O2 are strong oxidizing agents, and the production rate of such  oxidants  depends  on  the  final  temperature  and  pressure  at  the  time of  bubble  collapse.  These  oxidizing  agents  are  responsible  for  the 

 Journal of AdFviagnucrede1M: Eanfufefacctt uorfi nOgxTidecahtnioolnog tyime on % COD rem oval   Figure1: Effect of Oxidation time on % COD removal  GeGnernaelrlayl,l yp,rporlolnognegde dexepxposousurer eoof f wastewater ttoo eelelectcrtoro‐o‐oxxididaatitoionnm  mayay eGnehennaehnracelnl ycteh,  etph rgeoelgnoennrgaeetridao tnieo xonpf oosfxuoirdxeai dtoiavft eiwv  seapsetpceeiwecsia etisenr i nwtoaw teartle. crT.trhToihs‐o iisxsi idisnaiitntiioiatnitae  tdme dbay ethnehb yahnetcmhee otlhyetm icg oecnllyetariacvtacigolena  ovofaf  gwoexaiotdefarw timvaetoe lsrepcmuecloeileses cb uiynl e pwsyabrtyoelryp. tyTicrho  rilsey atiicsct ironeniatsica,t tiweodnh sibc, hy tmhaewy  hh beiecmh roemlpyarteiycs becneletreaedvp aargeses fe oonlflt oewwdasat:se  rf omllowlesc:ules  by  pyrolytic  reactions,  which ma y be represented as follows:                      HH22OO                               OOHH ++ HH                          (1)  (1)                    2H 2O 2OHH   +   2 + H  2  H                               OH HH22OO +22 + H+H  H  2 2                       ( (12))   (2)                   2 OH   + 2H                H2O2 + H2          (2) T  hTe hOeHO Hanadn Hd 2HO22O a2rea rsetrsotrnogn ogxoidxidzinzign gagaegnetns,t sa,nadn dthteh epprordoduuctcitoinon raratete of sTuhcoehf O souHxci hdaanondxt isHd ad2nOetp2s eadnredp sse tonrnod nstgho eon xftiihndeaizlf itnegam laptgeeemrnaptuse,r ae ntaudnr edth apen rdpersposurderusecs tuaitro enth areta tthieme oef osuf ctihbm uoebxboidlfeab nuctbsob ldllaeppcseoenl.l dapsT shoeen.s Teth  eo sxfeiindoaixzli idtneigmz inpagegreaangtutesnr et saaranerd e rpreersseppsosonunsrsieibb laleet  tffhooerr  thitmehe dofe dgbreaugdrbabdtlieao tnico oonfl loafrpgosareng. aicnT sihcuebssusetb asontxaceindsc iepzsirnepgsre ensateg nientn ittnhs et haweraews  taresewtsepawtoeanrts eirb.le  for  the d  egradation of organic substances present in the wastewater   3.2 Characterization of TiO2  Fig.2 shows the absorption spectra of TiO2 nanocomposites taken at room temperature. The sample possess an absorption edge around370‐430 nm. Figure 2: UV–vis spectrum for TiO2 nanoparticles.The scanning electron microscopy (SEM with EDX) image ofsynthesized TiO2 particles were shown in Fig 3. The results indicatethat the synthesized TiO2 particles are almost spherical. Fig. 3(a) showsevenly distributed spherical particles approximately 1μm in size, andFig. 3(b), under higher magnification, confirms the spherical shape andthe size range of each particle. Fig.3 (b). These structures increased theavailable surface area of reaction. Fig.3 (c) shows the wt% for TiO2 as70.9 for Ti and 29.1 for O. Fig.4 shows the X‐ray diffraction pattern ofthe TiO2 sample annealed at 300°C in air for 1 h. The spectrum showstwo major diffraction intensity peaks at 2θ = 36.08° and 41.01°. Thepeaks were identified to originate from the (1 1 0), (1 1 1), (2 1 1), (2 2 0),66 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

range  of  each  particle.  Fig.3  (b).  These  structures  increased  the  available surface area of reaction. Fig.3 (c) shows the wt% for TiO2 as 70.9 for Ti and 29.1  for  O.  Fig.4  shows  the  X‐ray  diffraction  pattern  of  the  TiO2  sample annealed  at  300°C  in  air  for  1  h.  The  speWcatsrtuewmate r sThreoatwmesn t btywEole ctrmo‐Oaxjoidra tion Process With TiO2diffraction  intensity  peaks  at  2θ  =  36.08°  and  41.01°.  The  peaks  were dentified to originate from the (1 1 0), (1 1 1), (2 1 1), (2 2 0), (0 2 2), (3 1 0) and  (3  0  1)  planes  o(0f 2F2e)O, ( 3re1sp0)ecatnivde(l3y 0(J1C) PpDlaSn ensoo:f  7F7e2O35r5e)s.p  Techteiv  Xel y– (rJaCyP DS no: 772355).could  be  indexed  toT htheeX  Fm– rˉ3amy  c(o2u2l5d)  bfaecein  gdreoxuepd  (tFoatchee  –F  cmenˉ3tmere(d2)2 5c)ufbaice  group (Face –structure, with cell pcaernatmeretde)r cau =b i4c.3s0tr9u Åct.u  re, with cell parameter a = 4.309 Å.The information onT the ipnafortrimclaet isoizneo wn aths eopbatartiinceleds  firzoemw aths eo bftualiln wedidftrho matt he full width athalf  maximum  (FWhHaMlf m)  oafx itmheu mdi(fFfrWacHteMd )boefatmhe  udsiifnfrga cstcehdebrreearm  foursminuglas:c herrer formula:The crystalline size wThaes craylcsutalalltiende usisziengw Dasebcaylec‐uSlcahtedrreurs ifnogrmDuelbay. e  ‐Scherrer formula.                                                                           `                                 ( 3)  (3)AAa :::  mmmaaagggnnniiifffiiicccaaatttiiiooonnn  aaattt  222000  lllmmm///222000000   BBb::  MMaaggnniiffiiccaattiioonn  aatt  1100  llmm//11000000      CCc:::  EEEDDDXXX  ooofff  TTTiiiOOO222      Figure 3:  SEM –EDX images of TiO2  Figure 3:  SEM –EDX images of TiO2 . .    ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 67

  Journal of Advanced ManuFfiagcuturrei n3g: T SeEchMno l–oEgyDX images of TiO2 .     Figure 4:  X‐ray diffraction analysis of TiO2 samples     JT ohuTrenh asela osmfa Ampdlvpea lnhecaehds a Masnaan naufvaaecvtruearrginaegg Tcereccyhrsnytoaslotllagiylnlien seizseiz 2e2262 o6fo 3fl.3ll n.lmnm +0+.50.. 5.   Figure 5:  FTIR spectrum of TiO2.    FFiigg..55 sshhoowwss ththee abasbosroprtpiotino npepaeka akt 3a4t5374cm57‐c1m a‐s1 reapsrerseepnrteasteinotna toifo ntheo fO‐H  tshtreetOch‐iHng stvriebtrcahtiinogn  voifb  frraeteio  nwaotferf raened witast ecrorarnedspoitnsdcinogrr eOsp‐Hon  dbeinngding  Ovi‐bHrabtieonnd oinccguvrriebdra atito 1n63o6c ccumr‐r1e dduaet t1o6 t3h6ec cmhe‐1mdicuaellyto adthseorcbheedm wicaatlelry.  a  dsorbed water. 3.3     Effect of current density  3  .3 Effect of current density TiO2  assisted  Electro  oxidation  degradation  was  carried  out  and  the  %TiCOO2 Das sreismteodvaEll ewctirtho roexsipdeacttio tno dtiemger aids asthioonwnw ains Fcaigr.r6ie. dDuoruitnga ntdhet hfierst 5  m%iCnO  oDf  trheme  orevaacltwiointh,  trhees preecdtutoctitoimn ewisass hmowucnhi nhiFgihge.6r.. DTuhrisin  igs tdhueefi rtsot  the  i5nimtiainl  orfeatchteiorne acotfi onT,iOth2 ewreitdhu ctthioen  owragsanmicu  cphohlliugthaenrt.s Tthhisati sadreu ehtioghly  stuhescienpittiiballer etoa cotixoindiozaf tTioiOn.2 Lwaittehr,t dhue eo rtog atnhiec epffoelclut toafn otsxitdhiaztatairoenh, tighhe lCyOD  csounsctienputeibdl etot odeocxriedaiszea ttioo na. cLoantseird, edruabeleto letvheel,e bffuetc tbeocfaomxeid ciozantsitoann,t tahfeter a  cCeOrtDainco  ntitmineu. edThtoisd  emcraeya seeittohearc  obnes idatetrraibbuleteledv etlo,  btuhteb epcaremseenccoen sotaf nnt on‐ daeftgerraadacbelret aoinrgatinmices. iTnh tihs em eafyflueeitnhte orrb teo athtteri bexuhteadusttoiotnh eofp TreiOse2n pcaerotifcles.  Tnhoen ddeegsrtarudcatbiolen omrgaayn  ibces  iimn pthroeveefdfl ubeyn  itnocrretaositnhge  tehxeh  aamusotiuonnt ooff TTiiOO22.  In  tphaisrt  ikcilneds.  of  reaction,  there  are  two  ways  in  which  the  organic  pollutants  are degraded, namely, through pyrolysis and reduction on TiO2 surface.    68 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

min  of  the  reaction,  the  reduction  was  much  higher.  This  is  due  to  the initial  reaction  of  TiO2  with  the  organic  pollutants  that  are  highly susceptible to oxidization. Later, due to the effect of oxidization, the COD continued to decrease to  ae ictohWneasrsi tdebweaert aerbaTltretera iltmbevuenettelb,dy b Eulteoctt  rbot‐eOhcxeai dmaptieor necsPoernoncsecstesa Wnotit hfa TfntiOeo2rn a‐ certain  time.  This  may degradable  organics  in  the  effluent  or  to  the  exhaustion  of  TiO2  particles. ThTeh ededsetsrturcutciotino nmmaayy  bbee  iimmpprroovveedd  by iinnccrreeaassiinngg ththeea  mamoouunnt to foTf iTOi2O. I2n.  In thtihs iks iknidn doof frreeaacctitoionn, ,tthheerree are two wwaayyssi ninw whhicihchth tehoe rogragnainc ipco plloultlauntatsnts araer deedgergardaedde,d n, anmameleyl,y t,hthroruoughgh ppyyrorolylysissi saanndd rreedduucctitoionn oonn TTiiOO22 surface.     Figure 6:  Effect of current density on COD                                                        with treatment time of 120 mins at pH=7.      33..44      EffEefcfet cotfo pfHp H     TThhe eeeffefecct tooff  pH  on tthhee %%CCOODDr ermemovoavlala fateftre1r 2102m0 imn ionf  pofr opcreossciensgsinisg  is  shshowownn ini nFiFgi.g7.7 F. rFormom thteh reerseuslutsl tssusguggegsteesdte bdyb tyhet hfeigfuigreu,r iet, ciot uclodu blde bneoted  thnaott eadt  pthHa t4a, tppHH  6,4  ,ppHH  7,6  ,ppHH  8 7a,npdH  p8Ha  1n0d  tphHe  %10COthDe  %reCmOoDvarl evmalouvea lwas  mvuacluhe  lwowaserm  aunchd lohwenecrea  nthdeh  efnfceecttihve erfefedcuticvtieorne dtuooctki opnltaocoek  apt latcheisa  tpH.  HtohwisepvHer., Hwohweenv etrh, ew  hpeHn  twheasp  Hadwjuassteadd jutos te6d,  tao  p6,oaorpeor oereffrecetf feocnt  oCnOD  reCdOuDctiroend uwcatiso nnowteads .n  Totheids . mThaiys  mbea ydbue dtou ethtoe threedruecdeudc eadctaivctiitvyi toyf oTf iO2  uTnidOe2r upnHd ecor npdHitcioonnsd. itions.     Figure 7:  Effect of pH on % COD removal at treatment time of 120 min    3.5     Effect of TiO2 Dosage    The  changes  due  to  %  COD  under  various  TiO2  dosage  conditions  are  shown  in  Fig.8.  The  results  show  that  an  increase  in  TiO2  dosage  increased  the  reduction  in  COD,  as  the  %COD  removal  decreased.  This  can  be  attribIuSStNed: 1  t9o85  a-3n1 5i7ncreVasoel. 1i0n  thNeo .s1urJfaancuea rayr-eJau noef 2T01i6O2  accessible6 9for  the organic pollutants.     

  Figure 7:  Effect of pH on % COD removal at treatment time of 120 min J ournal of Advanced Manufacturing Technology3.5     Effect of TiO2 Dosage T 3h.5e  chaEnfgfeesc tdoufeT itOo 2%D  CosOaDge  under  various  TiO2  dosage  conditions  are sThhoewcnh  aing  eFsigd.8u. e Tthoe%  reCsuOlDts  usnhdower  vtharaito  uasn TiinOc2redaossea  gine  cToinOd2i tidonosage ianrceresahsoewd nthien  rFeidg.u8c.tTiohne  irne sCuOltsDs, haosw  thteh a%t CanODin crreemasoevianl  TdieOcr2edasoesdag. eThis ciannc rbeae saetdtrtihbeurted utcot iaonn  incCreOaDse, ains tthhee %suCrOfaDcer eamreoav  oafl dTeiOcr2e  acseceds.sTibhlies  for tchaen obreganttirci bpuotleludttaonatsn. increase in the surface area of TiO2 accessible forthe organic pollutants.         Figure 8:  Effect of TiO2 on % COD removal at treatment time of 120 min       4.0 CONCLUSSION TiO2 nanoparticles prepared through a liquid‐phase reduction method are almost spherical and exhibit higher surface area available for reactions. The absorption spectrum of TiO2 at 400 nm is due to the charge‐transfer from the valence band (mainly formed by 2p orbitals of the oxide anions) to the conduction band (mainly formed by 3d t2g orbitals of the Ti4+ cations). The broad intense absorption edge of the spectrum is the result of formation of nanoparticles. The SEM find on the spherical particles where there were thread‐like or tube‐like structures clearly visible in these structures due to increased the available surface area of reaction. The sample annealed at 300°C/1h has an average crystalline size of 31.1 nm ±0.5. As the annealing time or temperature increases, the crystalline size increases. The band at 2432 cm‐1 is assigned to C‐H vibrations. The C‐H could be attributed to the organic residues, which remained in TiO2 even after calcinations. The broad intense band below 1200 cm‐1 is due to Ti‐OTi vibrations. Reduction test results indicated that oxidization can accelerate the reduction of organic pollutants present in wastewater when used with TiO2. The degradation of organic pollutants present in wastewater with TiO2 under Electro oxidation. Experiments carried out under various CD, pH levels revealed and dosage of TiO2. The electro oxidation experiments 70 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Wastewater Treatment by Electro‐Oxidation Process With TiO2for the treatment of petroleum wastewater using ruthenium oxidecoated titanium as the anode and iron as the cathode. were conductedin batch reactor. The optimized conditions was absorbed at currentdensity of 9 mA/cm2, pH of 10, catalyst additional of TiO2 0.15 g/L, andtreatment time of 120 min. Under these conditions, the COD removalefficiency of 92 %, were estimated. The electrochemical techniques areviable processes for the treatment of oily wastewater. The degradationstrongly depended on pH 10 while efficient degradation occurred inacid media. Tio2 serves as a substantial part that can be added to thereaction to reach desirable results.REFERENCES[1] Q. J. Rasheed, K. Pandian and K. Muthukumar, ʺTreatment of petroleum refinery wastewater by ultrasound‐dispersed nanoscale zero valent iron particles,ʺ Ultrasonics Sonochemistry, Vol 18 No. 5, pp.1138‐1142, 2011.[2] H. Shi, R. Magaye, V. Castranova and J. Zhao, ʺTitanium dioxide nanoparticles: a review of current toxicological data,ʺ Particle and Fibre Toxicology , Vol.10 No.15, pp.1‐33, 2013.[3] K. W. Pi, Q. Xiao, H. Q. Zhang, M. Xia and A. R. Gerson, ʺDecolorization of synthetic Methyl Orange wastewater by electrocoagulation with periodic reversal of electrodes and optimization by RSM,ʺ Process Safety and Environmental Protection, Vol. 92 No.6,pp.796–806, 2014.[4] L. Lei, N. Wang, X. M. Zhang, Q. Tai, D. P. Tsai, and H. L. W. Chan,ʺ Optofluidic planar reactors for photocatalytic water treatment using solar energy,ʺ Biomicrofluidics, Vol. 4 No.4,pp. 1932‐1058, 2010.[5] Q. J. Rasheed, ʺSynthesis and Optimization of Nisin‐Silver Nanoparticles at Different Conditions,ʺ Engineering & Technology Journal, Vol.33 No.2, pp.331‐341, Part (A), 2015.[6] M. V. Bagal and P. R. Gogate, ʺWastewater treatment using hybrid treatment schemes based on cavitation and Fenton chemistry: A review ,ʺ Ultrasonics Sonochemistry, Vol. 21 No.1, pp.1–14, 2014.[7] A. Afzal, P. Pourrezaei, N. Ding, A. Moustaf, G. Hwang, P. Drzewicz, E.S. Kim, L. A. Perez‐Estrad, P. Chelme‐Ayal, Y. Liu and M. G. El‐ Din,ʺ Physico‐Chemical Processes Water,ʺ Environment Research, Vol. 83 No. 10, pp.994‐1091.[8] K.P. Gopinath , K. Muthukumarand and M. Velan,ʺSonochemical degradation of Congo red: Optimization through response surface methodology,ʺ Chemical Engineering Journal ,Vol. 157 No.2‐3, pp. 427‐ 433, 2010.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 71

Journal of Advanced Manufacturing Technology [9] J. B. Parsa, ʺTreatment of wastewater containing Acid Blue 92 dye by advanced ozonebased oxidation methods,ʺ Separation and Purification Technology, Vol.98,pp. 315‐320, 2012. [10] E. A. Reynoso‐Soto, S. Pérez‐Sicairos, A. P. Reyes‐Cruzaley, C. L. Castro‐ Riquelme, R. M. Félix‐Navarro, F. Paraguay‐Delgado, G. Alonso‐Núñez and S. W. Lin‐Hoa, ʺPhotocatalytic Degradation of Nitrobenzene Using Nanocrystalline TiO2 Photocatalyst Doped with Zn Ions,ʺ Journal of the Mexican Chemical Society, Vol. 57 No.4,pp. 298‐ 305, 2013.72 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Application of Theory of Inventive Problem Solving for Systematic Innovation: Case Study of Water Dispenser Design APPLICATION OF THEORY OF INVENTIVE PROBLEM SOLVING FOR SYSTEMATIC INNOVATION: CASE STUDY OF WATER DISPENSER DESIGN M.R., Mansor1, H., Rusnandi2 and W.N., Mohd Isa3 1,2Faculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia. 3Faculty of Computing and Informatics, Multimedia University, 63100 Cyberjaya, Selangor, Malaysia. Email: *[email protected]; [email protected]; [email protected] ABSTRACT: This paper analyzed an application of the Theory of Inventive Problem Solving (TRIZ) method in providing systematic innovation process of consumer product. The TRIZ tools namely contradiction matrix and 40 inventive principles were employed in this project. The contradiction matrix was applied for problem identification purpose whereas the 40 inventive principles were employed to generate conceptual solutions for the problem. The application of both tools was demonstrated through a case study of water dispenser. Based on the case study, the utilization of the TRIZ tools resulted in the development of new water dispensing bottle design which was able to offer a simple and cost effective solution while retaining the current principle of operation especially during the water bottle changeover process. KEYWORDS: TRIZ, Contradiction Matrix, 40 Inventive Principles, Water Dispenser. 1.0 BACKGROUND TRIZ is a Russian acronym for “Theory of Inventive Problem Solving” [1]. It is a systematic innovation theory developed by Genrich S. Altshuller after analysing thousands of patents in the 40s. TRIZ has been successfully implemented by big companies, such as Samsung, General Electrics (GE), Intel, and many others to assist with product and technological innovation [2]. TRIZ is based on “contradictions that can be methodically resolved through the application of innovative solutions” [3]. TRIZ has three premises; an ideal design; contradictions that help to solve problems; innovative process which can be structured systematically [3].ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 73

Journal of Advanced Manufacturing TechnologyContradictions are technical compromises or trade‐offs that lie in anengineering system where some design parameters have become worsenin order for the problem to be solved. TRIZ has been demonstrated forceramics processing in 70 ways, whereby its aim is “to teach ceramicsprocessing to the next generation of scientists and engineers but closelyallied to classification is the question of creativity and inventivenessand how they are fostered”. The contradictions refer to simplifiedceramics processing classification, increased inventiveness, and goodpractice [4].A case study of a notebook design in research and development waspresented by Yeh, Huang and Yu [5] through an integration of qualityfunction deployment (QFD) and TRIZ. QFD has been implemented infour phases to identify major contradictions. At each phase of the QFD,major contradiction has been identified and TRIZ has been applied toresolve the contradiction. The final outcomes are three breakthroughsolutions generated from the TRIZ 40 Inventive Principles.Moreover, TRIZ has also been illustrated in the design of a passivelycompliant robotic joint [6]. Based on their report, TRIZ was demonstratedas a systematic methodology for enhancing creative capability in thedesign of an innovative robotic joint. Two contradictions have beenidentified from five literature studies. TRIZ Inventive Principles havebeen applied to resolve the contradictions and a prototype has beendeveloped and experimentally tested.TRIZ has also been adopted in a design of an implanted biomedicaldevice, a tracheal stent that fulfills the need of each patient andapprove by physicians at the same time [7]. The contradiction occursdue to required customization of the tracheal stent on patients but suchtracheal stents come in many materials, shapes, and characteristics. Aparametrization tool has been implemented that guides modificationof the general dimensions of stents to fit each specific patient. The QFDmethod has been applied prior to TRIZ to visualize and summarize thedesign attributes.Based on the discussion from the aforementioned literatures [3 – 7],resolving contradictions through TRIZ can lead to innovative solution.Thus, based on the TRIZ method, this paper aimed to identify thecontradictions that occurred in developing solutions for problemsinvolving consumer products. The application of the TRIZ tools wasshown through a case study to solve the contradiction that occuredin the bottle changeover process of a water dispenser. Implementationof TRIZ contradiction matrix tool was first conducted to resolve the74 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Application of Theory of Inventive Problem Solving for Systematic Innovation: Case Study of Water Dispenser Design contradiction. Finally, solution generation for the contradiction was performed using TRIZ 40 inventive principles to come up with an ideal water dispensing design. 2.0 RESEARCH METHODOLOGY Figure 1 shows a general framework of the problem solving process in this study [1]. The framework comprises four steps, which conceptually follows similar classical TRIZ problem solving method as shown in Figure 2. The first step in problem solving process is problem definition. In this step, the problem should be clearly defined and what benefits are expected if the problem is solved. The information about limitations of the existing condition and the requirements of the solution are also essential so that the problem formulations can be clearly stated. The second TRIZ problem solving process involves development of TRIZ model of the problem. In this paper, TRIZ technical contradiction was used to model the problem. The term contradiction is applied in TRIZ to represent the compromise in which designers need to decide upon when implementing a solution. For example, the design intents to improve the weight (reduce the weight) of a product by reducing the product thickness for better maneuverability may also cause deterioration on the product strength in handling the given load. Thus, the contradictions occurred in TRIZ is solved simultaneously to obtain the best solution without having to make a trade‐off or compromise in the design. The next step involves an application of 40 Inventive Principles to solve problem of the developed model of. In the last TRIZ process, the final result of the specific solution which generally covers the solution idea is generated from the selected potential solution obtained in previous step.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 75

  JoJouurnrnaal lofo fAAddvvanancecded MMananuufafcatcuturirninggTTecehcnhnoloolgoygy   Problem Definition Model the Problem       Apply TRIZ Solution Tools         Generate Conceptual Solution   Figure 1: TRIZ problem solving process flow        Model of the  Model of the    Problem  Solution          Specific  Specific    Problem  Solution    Figure 2: Classical TRIZ problem solving method     33..00        CCAASSEES TSUTDUYDOYN  WOANT EWR DAITSPEERN SDERI S P E N S E R     AAnn  aapppplliiccaattiioonn  ooff  TTRRIIZZ  mmeetthhoodd  iinn  ssoollvviinngg  pprroobblleemm aanndd ddeevveellooppiinngg  iinnnnoovvaattiivvee sosolulutitoionn ini nthitsh pisappearp iesr diesmdoenmstorantsetdra tthedrouthgrho au gchasea stcuadsey  osntu  dwyaotenr wdaitseprednissepre  nesqeuripeqmueinptm.  eAnt . wAawtear tedridspisepnesnesre  ruunniti t iiss  ddaaiillyy  ccoonnssuummeerr eeqquuiippmmeenntt tthhaatt pprroovviiddeess cclleeaann ddrriinnkkiinngg wwaatteerr ttoo tthhee uusseerr.. IInn  ggeenneerraall,, tthheerree aarree  ttwwoo ttyyppeess ooff wwaatteerr ddiissppeennssiinngg uunniitt;; oonnee wwhhiicchh uusseess  aa ddeeddicicaatetedd wwataetre rbobtotltetl eto tsoupsupplyp lwyawtear t(emr a(nmuaanl uraelfilrleinfigll imngethmoedth) oandd)   tahned otthheer oist hthere oisneth we hoinche iws hinictehgrisatiendt ewgritahte wdawteirt hpiwpea taesr thpeip seouarsceth oef  wsoauterrc esuopf pwlyat (earustuopmpalytic( arueftiolmlinagti mc reetfhilolidn)g. Tmheet hdoedsi)g. nT hoef tdhees idgendoicfattheed  wdaetdeirc atdeidspwenatseinr gd isppreondsuincgt  pisr odreulcattiivserleyl atcihveealypecrh ecaopmerpcaormedp atroe dtthoe  itnhteegirnatteegdr adteisdpednisspere‐npsiepri‐npgip dinesgigdne.s iHgnow. Hevoewr,e vite rre, qiturireeqsu uirseesrsu stoer ssetlof‐ cshealfncghianngg tinhge twheatwera tbeortbtloet taleftaerft eitr iist iesmemptpyt.y A. As ssshhoowwnn iinn FFiigguurree 33,, tthhee  mmaannuuaall wwaatteerr ddiissppeennsseerr eennccoommppaasssseess ffoouurr mmaaiinn ccoommppoonneennttss,, tthhee rreeffiillll  bboottttllee,,  ddiissppeennsseerr  iinnsseerrtt,,  ddiissppeennssiinngg  uunniittss  ((ffoorr  hhoott aanndd ccoolldd wwaatteerr)) aanndd  ddiissppeennsseerr mmaaiinn bbooddyy. .  76 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Application of Theory of Inventive Problem Solving for Systematic Innovation: Case Study of Water Dispenser Design Refill bottle Dispenser insert Dispenser unit Main body   Figure 3: Main components of manual water dispenser    ThTe hreefriellf ibllobttolett lheehlpeslp tso tporporvoivdied heihgihg hwwataetre crocnosnusmumptpiotino ncacpaapcaictyit ythtahta t is aisblaeb lteo tcoatceart efrorf omr amnayn uysuersse rws hwihchic his ivsevreyr yeceocnoonmomicaicla tlot obeb eusuesde dini n offoicffeisc easnadn  pdupbulibcl ipclapclaesc.e sT.hTeh  iessiusseu  aeraisreisse  ds udruinrign gthteh ererfeilfliilnlign gprporcoecsess s dude uteot otthhee  wweeiigghhtt oof ft htehree prleapcilnacginfugl l fwuallt ewr baotettrl ebwoittthlen  owrimtha lncoaprmacailt y capoafc5i‐tgya  ollfo n5‐(g2a2l.l7onL )(.2W2.7it hL)a p. pWroitxhi mapatperwoxeiimghatteo fw2e3igkhgt, tohfe  2r3e fkilgl ,b  tohtetl e refiimll pboostetlse niemgpatoisvees rnefeigllaintigvep rroecfielslisngis spureoctoestsh  iesscuoen stuom  there pcaorntsicuumlaerrl y pawrtiocmuleanrlyto  wlifotmtheen hteoa vliyftr  ethfiell  hboeattvley arnedfilpl labcoettilte inanthde  pcloarcree citt pinos  itthioe n corornectth  epotsoiptioonf otnh ethwe attoepr  doifs tpheen swear.teTr hduissp, etnhseers.o Tluhtuiosn, thtoe ssoolluvteiotnh e to csoonlvtrea tdhiec tcioonntirsaddeictetiromni nise ddettherromuignhedim thprleomugehn t iinmgpTleRmIZenmtientgh o dT.RIZ  method.    3.1 Problem Definition using TRIZ   3.1I n TPRrIoZblmemet hDoedf,intihtieonp urosibnlegm TRwIZas  first classified based on the  contradiction occurred. As for the water dispenser, the current design In pTrRovIZid  ems ehtihgohdd, rtihnek inpgrocbalpeamci tywaasn dfilressts  crleafsilsliifniegdp  rboacseesds . Hono wtheve er, conimtrapdoiscetdionre oficlcliunrgreddi.f fAicsu flotyr tdhue ewtaotehr idgihspfeonrcseer,i sthree qcuuirrreednt tdoelsiifgt nt he prohveiadveys  hreigfihll  dbroitntlkei.nTg hcuasp,abciatsye danodn  lethsse  rseiftiullaitnigo np, rToRceIsZs. cHlaosswifeievder,t he impcoonsetrda driecftiilolinnga sdainffeicnuglitnye  edruine gtoco  hnitgrahd  ficotricoen ,isw  rheeqruebiryedim  tpor olivfti ntgheo ne heapvayra  rmefeitlel rbroetstluel.t eTdhuins,c  breaasteidn goont hthere nseitguaattiivoen,p  aTrRaImZe  ctelars. sUifsieindg  tThRe IZ conmtreatdhiocdti,otnh eass paenci fiecngpirnoebelreimngi scloantetrracdoicntvioenrt,e  dwhinetroebgye niemraplrpovroinbgle m oneb apsaerdamonetethr ereTsRuIlZted3 9ins ycsrteeamtinpga  roatmheert enresgdateifvine itpioanra.mTehteerp. rUocseinsgs  to TRgIZen  mereatlihzoedt,h  ethsep escpifeiccipfirco  bplreomblienmto  mis olraetegre nceornavl eterrtemd reinptroe sgenentienrgalt he prosbitlueamti obnaseenda bolens  mthoer  eTiRdIeZa s3t9o  sbyesgteemne rpaaterdambeyterersm  dovefiningittihoen.c  rTehaeti ve prothceinssk intog  gbeanrreirearliczaeu stehde bsypethciefiicn  fpluroebnlceemo ficnotom  pmleoxret egchenneicraall tteerrmm. In repTrResIeZn, ttihneg ptrhoeb lesmitudaetifoinni tieonnabolrees nmgionreee riindgeacso ntotr abdei ctgieonnesrtaatteedm  ebnyt  is remfoorvminugla  ttehde bcarseeadtivoen  tthhienk“iifntgh ebna‐ rbruietr”  cparuinsceidp leb.yI nthgee ninerfalul,etnhcee woof rd complex  technical  term.  In  TRIZ,  the  problem  definition  or  engineering  contradiction  statement  is  formulated  based  on  the  “if‐ then‐but”  prinIScSipNl:e1.9 8I5n-3 1g5e7neraVlo, l.t1h0e  wNoo.r1d J“anifu”a ryco- rJurensep2o01n6ds  to  the  77

Journal of Advanced Manufacturing Technology“if” corresponds to the manipulating variable of the solution suchas length, volume and shape while the word “then” corresponds tothe positive or improving condition which the solution is intended toachieve such as increasing strength of the product. The last word toformulate the engineering contradictions statement which is “but” inthe other hand corresponds to the negative or worsening conditionwhen the solution is implemented, such as increasing the weight of theproduct [1].Thus, the specific problem defined into engineering contradictionstatement according to TRIZ method was formulated as follows:‐If the refill bottle volume is large, then more drinking water capacity is availablebut more difficult to lift the refill bottle.3.2 Solution Generation using TRIZBased on the previous engineering contradiction statement, theimproving parameter related to TRIZ 39 general system parameterwas defined. Based on the TRIZ method, the improving and worseningcondition for the problem can be linked with the TRIZ 39 systemengineering parameters. The 39 system engineering parametersavailable in TRIZ include weight of stationary object, weight of movingobject, speed, force, strength and shape. Based on the water dispenserproblem statement and engineering contradiction statement, two (2)TRIZ engineering parameters were selected which were productivity(parameter no.39) to represent the improving aspect intended for thenew design and the coupling worsening effect due to large refill bottlewhich reduced the ease of operation (parameter no.33) of the wholerefilling process. The general parameters obtained were then arrangedinto the TRIZ contradiction matrix whereby potential solution couldbe obtained based on the TRIZ 40 inventive principles solution. TRIZ40 inventive principles solution tool reflects 40 solution principles thatare available to be selected. The selection of the solution principles wasbased on the recommendation after creating the contradiction matrix.Table 1 shows the contradiction matrix formed for the water dispenserproblem based on the TRIZ 39 engineering parameters.78 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Application of Theory of Inventive Problem Solving for Systematic Innovation: Case Study of Water Dispenser DesignTable 1: Contradiction matrix for the water dispenser refilling process based Table 1: Contradoinct tiohne  TmRaItZri x3 9f oErn tghien weeartienrg d Piaspraemnseetre rrse f[i1ll]i ng process based Improving on the TRWIZor s3e9n iEnng gPianraemereitnerg ParaTmReIZte 4r0s  i[n1v]e ntive solution PIamrapmroevtienr g  Worsening Parameter TRIZ 40p irninvceinptlievse  solution #39. PrPoadruacmtivetietyr  #33. Ease of Operation  #1. Segmenptaritniocnip  les #39. Productivity  #33. Ease of Operation  ##218. SMeegcmheantiacsti osunb  stitution  ##72. 8N. eMsteecdh adnoilcl s substitution  ##170. NPreesltiemdi ndaorlly   action  (prior  a#c1ti0o.n  P –r e“ldimo iint ainry a dacvtaionnce  (dp”r)i or   action – “do it in advanced”) B ased  on  the  contradiction  matrix  formulated  as  shown  in  Table  1, thBBeaarssee ddw oeonrne t htfhoeeuc roc n(o4tn)r tasrduaidictiatcibotilnoen min  mavteranitxrtifvxo erf mosorumlulauttileoadnte apdsr sianhsco iwsphlneoswin tnhT aaitbn cl eoTu1a,lbdtlhe be  er1e , atwphpeelrrieee fdwo uertroe( 4f)otshuueri t(a4pb) rlsoeubiinlteavmbeln et isivnuevcsheon  ltuaivtsie o nssoeplgurmitnieocnipt apletrisiontnhc iaptalcenosdu t lhdmabt eeccoahupalpndli icbesde  satuopbptshtlieetudpt riootnbo.l  eTmthes uncpehrxotab ssltesamegg em sienun ctthah tei oawns aatsneedrg  mdmiesepnchteanatnsioeicrns  psrauonbbdsl teimtmu tesicoohnlva. inTnihgcse  psnrueobxcsettssisttu agtuieosniinn. gTt hheeT wRnIaeZtxe tr msdtiaesgtpheeo nidns e  trwhpear sow baldetemrv edslooislpvpiiennnggs eprsr popecrceoisbfsilceu mssi nosgloulTtviRoinInZg  spmtrraeottcehegosisde sw utaoss indsogel vveeTl oRtphIZien gomscpceuetcrhriofeidc scowolunattsiro anddsiectvrtiaeotlneog pbiienasgste odss opolenvc eitfthihcee   ofsocoucluur rt(ir4oe)nd  rsectocronamtteramgdieiscn tditooend  s bosoalvslueet ditohonen potrhcicenucfrioprueledrs ( c4so)hnortewrcaondm icnmt iToeannb dlbeead s1e spdor lueovtniio otnuhsepl yrfi.on Aucirfp te(l4ers)  arsnehacoloywmznimngien ndTteahdbe l seol1fuotpuiorren  v pio(r4ui)ns clyips. olAelsuf ttseihoronaw  nnar leiyncz oiTnmagbmlteh ne1d pafortieuovrnios( 4u)slnsyoa. lmAutefitloyenr  sareengcamolymeznmitnaegtni odnat,t himoe neschfoanunarim cse (lsy4u) bssetsigotumluteitoniontna, t inoenrse,tecodmm  edmcohlelan ndainacsdti opnsurse blsimtnitaiunmtaieorylny , asncetegisomtnee,d ntdwtaotoli lo(na2n,)  dmppoesrcsehilabimnleii cnsa prseyucibafsicctti itosuontli,uottnwi,o onn (e2sst)treapdtoe sgdsiioeblsll ewasnepdree c piafribcellesim otloiun tabioreyn   faosctrrtmaiotuenlg,a itetewsdow  w e(hr2e)i cahpb olwsesetibroeleb  r eeslpfaoetrecmidfi uctl oas toienlduvtewinohtniiv cshet rwsaotelerugetiieroesn la wpteerdirnetc oiapbilnleev  entnot .i bv1ee  (fssoeorglmumtuieolnanttaeptdrioi nwnc)hi paiclnehd n won.eo1r.e ( 1sre0eg l(mapteerednl tiamtoti ioninnav)ryean natdicvtnieoo n.so1).0l uB(tpaiorseneld ipm  roiinnn actrihpyelae  c TntRiooI.nZ  )1 . g(Besanesgeermdaleo nsnotaltuthiteoinoTn)R  aIrZencdgo emnnome.r ea1nl0sd oa(lptuiroteinolisnm, rsienpcaeorcmyif imca cestonioldunat)ti.oi oBnn asss,tersdapt eeocgniife icsth sreoe llTuatRteioIdZn   togst eirnaevtereagnli tesisvoelru estloaioltuendt iroetnoco simnegvmmeneentnidvtaetisoonlus a,t insopdne pcsriefegilcmi mseoinnlutaatrityoio nan cstatirnoandte fpgorireemsli umrelialnatetaedrdy   btayoc ttiihnoevn edfneotsriivmgenu seloar ltauesdt isobhnyo swtehnge midnee Tnsitagabntlieeor n2a . asnsdh opwrenliimniTnaabryle a2c.tion formulated   by the designer as shown in Table 2.    Table 2: Specific solution strategy based on the TRIZ solution principles TTaRblIeZ  240:  Sinpveecnitfivice  solutioSonl usttiroant edgesyc rbipatsioends on the TSRpeIcZif isco sloulutitoionn  pstrriantecgiyp les soTlRutIiZo n4 0p irninvceinptlievse   Solution descriptions Specific solution strategy #1s. oSleugtmioenn ptartiinocni ples  a) Divide an object into  a)  Use  many  small  refill  bottles #1. Segmentation  daif)f Derievnidt ep aarnt so  bject into  inas) teUasde  omn aonnye  slamrgalel rreeffiillll  bbootttllee. s  bd) iMffearkeen at np aorbtjse ct easy to  Tihnes teiands eornt  ocnoem lpaorgnee nret fiilsl  baoltstloe .  dbis)a Mssaekmeb alne object easy to  reTdhees iginnseedr t toc omfropmon  e1n t unisi t atloso    c)d Iisnacsrseeamseb tlhe e degree of  mreudlteipsilgen uendi tst.o    from  1  unit  to  frca) gImncerneatastei othne o dr egree of  multiple units.  sefrgamgmenetnataiotino n or  ds)e Tgrmanensittaiotino nto   micro‐level #10. Preliminary  ad) )P Terfaonrsmit itohne  troe qmuiicrreod‐ level  a) Redesign the refill bottle with a#c1ti0o.n P  reliminary  cha)a nPgeref orf man t hoeb jreecqt u(eiriethde r  haa)n Rdeled feosrig ena steh eo fr ehfainlld blointtgl e with action  fuchllayn ogre p oafr atina lolyb)j ebcet f(oerieth iet ri s  handle for ease of handling  nfeueldlye do r partially) before it is  bn) ePerdee‐adr range objects such  thba) tP trhee‐yar cran gceo mobej eincttso  such  atchtiaotn t hfreoym ca tnh ec ommoes ti nto  coacntvioen ifernotm p ltahcee m anodst   wciotnhvouent ileonstin pgl atcime aen fdor    thweitrh doeulti vloersyin  g time for   their delivery B ased  on  the  specific  solution  strategies,  new  conceptual  designs  of thBea sreedf ilol nb othttele  s  panecdi ftihc es odliustpioens  estrr aintesgeiret sc, onmewpo  ncoenct ewpteurea l ddeevseilgonpse dof  ((trhreefefe err et ftoio lF lF ibgigouuItrStreSlee N4  4:)a).1n .9  d 85 -t3h1e5 7dispVeonl.s1e0r  inNsoe.r1t  cJoanmuaproyn-eJunnte  w20e1r6e  developed79 

Journal of Advanced Manufacturing Technology Based on the specific solution strategies, new conceptual designs of the refill bottle and the dispenser insert component were developed (refer to Figure 4).  Journal of Advanced Manufacturing Technology   Figure F4i: gNuerwe 4 c:oNnecewptcuoanlc depestiuganl dofe sriegfinllo bfortetlfeil lwbiothtt lheawnditlhe hanandd dleispanendser  dispinesnesretr cionmseprot ncoenmtp foorn emnatnfouralm waantuera ldwisapteenrsdeirs penser ThTeh  neenwew  rerfeiflill lbbootttlele  conceptuuaall ddeessiiggnn ddeevveeloloppeeddu  usisninggth  tehTe RTIZRItZo olstoowlsa s  swmaasl lesrmianllseirz einco  msizpea rceodmtopathreedi ntioti atlhbeo  titnleitidael sibgont.tlHe odweesvigenr,. byHouwsienvgerth, ebnye  uwsidnigsp  tehnes enreiwns edritsdpeesnisgenr,  minasenryt sdmeasilglenr, rmefialnl byo  sttmleaslcleoru  ldrefbilel abtotattclhese dcotuoldth ebed aistptaecnhseedr atot  othnec edtiospeennssuerre atth oatnhceig tho wenastuerrec athpaatc ityhigwha ws mataeirn ctaaipnaecditsyi mwialas rmtoauinstianignesidn gsilme lialargr etor eufislilnbgo tstilnegulsee ldarpgree vreiofiulls ly.boAttlneo uthseedr  apdrvevaniotuagsleyo. fAtnhoetnheewr addevsaignntawgea soft hthaet  tnheewli fdtiensgigpnr wocaess sthoaftt hethen eliwftinsmg aplrloercersesf iollf  bthoett  lneewre qsumiraellderl ersesfillli fbtiontgtlee nreeqrguyir.edT hluesss,   liitftcianng  beenoerpgeyr.a tTehduesa,s  iilty  ceasnp ebcei aollpyebryatwedo meaesniluys  eerssp.eAcidadlliyti obnya lwaodmvaennt augseeorsf.t heAdndeiwtiodneasli gandwvaanstraegfele  cotfe  dthteh rnoeuwg hdtehseighna nwdalisn  grepflreoccteedss  twhhroicuhghw atshea lsohainmdplirnogv pedrobceystsh we haidcdhi twioans oalfsho ainmdplerotvoetdh ebyb othttele afdodritaiobne totef rhgarnidplea ndto athnee baosettloef fpolra cai nbegtttehre gbroiptt laencdo rarne cetalyset ooft hpeladciinspge tnhsee br ointtsleer ctosrercetciotlny.  Into adthdei tiodnis,pthenesneerw  irnesdeerts igsnecdtiiospne. nIsner  iandsderittiwonit, h tuhned  enrecwut  srloedt wesaigsna lsodisapbelensteor exinpseedrti tewainthd  upnrodveirdceutp  rselocits  ewpalsa caelmsoe natbolef  tthoe  erxepfielldbitoet tlaenodn  toprothveidien sperrte.cTishee  palpapcelimcaetniotn  oof f tthhee  TreRfiIlZl  tboootltslea  sondteom  tohnes tirnasteedrt.t hTrhoeu ghaptphleicactaisoen sotfu dthye hTaRsIZp rtoovoilds eads  dsyesmteomnsattriactepdro tbhlreomugdhe  tfhinei tciaosne asntuddiyd  eahags enperoravtiidoend prsoycsetesmseastitco  pdreotberlemmin  edetfhienitrieoqnu iraendd siodlueati ogne.nMeroartieoonv er,prothceesssoeslu ttoio dnestegremnienrea ttehde aretqtuhiereedn dsolouftitohne. cMoonrceeopvtuera,l thdee ssioglnutpiornocs essgenweerraeteadls aot atbhlee etonds oolvf ethteh ecocnucrerepntut aplr dobesleigmn wpritohcoeusst hwaevrien aglstoo mabalke e ato tsroaldvee‐ otfhfeo  cnutrhreendte spirgonbpleemrf owrmithaonucet  whahviicnhgi stou smuaaklley  cah  tarlaldeneg‐oinffg  otno bether edaleisziegdn upseinrfgorcmonavnecne tiwonhaiclhs oilsu  tuisounaglleyn  ecrhaatliloenngpirnogc etsos .be  realized using conventional solution generation process.    80 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016  

Application of Theory of Inventive Problem Solving for Systematic Innovation: Case Study of Water Dispenser Design 4.0 CONCLUSIONS In conclusion, the applicability of the TRIZ method in problem solving process has been demonstrated based on the case study of water dispenser design. It has been shown that the TRIZ method is able to provide innovative solutions to the sample problem through utilization of systematic approach which covers problem definition, idea generation and conceptual solution development. The structured problem solving process is also able to quickly assist in exploring possible solutions based on its proposed solution principle method. In addition, the solutions generated at the end of the conceptual design process are also able to solve the current problem without having to make a trade‐off on the design performance which is usually challenging to be realized using conventional solution generation process. ACKNOWLEDGMENTS The authors would like to thank Universiti Teknikal Malaysia Melaka and Multimedia University for supporting this project.REFERENCES[1] T. S. Yeoh, T. J. Yeoh, and C. L. Song, TRIZ ‐ Systematic Innovation in Manufacturing. Malaysia: Firstfruits, 2011.[2] S. Hamm, Tech Innovations for Tough Times, http://www.bloomberg.com/ bw/stories/2008‐12‐25/tech‐innovationsfor‐tough‐timesbusinessweek‐ business‐news‐stock‐market‐andfinancial‐advice, retrieved online of 2nd February 2016.[3] F. C. Labouriau and R. M. Naveiro, “Using the evolutionary pattern to generate ideas in new product development”. J. Braz. Soc. Mech. Sci. Eng., Vol. 37, pp. 231‐42, 2015.[4] J. R. G. Evans, “Seventy ways to make ceramics”. J. of the European Ceramics Soc., Vol. 28, pp. 1421‐32, 2008.[5] C. H. Yeh, J. C. Y. Huang, and C. K. Yu, “Integration of four‐phase QFD and TRIZ in product R&D: a notebook case study”. Res. Eng. Design, Vol. 22, pp. 125‐41, 2011.[6] D. Petković, M. Issa, and N. D. Pavlović, “Application of the TRIZ creativity enhancement approach to design of passively compliant robotic joint”. Int. J. Adv. Manuf. Technol., Vol. 67, pp. 865‐75, 2013.[7] E. L. Melgoza, L. Serenό, A. Rosell, and J. Ciurana, “An integrated parameterized tool for designing a customized tracheal stent”. Computer‐ Aided Design, Vol. 44, pp. 1173‐81, 2012.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 81

Microelectronics Thermal Dissipation Characterization Using Triz MICROELECTRONICS THERMAL DISSIPATION CHARACTERIZATION USING TRIZ M.C., Ong1, M.N., Abd Rahman2 1,2Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia. Email: *[email protected]; [email protected]: Thermal dissipation of a microelectronic device is a topic ofinterest amongst the researchers because poor thermal dissipation may causereliability problem during customer’s application. One of the factors thatcaused poor thermal dissipation of a device is the existence of air gap inside thepackage. Air gap blocks the heat dissipation path of the device, causing the heatto be entrapped inside the device and to the extent of becoming malfunction.In this analysis, TRIZ was proposed through Parameter Change (PC) as one ofthe principle solutions to increase the effectiveness of identifying poor thermaldissipation devices. Experiment confirmed that TRIZ PC principle was ableto identify poor thermal dissipation in microelectronic device even thoughthe device did not have air gaps. Such identification was not possible throughtraditional approaches, such as XRay or SAM.KEYWORDS: Air Gap, Thermal Dissipation, TRIZ1.0 INTRODUCTIONAbility to dissipate heat is one of the important elements in ensuringfunctionality of a microelectronic device. The thermal dissipation ismainly achieved by means of conduction from the die to the packageand by convection from the package to the external environment.One of the common problems faced in thermal dissipation in suchdevice is the presence of air gap between the die and package whichsignificantly reduces its thermal impedance and thermal dissipationcapability [1]. Such device potentially has poor reliability performanceand has to be selected out. The presence of air gap will slower downthe thermal dissipation of the device, but wafer process defects likeionization, inhomogeneous current distribution within a cell field orsome parasitic capacitance and inductance may contribute as well tothe poor thermal dissipation of the device even though the device iswithout the presence of air gap [2‐3].ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 83

   Journal of Advanced Manufacturing Technology    X‐Ray and SAM are the traditional approaches that are widely used to  idXe‐Rntaiyfya annd aSiAr gMapa rienstihdeet mraidcirtoioenleacltraopnpirco daecvhiecset whahticahre hwasid peolyteunstieadllyto  piodoern ttihfyeramnaali rdgisaspipiantsioidne. mHiocwroeevleecr,t rtohneisced  aepvpicreoawchhiecsh  rheaqsupiroet elonttsia  ollfy  epffooorrt  tahnedrm  atilmdei.s siMpaotrieoonv. eHr,o  wXe‐Rveary,  tahnedse  SapApMro  aacrhee  spreerqfourimreeldo tsbyo f seafmfoprltianngd btaimsise .oMnloyr.e Noveevre,rXth‐Relaeyssa,n edleScAtrMicaal rme peaesrfuorremmeedntb ymsaaym fpitl iinng  thbae sgisapon  tloy .idNeenvteifryth  seulecshs ,peoloecr trhiecaatl mdiesasispuarteimone ndtemviaceysf iitf ianptphreopgraipatteo  ciodnednittiifoyn suisc huspeodo rahs easht odwisnsi pinat ioTnabdlee v1ic. eTs hife acphparlolepnrgiaet eisc oonnd ittihoen  eifsfeucstievdenaessssh  oofw  tnhei nelTeacbtrlieca1l.  mTheeascuhraelmleenngte  tios  iodnenthtiefye fpfeocotri vtehneersms aol f dtihsesieplaetcitornic adlemviecaes ubreecmauesnet  tuosiindge nttoifoy  lpoowo rEtnheerrgmya, ltdhies smipeaatisounredmevenicte  mbaecya nuoset bues isnegnstoitoivleo wenoEungehrg; yb,utth ief museiansgu troeom henigthm Eanyerngoyt, btehes ednesvitiicvee  menayo ubgehc;obmuet  ifduessitnrugcttoioveh.i gThhEisn iesr gay t,ythpeicdael vciocnetmraadyicbteioconm foeudnedst riunc tthivise . InTvheisntiisvae tPyrpoicbalel mco nwtrhaidchic tcioann fboeu nsdolivnedth  ibsyI nuvseinntgiv  e“TPhreo bTlehmeowryh  iocfh  Incavnenbteivseo lvPerdobblyemus”i‐nTgR“ITZh  ewThhiceho ryiso  faI nwveelnl tisvteruPcrtoubrleedm  ”a‐pTpRrIoZacwhh  itcoh  sitsimauwlaetell  nsetrwu citduerae dina  psoplrvoinacgh  thtoe  estfifmecutilvaetenensesw  priodbelaemin  [4so].l vTianbglet h1e  ilelfufsetcrtaivteesn ethsse pardovbalenmtag[4e]s. Toafb  elele1ctirlliucaslt rmateeasstuhreeamdevnatn tcaogmespoafreedle ctotr iXca‐l Rmayea asnudre SmAeMnt. compared to XRay and SAM.           TabTlaeb 1le: A1:dAvdavnatnatgaegse sofo fEElelecctrtriiccaall MMeeaassuurreemmeenntt ccoommppaarreeddt otoX X‐R‐aRyaayn adnSdA SMAM  No  Area  X‐ Ray  SAM  Electrical measurement  1  Sampling  Sampling  100%  <1s  Size  2  Time  ~1 ‐ 30mins  3  Effort  High(manual/semi‐  Low  auto/auto setting)  4  Effective Medium(wafer  process  Low  if  inappropriate  ness   defect  can’t  be  condition is used  identified)  High  if  appropriate              condition is used  hPITmcim dnIhTmPTiaeaahdneeevraahRvreeevtctanrveaeIae haneeasntZeme isrouintmenftfuuitdfifteryfua mvefeinryeptoiivenecteenmnaierlceetnmar onogtitr pneghvigpid epvCnmrioeytCrnmuoerthtnhdo o othnchbweeaodotbuweelaw s,nuelul assnsopeapmgssaclsp ggmoysle ortsoyd eo,yoo   fdaoef arc(pneauawriP( megulPmrngdtsslCroahustoCisrde honsic)e egnsen )oeengetrdesiggwrsrrmdsl tnwa smel TtruaaetTtrnaaaRhet asarostlRehssd a tateIlrryreaZItudtd aZaeuds dta sit.tt Ts sis.eieeemTssiyseRdsdsm siRdsmypop iItppZ IssrertadZotoryetoam teoore it svimeoiissvitaieodsei nmietngnmimeia ndcdan pabdabpabee sdrlbel[eaet,rslole5 eievcoy isvcpv‐gca,itv a7ecaaiotnuecl]oe put al.see y tahsn[eIhtnbh5etnhe dbaeety‐eml esy 7n nmpl t p]heatdu ih.esanfunitsfsfonhtI hsyeif ihnwinyeienpco mnecmgrtwa migrtet pivpihe smvPereseeitPeleosreontrapelrinov,ae ercni rpercncisTstocncsrsthaoscRivrhiosg pplieciivpIle ciranelvZniaeeraslrlngees       l,   22.0.0        MMEE TTHHOODDOOLLOOGGYY           22.1.1 T RIZT ARIpZprAopapchro  ach  fTofeTRofuRfuIneZIncZd td iwvwineaianns s etchtschhsehoe ocsposeperunronl obddbdluelbuemeeme  tiotinoti csttserwteelwflao.fo s. eBrdBreyea;y ashisonioonncnwscrs.ree .eavFasFeisirirnirs,nsgtlgtt ylhyt,i ht,sh“e“Cei nCoEcoEnnrnnetertaerrarsgadgeyddiy cictuoituoisfosenendE”d”,n  ,wetwrhtaghaesyes    84 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Microelectronics Thermal Dissipation Characterization Using Trizeffectiveness  could  be  increased;  however,  this  increased  of  Energy coucoldu lbdribnrgin rgelriaelbiialbitiyli tpyropbrolebmlesm toswtoawrda rtdheth deedviecvei.c Te.hTish cisoncotrnatdraicdtioctnio  nis isbbeesstt  soslovlevdedb y ubsyi nguTsRinIgZ  beTcRaIuZs e TbReIcZaudseea lsTwRiItZh “Cdoenatlrsa diwctitohn ”.“CMonotrreaodvicetri,oTnR”.I ZMisoarewovelelr‐,s trTuRcItZu reisd  a pwpreolla‐cshtrutoctsutirmedu latpepnreowachid  etao instimsoulvlainteg nthewe e ifdfeecat iivne nsoelsvsinpgro tbhle mef.feTchtisveisnevsesr yprimobpleomrta. n Tt heissp iesc ivaelrlyy inimmpoarntuanfat cetsupreincgiaallnyd ind mevaenloupfamcteunrtinfigel adn. d development field.   FigFuigreu r1e  s1hoshwosw  tshet hfelofwlocwhachrta rotf oTfRTIZR.I ZT.RTIZR IZbegbiengsi nbsyb  dyradwraiwngin  tgheth  eFuFnuctnioctnioanl aMl oMdeold AelnaAlynsailsy sfoisr “foInre“ffIencetfifveec tEivleectErilceaclt rMicaeal sMureeamsuenretm ine ntideintiifdyeingti fypionogr pthoeorrmtahle rdmisaslipdaitsisoinp adtieovniced”e.v  iScuec”h.  Sduiachgradmia gwraams  two asuntdoerusntadnedrs thaonwd  thhoew  sythsteemsy, ssteumb‐,sysustbe‐msy satnedm  thane dsuthpers‐suypseter‐msy  sotfe man of“Inaenffe“cIntievfef ecEtilveectrEicleacl trMicaelasMureeamsuernetm  einn t iidnenidtiefynitnifgy inpgoopro  otrhethrmeraml aldisdsispsaiptiaotnio  ndedviecvei”c ew” ewree rceonconnecnteecdte. dC. aCuaseu‐saen‐adn‐Edf‐fEefcfte catnanlyasliyss  iws aws aspropvroidveide adftearft FerunFcutniocntiaoln MaloMdeol dAenl aAlynsailsy tsois idtoenitdifeyn thifey rtohoet rcoaoutsec aouf seineoffecintievfefe  cetilveectreicleacl trimcaelasmureeamsuernetm  eint  idnenidtiefynitnifgy inpgoopro  otrhethrmeraml aldisdsispsaiptiaotnio  nddeevvicicee. . NNeexxtt,,b  abseadseodn  thoeni dtehnet ifiieddernotoiftiecdau  sreo,oEtn  gcinaueesrei,n  gEnCgionneterraidnigc tioCnonstraatdemicteinotn wsatsatecmonesnttr ucwteads.  Scpoencsitfriuc ctiemdp. roSvpinecgifiacn  dimwproorvseinngin  agnds ywstoemrsenpianrga msyestteerms   wpaerraemiedternst ifwieedre firdoemntiEfinedg infreoemrin  gEnCgionneterraidnigc tiConontsrtaadteicmtieonnt . stWatheemnentth. eWseheimn ptrhoevsien gimapnrdoviwngo rsaenndin  gwoSryssetneimng PSayrasmtemete  rsParmamatcehteerds  wmiathtchtehde  wCoitnht ratdhiec tiConontMraadtricixti,onth  eMarterliaxt,e dthpe rrinelcaitpeldes  ptroinimciplreosv etot hime eplreocvtrei ctahlem  eeleacsturriceaml emnteaesfufercetmivente sseffienctidvenetisfsy iinng  idpeonotriftyhinergm  paolodr istshiepramtiaoln  dwisesripeaptiroonp owserde bpyroTpRoIsZed.  Inbyt hTiRsIZst.u Idny t,hPisa rsatumdeyte, rPaCrhaamnegter( PCCha) npgrein (cPipCl)e pwriansciupslee dwtaos uchsedck toth  echecffke ctthive eenfefescstiovfeneelescst roifc aellemcteriacsaul rmemeaesnutreinmiednetn  itnif yidinegntipfyoionrg tphoeromr althedrimssaipl adtiisosnipdaetivoinc ed. evice.                    85 Figure 1: TRIZ Flow Chart Figure 1: TRIZ Flow Chart ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

   Journal of Advanced Manufacturing Technology 2.1.1 Functional Model  2F .u1.n1c tioFnuanl cMtioondaell Manoadlyelsis  in  Figure  2  was  a  modelling  to  analyze  Fhuonwc tiothnea l Mcoomdpeol nanenaltys siosfi n“FIingeufrfec2tiwvea s Ealmecotrdiceallli nMg teoasaunraelymzeenht owin  tihdeenctoimfypinogn enptosoor f “thIneremffeacl tivdeisEsilpecattriiocna l Mdeevaiscue”re  minetnetrainct idwenitthif yoinnge  paonoorthtehre. rmFraolmd iass  itpyapticoanl  d“eFvuincect”ioin teMraocdtewl”i,t hthoen  e“Aarnrootwhe  r(.F)r”o mis  aa  tfyupnictailon“F  suynmctbionl  tMhaot dceoln”,tatihnes “lAotrsr oowf  i(nfo)r”miastaiofnu n(Bcotilodn:  Usysmefbuol;l  Rtheadt:  cHonartmainfusl;l otDsootfteidn folrinmea: tiuosnef(uBlo  lbdu: tU  sienfsuulf;fRiceiedn:tH). a rmGfeunle; rDaloltyt,e difl inthee:   ufusenfcutliobnu tiisn susffeifcuiel,n  tt)h. Gene nietr amllyu,sitf tbhe fuknepcti;o  notihseurswefiusel,  tiht enmiut smt ubste  beelimkeinpat;teodt.h  eFrowr istehei t fmunucsttiobne  welhimicihn aitse du.seFfourl tbhuet fuinnscutifofinciewnht,i cthheisn  uimsepfurol vbeumt eints ufmfiucisetn  tb, eth  ednonime ptroo veimmpernotvme utshteb  eindsounffeictioenicmyp. roTvhee  tihneteripnrseutfafitcioienn coyf.  FTighuerei n2te  rwparse tatsi ofnollofwsF:i g“uMreeas2urwemaesnta sCofnodlliotiwons”:   “wMaesa ususreefmule nbtuCt oinnsduitfifoinci”enwtalys suuspefpulliebdu toi nthsue f“fiEcilecnttrliycasl uMpepalsieudremtoentht”e.  “TEhlecrterfiocarel , M“eEasleucrtermicaenl t”M. eTahsueremfoernet,” “Eisle ctnriocta l sMenesaistuivreem  eennto”uigsh noint   smenesaistuivreinegn othueg h“Dinevmice”a saunrdin ngotht eab“lDe etvoi cde”istainndguniostha bbeletwtoeednis tthineg guoisohd  baentdw epeonotrh  ehegaoto  ddiasnsidpaptoioonr  hdeeavticdei.s sIipna  toiothnerd ewviocred. sI,n  “oMtheearsuwreomrdens,t  “CMoneadsituiroenm” esnhtoCulodn dbieti osnu”ffischieonutldy abpepsliuefdfi ctoie “nEtllyectarpicpalli eMdeatosu“reEmleecntrt”ic atol   Minecarseuarseem  etnhte”  teoffiencctirveeansestsh eoef ffiedcetinvteifnyeisnsgo  fpiodoern  ttihfyeirnmgapl odoristshiperamtioanl   ddiesvsipcea.t i on device.    F  i  g Fuirgeu2r:eF 2u: nFcutniocntiaolnMalo Mdeoldoefl aonf a“nIn “eIfnfeecftfievcetiEvlee EctlreictarlicMale Maseuarseumremnteinnt in  idideenntitfiyfyininggp poooorrt htheerrmmaalld disissipipaatitoionnd deevvicicee””    22..11..22  CaCuasues Ae nAdn dEfEfeffcetcst As Ananlaylsyisi s fiiBMrfi Birdnoondooyyeueoeeueo fnantfnntfpfpst edtedcieuceicfc.afr.aytrry tfuiBfeuiBioviovnsmynsryereegemgnm enq q “enp“ieupiunsItnIsoneosnegsgCossos s ttrutorutiCoiCo ofnoftfta hfnainhdiiuicdueicdieinisnritesereeiemgengmnonn‐‐ ttanataotaioin f”lnnfMlnyM dy.dd d “T‐e“‐ietEitWsaEhhWsahsfssfesifeiufshieuphep rycpryaacpaetetotg omtt imtioaho(oho(CeirCneerennn An A tmttdmchdthEE oeeCeee)Cev)nrvara omoifmsaiscanicnunruenaedamdra?rl?alei”eli ”tleytmd,imyd,idos oistietinsehisnshtnssn”sh,e”i,etit p ep  toatioaahiashnrosnrtet eib sinso“no w“sworInornIenoetnoter oa rvdoaredept patfelfel fpetfvpevceicedrdoiarciacoccoutn tuetpietiposvvso rserewewi eeita ta heahoitaoitnneesnfeesf       86 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Microelectronics Thermal Dissipation Characterization Using Triz iMn ethaseuFruenmcetinotn CaloMndoidtieolnA”n. aTlhyissi sawgahiner ecotnhfeir“mMeeda stuhree mobesnetrvCaotniodnit isoenen”  iisn thtehreo otFcuanucsteiofnoarl “InMeoffdeectl iveAEnlaelcytsriisc alwMheearseu  retmhee nt“Mineiadseunrteifmyienngt  pCMooonerdatsihutieroernm”ea inlst dt  hCiseos nirpodaoitti oocnna”ud. seTevh fiocsre  a ”“g.Ianinef fceocntfiivrem Eedle cthtrei coabl sMerevaastiuorne mseeenn t in  idine nttihfyei ngF upnocotiro tnhael rmMaol ddeisl sipAantaiolyns ids evwichee”r.e    the  “Measurement  Condition” is the root cause for “Ineffective Electrical Measurement in  identifying poor thermal dissipation device”.       2  C    . 2  1 oF  .  .1n i 3  g.  t3   u  r   Fa rFiedECgiEg3iuEnoucn:rngntrCegiegi toia 3nir3nunn:a:e  eCsed CeMeeeariarrcauiuiaintnssnniteegdorgg  iaan E xnnf tdMtdfthheh CC CEeecEearrotforoftfmmAfnmnerneciatatncaxttrlrl tra alAa d daAldddyindisiinssaisscisicalisctsiyptiliptiypsoafioaiotsoansitnir toni,sfi oino, o,nfn r node ir dfeSnd fvieSeyeeSnivfcsvcyfeyitteeifcsiesc.cfve tteemtee.ie.cv mmt ieidv ie den P eitandiPfrteiiaacanfmirartcatiaaefimtmoiticenoaeerntot ti eoeofrfrnp  pa oonoofod rapr  noodr   Contradiction Matrix                       Figure 4: Engineering Contradiction, System Parameter, Contradiction Matr ix          FFigure 44:: EEnnggiinneeeerirningg CConotnrtardaidctiicotnio, nS,ySstyesmte PmarPaamraemtere,t Cero,nCtroandtircatidoinc tMioantrix   Next,  based  on  the  root  caMuaster ixmentioned  above,  Engineering    NEC E ECEE  NCnnnooenngggonnxegginiixtttnnn,rriittnna,raeee aeededeebdeebrrriiarrciciiiasnciinnttsnnetiigggeiooggdod  nn  CCnC   ososoosCCottnntnnaanaootttttt rnrnreeeaaattmttmmdrdrdhhaaiieeeiedccdcn nntttiiititcitrco roo twowtowninnioooo:aa::a tns tn ss  c  cccocaoocnaucannusasnstssenr tte urr uucmbtccmebetet deeened .dt nei..ot aeinsoaienlsdyiel  dya cboaocnbvosoetnvr, suetcE,rtuneEcgdtin engdeuie nsreiinnueggrsi  inngg  bEI “fuII “n ffIttg …fh…t…ihente” htem heemsernteniae…an…atsegsubmubCurureeetotmn…m…ntte.””rn  assttdtt  aaccitcotoeetnnmimdodenieitntinciotot.an .n n    isbis ei niencarcseriaelsyaescdeo,d nt,h sttehrnue nctht eetdh  ʺeTu eʺsmTinepgmer“paIteufr…aret”uth roeef”n  …of  tdI SdthfhyS dteeheetyvsvehe tsviidde ecctidemeceeemmeev voo  vioPi rerccPirca aeecca ercs aar aauiiauuissmusrms s seiieeeienemnn tʺʺcceeRRrrrnee:ee  aaltliissaaceeebbboddidiilnll,i,,i it dttybbybyiʺuʺutuʺ ip ttpot pr tnrothtrohhboiibsiilbsses llet meiettmnmeme.c mm.r.p  eppeareesarretaaudttru,uerrt heeri esrrneiis stemeh  imemghʺiiggtT hhedmtte  sdpdteererossatyttrr uootrhyyee”   tthhoeef   FFroromm  t hthee  aabboovvee  EEnnggiinneeeerriinngg  CCoonntrtardadicitciotino ns tastteamteemnet,n tth, et hime pimropvrinovg ing  anandd w woorrsseenniinngg  ssyysstteemm  ppaarraammeetetersr sw wereer eid iednetniftiiefdie ads  afos lfloolwlosw:  s:     WImWImoporprsrorseoevnvniinininngggg   S SSSyyyysssstttteeeemmmm    PPPPaaaarrrraaaammmmeeeettteteeerrr:r: : :# # ##1217277,7,  ,T,R  TReemeleimalpibaepibrleaiitrltyaiut tyrue r  e  ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 87

Journal of Advanced Manufacturing Technology System Parameter: From the above Engineering Contradiction statement, the improving and worsening system parameters were identified as follows:   Improving System Parameter: #17, Temperature W  orsening System Parameter: #27, Reliability BC BCyyoo nnppttrruuaattddttiiiinnccgtgtii oottnnhh eMeM  iaiammttrrpipixrxr:o:o vviinngg  ssyysstteemm  ppaararammeeteter r#1#71,7 ,TTememppereartauturer eanadn d wwoorrsseenniinngg  ssyysstteemm  ppaarraammeetteerr  ##2277, , RReelilaiabbiliiltiyty  inin  ththe eCConontrtardaidcitciotino n MMaattrriixx,,  TTRRIIZZ  pprrooppoosseedd  tthhee  ffoolllolowwiningg  pprirnincicpiplelse s toto  imimpprorvoev ethteh e eeffffeeccttiivveenneessss iinn iiddeennttiiffyyiinngg ppoooorr tthheerrmmaal lddisisssipipaatitoionn ddeveviciec.e .   11.. PPrriinncciippllee 1199:: PPeerriiooddiicc AAccttiioonn  22.. PPrriinncciippllee 3355:: PPaarraammeetteerr CChhaannggee  33.. PPrriinncciippllee 33 ::  LLooccaall QQuuaalliittyy  44.. PPrriinncciippllee 1100:: PPrreelliimmiinnaarryy AAccttiioonn    FFiigguurree 55:: SSoolluuttiioonnss PPrrooppoosseedd bbyy TTRRIZIZ[8[8] ]   2.1.4 Propoossee SSoolluuttiioonn:: PPrriinncciippllee 3355 ““PPaarraammeeteter rCChhaanngge”e ”   TThhee  ssoolluuttiioonnss  pprrooppoosseedd  bbyy  TTRRIIZZ  mmuusst tbbee  ccaarerefufulllyly  sesleelcetcetded  babsaesde dono n EEnnggiinneeeerriinngg JJuuddggeemmeenntt.. OOuutt ooff tthhee pprrininccipipleles spproroppoosesded bby yTTRRIZIZ, o, nolnyl y pprriinncciippllee  1199  ““PPeerriiooddiicc  AAccttiioonn””  aanndd  PPrrininccipiplele  3355  ““PPaararammeteetre rCChahnagneg”e ” wweerree  mmoorree  ssuuiittaabbllee  ttoo  iinnccrreeaassee  tthhee  eefffefecctitviveenneesss sinin  ididenentitfiyfiynign gpopooro r tthheerrmmaall  ddiissssiippaattiioonn  ddeevviicceess. .HHoowweevveerr, ,““PPeeriroioddici cAActcitoionn” ”wwilill lnonto tbeb e discussed hheerreed  udeueto  tho e tfhoec ufsoicsuosn  iPsr inonci pPleri3n5c,ip“Plea r3a5m, e“tePraCrahmanetgeer”  . Change”.     In  TRIZ  context,  the  definitions  for  Principle  “Parameter  Change”  8w8 ere as folloIwSSsN: : 1985-3157 Vol. 10 No. 1 January - June 2016 a)  Change  an  object’s  or  system’s  physical  state  (e.g.:  to  a  gas,  liquid,  or solid)  b) Change the concentration or consistency 

Microelectronics Thermal Dissipation Characterization Using TrizIn TRIZ context, the definitions for Principle “Parameter Change” wereas follows:a) Change an object’s or system’s physical state (e.g.: to a gas, liquid, or solid)b) Change the concentration or consistencyc) Change the degree of flexibilityd) Change the temperaturee) Change other parametersThe definition of “D‐Change the temperature” was most relevant inthis study where the “Temperature” of the device can be increased bychanging the Energy used to increase the effectiveness of identifyingpoor thermal dissipation device.The experiment was carried out using with and without air gap deviceand using the existing measurement condition (Condition A, BeforeChanged of Energy) and new measurement condition (Condition B,After Changed of Energy). The results and findings were tabulated inthe next section.3.0 RESULTS AND DISCUSSION3.1 Negligible Air Gap Device versus Air Gap DeviceFigure 6 shows the SAM picture for 4 devices. A141 and A42 were withnegligible air gap while B75 and B112 were with air gap. Theoretically,those devices with air gap would be having difficulty in thermaldissipation and therefore regarded as poor thermal dissipation deviceif compared to A141 and A42 which only had negligible air gap. Thetheory is proven through experiment and could be observed fromFigure 8, Graph After “Parameter Change” where device B75 andB112 were showing “Elongated Non‐Linear Curve” earlier than A141and A42 when there was an increased in Current along X‐axis. This“Elongated Non‐Linear Curve” behavior was the “Curve line” in Y axiswhich happened especially on poor thermal dissipation device whenheat was trapped inside the package and resulted in self ‐ heatingphenomena causing non‐linear output response [9] before the devicebecame malfunction. While the A141 and A42 still showed a stable lineargraph, those poor thermal dissipation devices showed “ElongatedNon‐Linear Curve” Therefore, the quality performance between goodand poor thermal dissipation devices was clearly distinguished. Devicewith air gap was poorer in thermal dissipation compared to devicewithout air gap.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 89

and  A42  still  showed  a  stable  linear  graph,  those  poor  thermal  dissipation  devices  showed  “Elongated  Non‐Linear  Curve”.  Therefore,  the  quality  performance  between  good  and  poor  thermal Joduirsnsailpoaf Atidovnan  cdedevMicaneusf awctuarsin  gclTeeachrnlyol ogdyistinguished.  Device  with  air  gap  was  poorer  in  thermal  dissipation  compared  to  device  without  air  gap.  FFiigguurree 66:: SSAAMM PPiiccttuurree ffoorr 44 DDeevviicceess 3.2 Poor Thermal Dissipation Device in Negligible Air Gap DeviceAlthough A141 and A42 were both devices with negligible air gap,the device quality performance between the two was not identical andcan be clearly distinguished as illustrated in Figure 8. Device A42 wasobserved to have “Elongated Non‐Linear Curve” earlier than A141before it became malfunction while A141 survived at the end of theexperiment and did not have any “Elongated Non‐Linear Curve”.Such observation could be due to the weaknesses inherited from waferprocesses [2‐3] which caused device A42 performed poorer in thermaldissipation than device A141.3.3 The Attribute of Poor Thermal Dissipation DeviceBased on the experiments, air gap contributed to the poor performanceof the device. With the existence of the air gap in the device, the thermaldissipation was rather slow if compared to the good device. However,poor thermal dissipation device may not contribute from the air gapalone. Weaknesses from wafer processes could affect the performanceof the device. Therefore, electrical measurement was the better way inidentifying poor thermal dissipation devices compared to traditionalX‐Ray or SAM approach.3.4 Before and After “Parameter Change”Following the TRIZ Approach, Figure 7 and Figure 8 show the Graphbefore “Parameter Change” and the Graph After “Parameter Change”respectively. “Before Parameter Change” which used Condition A(Before Change of Energy) showed that the sensitivity of the electricalmeasurement was not significant. Therefore, straight curve could beseen and there was no difference between the good and poor thermaldissipation device. However, “after Parameter Change” which usedCondition B (After Change of Energy), the effectiveness in identifyingpoor thermal dissipation devices increased. Good device could be seenwith a straight curve while poor thermal dissipation device showed“Elongated Non‐Linear Curve”. Hence, good and poor thermaldissipation devices were distinguishable.90 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Microelectronics Thermal Dissipation Characterization Using Triz 3.5 X‐Ray/SAM and Electrical Measurement in identifying poor thermal dissipation Based on Table 2, X‐ray/SAM is only capable of informing the general srtealtaetmioennsth iwp abse twnoete n10t0h%e  btirguaei rbgeacpauasne dBt7h5e  tdheevrimcea lwdaisss icpoantifoirnm; tehde  hbaigvginegr aitrhge apw, othrset pothoerremr tahle  rdmisaslipdaistsioipna  ticoonm. pHaorwede vetor,  tdheisvsictae teBm1e1n2t  awltahsonuogth1  0d0e%victreu  Be 1b1e2c awusaes Bh7a5vdinegv iclaerwgears  aciorn  gfiarmp.e  idnh  aadvdinitgiotnh,e  Aw1o4r1st  dthevericmea  wl adsi scsoipnaftiriomnedco  hmapvianrged  thteo  bdeesvt itcheeBrm11a2l  dailsthsiopuagtihond ecvoimcepaBr1e1d2  two aAs 4h2a vdinegviclaer  gwerhiacihr  guasped.  ineleacdtdriictaiol nm, Aea1s4u1redmevenicte  awltahsoucognhf irbmotehd  dheavviicnegs hthaed nbeesgtligthibelrem aailr gdaisps.i pIna toiothnerc owmoprdasr,e deletcotrAic4a2l mdeeavsicuerewmheincth  cuosueldd eildeecntrtiicfyal  dmeevaicseu rwemithe nptoaolrth  tohuegrmh ablo  dthisdsiepvaitcieosn hmadornee  egflfiegcibtilveealyir  cgoamp.pIanreodth  etor wXo‐rRdasy, ealencdtr iScaAlMm eraesguarredmleesnst  coofu  lwdhidetehnetri fythdee vtihceerwmiatlh  dpiososirptahteiormn awl dasis  sciopnattriiobnumteodr ebeyf faeicrt ivgealpy  coorm  bpya  reexdtetronXal‐ Rfaayctaonr‐dwSaAfeMr  prerogcaersdsl edsesfeocftsw. hether the thermal dissipation was contributed by air  gap or by external factor‐wafer process defects.        Table 2: Effectiveness of Electrical Measurement compared to X‐Ray and SAM  Table 2: Effectiveness of Electrical Measurement compared to X‐Ray and SAM Device  A141  A42  B75  B112  Remarks  Air Gap  small  very small  2nd Biggest  Biggest  NA  If X‐Ray/SAM is  Fair  Best  2nd Worst   Worst   General  used in  Thermal  Thermal   Thermal  Thermal  Statement:  identifying  Dissipation  Dissipation  Dissipation  Dissipation  Bigger air  poor thermal  gap, poorer  dissipation  thermal  dissipation.  But not 100%  true.  Electrical    measurement is    used in  Canʹt distinguish the good and poor thermal dissipation device  identifying  poor thermal  dissipation  (Before  Parameter  Change)  Electrical  Best  Fair  Worst   2nd Worst   Electrical  measurement is  Thermal   Thermal  Thermal   Thermal  measuremen used in  Dissipation  Dissipation  Dissipation  Dissipation  t can identify  identifying  device with  poor thermal  poor thermal  dissipation   dissipation  (After  effectively  Parameter  compared to  Change)  X‐Ray and  SAM      ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 91

  Journal of Advanced Manufacturing Technology           Figure 7: Graph Before “Parameter Change”      Figure 8: Graph After “Parameter Change”         4.0     CONCLUSION   4.0 CONCLUSION IInn  ccoonncclluussiioonn,,  tthhee  aaddvvaannttaaggeess  ooff  uussiinngg  EElleeccttrriiccaall  mmeeaassuurreemmeenntt  iinn  iiddeennttiiffyyiinngg  ppoooorr  tthheerrmmaall  ddiissssiippaattiioonn  ddeevviiccee  ccoommppaarreedd  ttoo  XX‐‐RRaayy  oorr  SSAAMM hhaavvee bbeeeenn ddiissccuusssseedd.. TThhee iinneeffffiicciieennccyy ooff eelleeccttrriiccaall mmeeaassuurreemmeenntt  iinn iiddeennttiiffyyiinngg ppoooorr tthheerrmmaall ddiissssiippaattiioonn ddeevviiccee wwaass aallssoo ssoollvveedd  uussiinngg  TTRRIIZZ apapprporaocahchw hiwchhihcahs  bheeans dbemeeonn  stdreamtedonssytsrtaetmeda ticsaylsltye.mPraitniccaiplllye.  PParrinacmipeltee rPCahraamngeete(rP  CC)hapnrgoev id(PesC)a nportohveirdepse raspneocthtievre  pinerssoplevcitnivget hine   esloelcvtirnicga lthme eealescutrreicmael nmt eianseuffriecmieenncyt inperoffbicleiemn.cyD pevroicbelewmi.t hDeaviricge awpitihs   paioro  grearp iins  pthoeorrmera lind itshseirpmataiol ndicsosimpaptaiorend  cotomdpaevreicde  tow idthevoiucte awirithgoapu.t  Haior wgeavpe.r  ,Hdoewveicveesr, wdiethvicneesg  lwigiitbhl eneagirliggiabple caainr  ghaapv ecapno ohravthee  rpmooarl  thermal  dissipation  due  to  some  weaknesses  inherited  from  wafer   92 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Microelectronics Thermal Dissipation Characterization Using Trizdissipation due to some weaknesses inherited from wafer processes.Such identification of poor thermal dissipation in microelectronic devicecan be achieved by using electrical measurement with “ParameterChange” of TRIZ principle.REFERENCES[1] D.C. Katsis and J. Daniel, “A Thermal, Mechanical, and Electrical Study of Voiding in the Solder Die‐Attach of Power MOSFETs” Components and Packaging Technologies, Vol. 29, No.1, 127‐36. March 2006.[2] S. Wolfgang, “Void‐Detection in Power Transistors for the automotive use”. Master Thesis, Infineon Technologies AG. 2007.[3] H.Schulze, F. Niedernostheide, F. Pfirsch and R. Baburske,”Limiting Factors of the Safe Operating Area for Power Devices”, IEEE Transactions on Electron Device, Vol. 60, No.2, 551–562. February 2013.[4] T.S. Yeoh, T.J. Yeoh, and C.L. Song, “TRIZ Systematic Innovation In Manufacturing”. Firstfruits Publisher, Malaysia. 2012.[5] J. Chou, “Advanced Engineering Informatics An ideation method for generating new product ideas using TRIZ, concept mapping, and fuzzy linguistic evaluation techniques”. Advanced Engineering Informatics, Vol.28, No.4, 441–454. 2014.[6] P. Jiang, J. Zhai, Z. Chen and R. Tan, “The Patent Design Around Method Based on TRIZ”, Proceeding 2009 IEEE IEEM, 1067–1071. 2009.[7] Y.T. Jin, “TRIZ: Application of Advanced Problem Solving Methodology (ARIZ) in Manufacturing”, International Electronic Manufacturing Technology Conference. 2010.[8] Solid Creativity, 2014. TRIZ40 [online] Available at: http://www.triz40. com/TRIZ_GB.php [Accessed on 5 April 2014][9] C. Xu, X. Guo, H. Jiang, and Z. Zhang, “With Temperature Difference Air Flow Sensor”, International Conference Electronic Packaging Technology, 655–59. 2014.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 93

Minimizing Number of Defects in Nickel Plating Process Using Factorial Design MINIMIZING NUMBER OF DEFECTS IN NICKEL PLATING PROCESS USING FACTORIAL DESIGN N. Q. I. Baharuddin1, L. Sukarma2, E. Mohamad3 , A. Saptari4 and M.R. Salleh5 1,2,3,4,5Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia. Email: *[email protected]; [email protected]; [email protected]; [email protected]; [email protected]: Product defects may have a serious problem in anymanufacturing company because they may increase the production costdue to rework, delays, waste of time and material. The purpose of this studywas to investigate significant factors and their interactions in order to findthe optimal setting that could reduce the number of defects in nickel platingline. Factorial design has been used as the experimental design technique toidentify the critical factors to be controlled. This experiment investigated threedifferent factors using full factorial design. The results were analyzed usingDesign Expert software. Analysis of variance (ANOVA) was utilized to findthe most significant factors. The finding suggested that only one main factorBrightner Correction Solution (BCS) and one interaction factor (BCS and hotCOT temperature) affected the number of defects in nickel plating line. Theoptimum process setting was attained at 22 g/L of BCS and 50°C of hot COT(Cream or Tartar) temperature. A confirmation run using these new settingsapproved a reduced number of defects in nickel plating process.KEYWORDS: Factorial design, Design of Experiment, Product Defects, ANOVA,Nickel Plating Process.1.0 INTRODUCTIONDesign of experiments (DOE) has been used widely in industries tomodel and optimize manufacturing processes. This method focuses onminimizing the amount of required experiments for an analysis, whilemaintaining high quality results [1]. Factorial design, an instrument ofDOE, is an excellent statistical method for quality improvement, thatis, the optimization of heat treatment variables to eliminate wobblingof gears [2].Using factorial experiment to analyze industrial problemscan provide a good result within shortest periods of time with the leastcosts [3].The nickel plating process encounters a problem of high reject or defectrate especially in nickel plating production line number five. The FullISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 95

Journal of Advanced Manufacturing TechnologyFactorial Design experiment was implemented in this study to reducethe number of defective products. This study involved three factors,each with two different levels which is lower and higher. These factorsare suspected to have high impact on the number of defects.A previous study on eliminating wobbling of gears has shown the gearwobbling defects in the gears assemblies can be reduced to less than1% when applying factorial design [2]. The wobbling of gears can beremoved by finding the optimum setting between three heat treatmentvariables because it causes the multi speed gear assemblies becomedefective. Factorial design considers a response at every possiblecombination and set up factors at different levels [2]. The advantageof factorial experiment compared to the conventional experimentationis that all levels of a given factor are combined with all levels of everyother factor in the experiment, hence, a possible interaction betweenfactors can be verified.This study investigated factors and their interactions that had significantcontribution to the number of defects in the nickel plating process. Thedevelopment of regression model helped to explain the relationshipbetween the number of defects of the process and their significantfactors or interactions. Moreover, another crucial contribution of thisstudy was to find the optimum setting of parameters which minimizedthe number of defect products.2.0 METHODOLOGY2.1 Determination of the response variable and parametersOriginally, seven factors are assumed to have impact on the numberof defects in nickle plating line. However, only three variables wereallowed to be adjusted to avoid disruption in production operation.The input variables, therefore, include BCS (Brightner CorrectionSolution), hot COT (Cream or Tartar) temperature and nickel platingsolution temperature.To prepare the BCS, several steps should be followed and the analysiswas performed everyday to ensure the density level as required. Thepreparation involved titration process as in Figure 1.96 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

performed  everyday  to  ensure  the  density  level  as  required.  The preparation involved titration process as in Figure 1.   Minimizing Number of Defects in Nickel Plating Process Using Factorial Design 1 2 3    4 5 6       8 9 7     Figure 1: Analysis process of Brightener Correction Solution (BCS)  Figure 1: Analysis process of Brightener Correction Solution (BCS)TThheerree aarere ththreree etytpyepse sofo df edfeefcetsc tisn innicnkicekl epllaptliantgin pgropcreoscse. sTsh. eT hfiersfti riss tciaslled ycealllolewdiyshel lwowhiischh wohccicuhrso cwcuhresnw  choelonrc oolfo rthoef thperopdruocdtu  cdtodeos ens onto  tmmeeeet tthe rtehqeuriereqdu isrpedecsipfieccaitfiiocnat. iOonth. Oert htyerpteysp oefs dofedfeecftesc tasraer deudlul l(lu(unnbbrirgighhtetneneded) )and raunstdy.r uTshtey .inTihtieali nsiettitailnsge tptainrgampeatrearms ectaenr sbcea sneebne isne eTnabinleT 1a.b  le 1. TaTbalebl1e: 1T:h TehIen iItniaitliaSle Stteinttginsgosf othf ethPea Praamraemteertsers   Parameters  Level        High        Low  22   Brightener correction solution density (BCS) (g/L)  17    Nickel Plating solution  Temperature (⁰C)  52  58   50  60   Hot COT Temperature (⁰C)  22.2.2          DDaattaa ccoolllleeccttiioonn aanndd mmeeaassuurreemmeenntt ooff ddeeffeeccttss  In this study, data were collected from the result of one shift productionInru  tnhiws hstiuchdyc,o  dnsaitsat ewdeoref  4c0olloectstefdo rfreovmer ythseh  rifets.uTlth  eofn  ounme bsehrifot fpdreofdeuctcstion riunn nwichkieclh pcloantisnigstepdr oocfe s4s0 wloatss dfoert eervmeirnye dshbifyt. iTnhspe encutimonbse.rC  ouf rdreenfetlcyt,s  in ntihcekreel  pislantiongte cphronciceasls mweatsh  dodetetrommineeads ubrye  idnesfpeecctstiofonrs. pClautrinregntplyro, ctehsesr.e  is nToh teecinhsnpiceaclt omrewthaosdu stoin mg evaissuuarel  edxeafmecitnsa ftoior npblaytivnigs uparlolycelsoso. kTihneg iantstpheector wpaasr tussainngd vjuisdugaeld ewxahmetinhaetriothne bpya vrtissuwaellrye lroeojekcitnegd aotr tnhoet .pTarhtiss amnedt hjuoddged witnhhveeyothlvaerere dthqeeux appleaifrriiteesdn wcteoerwdeh oreeirjneesbcptyeedcet vioeorrn yn. oiTnto.s pTaehvciotsio dmr wveatahrsioadwti oeinlnlvtiornalvitnehdeed erexbspeufeolrtrisee,nce  only two inspectors were allowed to analyze and detect reject parts. Figure 2 illustrates the conceptual framework on the relationship between independent variables and a dependent variable. ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 97

inspection.  To  avoid  variation  in  the  results,  only  two  inspectors  were  allowed  to  analyze  and  detect  reject  parts.  Figure  2  illustrates  the Jocuornnacleopf tAudaval nfcreadmMeawnuofarcktu roinng tTheech rneolloagtyionship between independent variables  and a dependent variable.    FigurFeig2u: Treh 2e: CTohnec CepotnucaelpFturaaml Ferwamorekwork 22..33         DDeessiiggnn ooff eexxppeerriimmeenntt In this experiment, full factorial design was used to study the effectoInf  thrise eexinpdereipmeenndte, nftulvla  fraiacbtolerisa.l Adsestihgen nwuamsb  uerseodf  tfoa csttourdsyi ntchree aesfefes,ct  of therene uimndbepr eonfdreunnts  vreaqriuaibreleds.f oAr sa  tchoem  pnluemtebreerp  loicf atfiaocntoorsf tihnecrdeeassiegsn,  the onutmgrboewr osft hruenress roeuqrucierseodf ftohre ae xcpomerpimleetne tr[e5p]l.iHcaetniocne, oitf itshper dacetsiicganl  toouutsgerows ftuhell  fraecstoourriaclesd eosfi gtnhew  hexepnelreisms etnhta n[5f]i.v eHfeanctcoer, s aitr eisb epinragcitnicvael sttiog autesed  full [f2a]c.toTrhiaisl deexspiegrni mwehnetnw leasss dtheasing nfievde ftaoctuosres aarfeu blleifnagct oinrviaelstdigesaitgend t[h2]a.t This hocSatehoxrrtigarrnpeaenhseqendi.r sugaiftWmreieadvmdceiattOnleohoetnrrn fdsttwt.,het  rhaitEasorsw ae fac8edhuhreirtlf clsraah heincgfaatagwnstocem eratmtdsowse. rendotiEnato eatl lcv ,ceuodehvasmleeeohs lfbpsiuaagi e snlwndlfaut hftwblwailioy ccoonfthaoFusl cre.rlwtidavToan eelrhrlknisieades lYeew lsasdodtihtwu egeis2dsnc i3hyag[ w6nonwu]dr os tae uheehrsdlaqeidatgu tlhihcomnvo.ewe aneWelYtsedhaainisnotttt2ehdd es3 dttoh  oi8sf   toregatemneernatt ecoemxpbeinriamtieonntsa.l  Tdheissi gsntusdiny ausceodn stihsete  Yntataens dStlaongdiacradl fOasrdheiro nw..hich Dweassi gdnevmealotrpiexdi nbyTa  Fbrlaen2ks hYoawtes t[h6e]  a2s3 faa cmtoertihaol d etsoi ggnesnweriathte treexaptemriemntental cdoemsigbninsa itnio an csoinsYisatteen’st aonrde lro.gical fashion.. Design matrix in Table 2 shows the 23 factorial designs with treatment combinations in Yate’s order.   Table 2: Design matrix for 23 full factorial design Table 2: Design matrix for 23  full factorial design  Factors Standard  (Factor A) (Factor B) (Factor C)  Order  Hot COT  Brightener correction  Nickel Plating solution Temperature  1  2  solution Density   Temperature   (⁰C)  3  50  4  (BCS) (g/L)   (⁰C)  50  5  50  6  17  52  50  60  22  52  60  17  58  22  58  17  52  22  52 Pilot experiment was done simulataneously as the conduct of replicate1. The purpose of the pilot test was to verify problems that might appearduring the experimental run. This was accomplished by running98 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Minimizing Number of Defects in Nickel Plating Process Using Factorial Designdifferent random numbers. When the problems were solved, the realexperiment could be further conducted on replicate 2 and replicate 3.In this experiment, ANOVA was applied to identify the most significantvariables that influenced the result. This statistical analysis was thenapplied to the experimental results in order to determine the percentcontribution of each factor and factor interactions [6]. This analysis alsohelped to determine factors which needed to be controlled and not becontrolled.3.0 RESULTS3.1 Parameter ScreeningA visual inspection on the number of defects after the plating processshows different response from different treatment combinations. Table3 presents the percentage of defect products for three replication. Table 3: Full Factorial Experimental ResultsAccording to the results, run order number 3 in replicate 1 producedthe highest percentage of defect which was 48.5%. Run order number3 was a combination of 17 g/l of BCS, 58°C of Nickle Plating SolutionTemperature and 50°C of Hot COT Temperature. The run ordernumber 4 in replicate 3 produced the lowest percentage of defect whichwas 2.63%. Run order number 4 involved 22 g/l of BCS, 58°C of NickleISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 99

and 50°C of Hot COT Temperature. The run order number 4 in replicate 3 produced  the  lowest  percentage  of  defect  which  was  2.63%.  Run  order number  4  involved  22  g/l  of  BCS,  58°C  of    Nickle  Plating  Solution TJeomurnpaelroaf tAudrvea nacenddM  a5n0u°fCac tuorfi nHg Toetc hCnoOloTgy  Temperature.  In  order  to  know  the significant  factor  of  the  model,  the  data  were  analyzed  using  Design ExPpleartitn  gsoSftowluatrieo n toT emdepteerramtuinree  atnhde  5a0n°Calyosfis Hooft  CvOarTianTceem  p(AerNatOuVreA. ), regInreossridoenr mtoodkenlo awndt hgeraspighniciafilc danataf. actor of the model, the data were  analyzed using Design Expert software to determine the analysis of3.2v arianceH(AalNf ONVoArm),arle gPrloest sion model and graphical data.Fig3.u2r e 3 sHhoawlf sN tohrem reasluPlltointg plot generated by Design Expert software for nuFmigbuerre  3ofs hdoewfescth  eproesduulctitns gwpiltoht gaelnl ebraigte  defbfeycDts esieglnecEtexdp eartccsoorfdtwinagr eto hieforar rncuhmy.b Ienr tohfisd pefloect,t fpivroed ouf ctthsew eiftfhecatlsl  b(Big, Cef,f eAcBts, sBeCle acntedd AacBcCo)r dfeinllg otno or clohsiee rtaor cthhye .lIinneth. iOs np ltoht,ef icvoenotrfathrye, etfhfeec etsff(eBc,tCs ,oAf BA, BaCnda nAdCA wBCer)ef erlelloantivorely Tsehclspieelnaorpreesaa.feortTetarodhtee,e t dfhrbreeooffrmltoiohnr m eete,h.fOebtfhe onocettthtshoh etesehrfh cfeoeeorfcunfteletsdfrcfa stebshrc.ye otTs ,ua.thhlsTdesehyube,em feyofee,bacdovst sbisaouvosumi fossAeliuygdsa,nl nyadifds,iidcdAsa iinngCdotn wtnif faofieacctrlatelfon arortlesnll.f a aotItchnnitve otoe rhlltsiyhen. eer.  woInrdost,h  ebrowtho  rfdasc,tobrost hAfa catonrds  AAaCn  dwAerCe wiemrepoimrtapnotr taanntda nndeendeeedd edtot obe inbveesitnigvaetsetdig aantedd aannadlyzaenda lfyuzretdhefru trot hseere thoowse ethheoyw intfhlueeynicnefdlu tehnec reedsptohnese ofr veasprioanbslee noaf mvaerliya bthlee nnaummeblyert hofe dneufmecbtse.r  of defects.   Figure 3: Half‐normal Plot Effects for Number of Defects Figure 3: Half‐normal Plot Effects for Number of Defects 3.3 Analysis of Variance  Analysis of variance was applied to confirm which factors and theirinteraction contributed significantly to the number of defects. Figure 4demonstrates the ANOVA summary for each factor that consists of BCSdensity, nickel plating solution temperature, hot COT temperature andall interactions among the factors.100 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

interaction  contributed  significantly  to  the  number  of  defects.  Figure  4 demonstrates  the  ANOVA  summary  for  each  factor  that  consists  of  BCS density, nickel plating solution temperature, hot COT temperature and all interactions amoMningi mthizien gfaNcutmobresr.o f Defects in Nickel Plating Process Using Factorial DesignFigure 4: ANOVA result for Number of Defects (all big effects selected) Figure 4: ANOVA result for Number of Defects (all big effects selected) “Prob>F” often reported on a scale  from 0 to 1. If the p‐value was“lePsrsobth>aFn” o0.f0te5n, rtehpeonr,ttehde ofna cat osrcahlea sfrsoimgn 0if itcoa n1.t Ief ftfheect po‐vnatlhuee rweasps olenssse t,han 0lvpwe.ar0aiolt5suhvt  e,i9 pdot5‐hifv%ne0agn .lc0u,ao 3ettn6hlof3eeifdaw  0fseae.tn0cr91tte 5o1fs%ro6i grha cnanaoilsdfnl i cfsrAiaeidgCsnenutn(ilsBfttiisnCcf oa[cS5nre]atab.  nloIeldnftrfh Heethoscoutifs tlpo tCc‐snavO [sa5teThl]u,.e TAeI enrw me(tBsehpprCieeosSrnlc)ae satswesus,eir tt,pehhA)ra owpn(v‐Bi0vitCd.ha0iSl5npu).ge  oaft  0E.v01e1n6t haonudg  hACA C(BwCaSs  asnigdn iHficoat nCt,OthTe  TmeaminpefaracttuorreC) wwaitshn  po tvsaigluneif iocfa n0t.0. 363 were significant since both of p‐value were less than 0.05. Even though AC w3.a4s  signRiefigcraensts, itohne Mmaoidne flactor C was not significant.  3Ithn.4e ardedgirteiossnRioetongrcgeorsaesfpifoihcniic eManltoa. dAneacllcy osrids,inreggtroetshsieornesaunlatslyosfisAwNaOsVuAseidn to find Figure 6, two factors (A and AC) were statistically significant (p‐value < 0.05).IHn oawdedviteiro,nt otom graainpthaiicnalh aienraalrycshisy,, rfeagcrteosrsiCons haonualydsibse winasc lusdeedd ttoo fitnhde the rmegordeesls.iTonh ecroeeffofricei,etnhte. Arecgcroersdsionng mtoo tdhel riensutelrtsm osf oAf NcoOdVedAf ianc tFoirgsuirse 6, two  factors (A and AC) were statistically significant (p‐value < 0.05).  However, tYo =m20a.i0n2ta–in5 .4h0ieXr1a–rc2h.y43,  Xfa3c+to4r. 36  CX 1Xs3h.ould  be  included  to  the  model.  Therefore, the regression model in terms of coded factors is   WY ihsetrheebyn,umber of defects,YX 1= i s20th.0e2b –r i5g.4h0te Xn1e –r 2co.4r3r eXc3t i+o n4.3s6o lXut1Xio3n.   (BCS) density (g/L), X3 is the hot COT temperature (⁰C)According to the regression coefficient above, the number of defect waslow if the BCS was at the high level (+1) and Hot COT was at the lowlevel (‐1) which produced the total number of defects of 12.69%.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 101

According  to  the  regression  coefficient  above,  the  number  of  defect  was  low if the BCS was at the high level (+1) and Hot COT was at the low level  (‐1) which produced the total number of defects of 12.69%.   Jo urnal of Advanced Manufacturing Technology 3.5  Model Validation (Residual Analysis)  3  .5 Model Validation (Residual Analysis) RReessiidduuaall iiss aad  disicsrcerpepanancycyb  ebtewtweeenenth  tehpe repdreicdteicdtevda lvuaeluaen danthde  tahcetu  aacl tual  (observed) value [2]. Figure 5 shows the Normal Plot of Residual.     It  iiss  eesssseennttiiaall to  tod iadginagonseosteh ethree sirdesuiadlus aalsn danvda livdaltiedatthee  tshtea tistaictaisltical  aassssuummppttiioonn ffrroomm nnoorrmmaall lliinnee.. AAccccoorrddiinngg ttoo tthhee FFiigguurree 55,, tthhee rreessuullttiinngg plot  ipsl oatppisroaxpipmraotxeilmy alitneleyarl.i nTehaer .pTlohte shpolowt esdh onwo eadbnnoormabanliotirems aalnitdie sthaenred was  nntdshaooeetvr irmssieafiigatewinldoistany stso ha.nfes osanunsomiyrg mpnptsairolooinbtfy lbeaemancsya suuinpsm reotp htbhtiilseoe rmnde abwitneaac.s at Thunihsosee srditegahfntoeairr.feei,Tc wahtnheaters e dnfdeooavrtieaas,i tgitsohnanetifissi.dcf aiaentdat  the                            FigFuirgeu5r:eN 5o: Nrmoarml Pallo Pt looft Roef sRideusiadlual    3.6 The Optimum Setting of Parameters O3.6n e factorTphleo tOwpatismuusemd Stoetptirnegs eonft Ptahreamaeitneresf fect plot of the result.JournaF l oifg Audrvean6ceds hMoawnusfactthuerinmg TaeinchnEoflofgeyct Plot for BCS. The number of defects Ownoeu ldfacbteorre  pdluocte  dwwash  eunsetdh etoB CpSrewseansts etthfeo rmhaiignh .effect  plot  of  the  result.    Figure 6 shows the main Effect Plot for BCS. The number of defects would    be reduced when the BCS was set for high.                   FFiigguurree 66:: MMaaiinn EEffffeecctt PPlloott ffoorr BBCCSS  Furthermore,  the  highest  number  of  defects  (25.42%)  was  achieved  when  B10C2S  was at 17IS SgN/L: .1 9T8h5-e3n1 5t7he grVaopl.h1 0starNtoe.d1 toJa dnueacrryea- sJuen teo2 l0o1w6 er level which  was  14.63%, when BCS  was at 22 g/L. Hence, the optimal condition was  achieved when BCS was set at 22g/L.  

   MinFiimgiuzirneg N6:u Mmbaerinof EDfeffeecctst iPnlNoitc kfeolrP BlaCtinSg Process Using Factorial DesignFuFruthrtehremrmoroer, et,heth  heighhigeshte  sntumnubmerb  oerf  doef fedcetfse c(2ts5.4(225%.4)2  w%a) sw  aacshiaevchedie vwehden BCwSh  ewnaBs CatS 1w7 ags/La.t T1h7eng /tLh.eT ghreanphth setagrrteadp htos dtaerctreedastoe tdoe lcorweaesre letovello wwherich walesv  e1l4w.6h3%ich, wwhaesn1 4B.C63S%  w, wash aetn 2B2C gS/Lw. aHseantc2e2, tgh/eL .oHpteimncael, ctohnedoiptitoimn awlas acchoienvdeitdio wnhwenas BaCchS iwevaesd sewt haet n22BgC/LS.w   as set at 22g/L.     Figure 7 : Interaction Plot of BCS and Hot COT Temperature Vs Figure 7 : Interaction Plot Nofu BmCbSe arnodf  DHeofte CctOT Temperature Vs Number of   Defect  According to Figure 7, an interaction  exists between BCS and Hot COTAcTceomrdpienrga ttuor eF.Tighuertew  7o, lain eisnotevrearcltaipopne  edxwististh  beeatcwheoenth eBrC,iSn daincadt iHngot hCaOt T Tetmhepreersautultrefr.Tohme otwneo flaincteosr owvearslainpfplueedn wceidthb eyacahn ootthheerr,fiancdtiocra.tiFnrgo mthatht ethe reisnutlet rafcrtoimon  polnoet , tfhacetolorw  wesatsn  uinmflbueernocfedd efbeyc t acnouotlhdebr e faacchtoierv. eFdrwomhe  nthe intctheorenatcBrtaCiroSyn, wpthaloesth,2 2itghghe/e Llsotw(nheuigsmth nb) euarmnodbfetdhr eeofefh cdotset foCeccOct uTcroewudaldws b5h0ee na⁰Ccthh(ieleovBweCd)S. wOwhnaestnh1 7ethe BCgS/L w(laosw 2)2 agn/dL t(hheighho)t aCnOd Tthwe ahso5t 0C⁰OCT( hwigahs )5. 0 ⁰C (low).  On the contrary, the highest number of defects occured when the BCS was 17 g/L (low) and thIef hthote sCeOoTp twimasu 5m0 ⁰vCa l(uheisghw).e  r e inserted into the regression coefficient model Y = 20.02 – 5.40 X1 – 2.43 X3 + 4.36 X1X3.., the lowest number of defects would be achieved, which was 12.69%, when X1 was replaced by +1 (high level) and X3 was replaced by ‐1 (low level). In this study, confirmation run was conducted using these optimum values to see the difference. Within two weeks, there was a reduction in the number of defects. However the production cost also increased because the new setting required high quantity of BCS compared to the usual production run and the cost to buy the BCS was quite high. For manufacturing firm, producing good quality of product is important to comply with customer requirement. However, they also need to make sure that the production cost does not exceed the budgetISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 103

Journal of Advanced Manufacturing Technologybecause their target is to reduce number of defects without increasingthe production cost. Therefore it is hard to continue using the newsetting if it may affect the production cost in the long term unless theycan find very cheap raw material compared to the current usage. Inthis case, pre and post comparison cannot be made because the numberof defects is analyzed every month and the confirmation run for thisstudy can only be carried out for 2 weeks.4.0 CONCLUSIONSIn conclusion, an interaction occurs between the two factors whichshows that the combination of high level of BCS with the low level hotCOT temperature can reduce the number of defects in nickel platingprocess. In short term, this project has achieved its objectives which is tounderstand the problem magnitude, the source of the problem, analyzethe factors involved and find the optimal setting that can solve theproblem. Basically, two parameters are identified as having significanteffect in reducing the number of defects in nickel plating process.However, the data collected in the confirmation run are considered asa short term capability. Due to the cost limitation, the company cannotproceed with the new process setting at the longer period of time.This study is limited in terms of the number of factors involved asonly three factors are allowed to be investigated because the companydoes not want to take a risk by adding other factors that may affect theproduction process. In order to get accurate results, all the factors orinput of the process should undergo the screening experiment to seewhich factors have important effect to the number of defects. Once themajor factors that affect the process have been identified, more complexor multi‐level design experiment can be used to identify the optimalsettings. For further improvement, the company should take a risk toconsider more factors for the experiment. When screening process isdone, the interaction of all factors involved can be known. This willfacilitate the next phase which is to find the optimal results usingResponse Surface Methodology so that better and accurate output canbe achieved.104 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Minimizing Number of Defects in Nickel Plating Process Using Factorial DesignACKNOWLEDGMENTSThe authors extend sincere thanks to the Universiti Teknikal MalaysiaMelaka for a continuous support for this study.REFERENCES[1] F.Dobslaw, ʺAn Experimental Study on Robust Parameter Settings.ʺ Proceedings of the 12th Annual Conference Companion on Genetic and Evolutionary Computation, pp. 1999‐2002, 2010.[2] D. C. Montgomery, Design and Analysis of Experiments, 8th Edition, New York: John Wiley & Sons, 2012.[3] L. T. Ek., “Quality Improvement Using Factorial Design”. 9th Int Convention on Quality Improvement. Karachi, Pakistan, pp. 14‐15, 2005.[4] N.Manouselisand C.Costopoulou. ʺQuality in Metadata: A Schema for e‐ Commerce.ʺ Online Information Review 30, No. 3, pp.217‐37, 2006.[5] M.J. Anderson, P.J Whitcomb,. DOE Smplified: Practical Tools for Effective Experimentation 2nd Edition. Productivity Press: New York, 2007.[6] F.Yates, Experimental Design: Selected Papers. Griffin: London, 1970.[7] A. Piratelli‐Filho and B.D. Giacomo.ʺApplication of Design of Experiment Techniques to Estimate CMM Measurement Uncertainty.ʺ Proceedings of American Society for Precision Engineering—ASPE Annual Meeting, Scottsdale,. 2000.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 105

Investigation of Forces, Power and Surface Roughness in Hard Turning with Mixed Ceramic Tool INVESTIGATION OF FORCES, POWER AND SURFACE ROUGHNESS IN HARD TURNING WITH MIXED CERAMIC TOOL B., Varaprasad1 and R. C., Srinivasa2 1Faculty of Mechanical Engineering, GVP School of Engineering (Technical Campus), Rushikonda, Visakhapatnam, India. 2Faculty of Mechanical Engineering, Andhra University, College of Engineering (A), Visakhapatnam, India. Email: *[email protected]; [email protected]: Hard turning has been explored as an alternative to cylindricalgrinding used in manufacturing parts made of tool steels. In the present study,the effects of cutting speed, feed rate and Depth of Cut (DOC) on cutting force,specific cutting force, power and surface roughness in the hard turning wereexperimentally investigated. Experiments were carried out using mixed ceramic(Al₂O₃ + TiC) cutting tool having nose radius of 0.8mm, in turning operationson AISI D3 tool steel, heat treated to a hardness of 62 HRC. Response SurfaceMethodology (RSM) based Central Composite Design (CCD) in Design ofExperiments (DOE), was adopted in deciding the number of experiments (20)to be performed with various combinations of input parameters. The rangeof each one of the three parameters was set at three different levels; namelylow, medium and high. The validity of the model was checked by Analysis ofVariance (ANOVA). The results yielded that most favorable parameter settingfor superior surface finish was acquired at a medium speed of cutting (155 m/min), medium feed (0.075 mm/rev) and low DOC (0.3mm).KEYWORDS: Hard turning, Specific cutting force, Surface roughness, AISI D3 andMixed ceramic.1.0 INTRODUCTIONHard turning is the process of machining hardened steels where thevalue lies between 45 – 68 HRC (Rockwell hardness) with the latestcutting tools i.e., Poly‐crystalline Diamond (PCD), Cubic Boron Nitride(CBN), Poly‐crystalline Cubic Boron Nitride (PCBN), Chemical VaporDeposition (CVD) and Physical Vapor Deposition (PVD) Coated toolsand Ceramics. Finishing operation like grinding requires many setups,hard turning is the best option to replace grinding and has severalbenefits such as coolant elimination, reduced cost of production,enhancement of material properties, reduction in power consumptionISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 107

Journal of Advanced Manufacturing Technologyand productivity. Ceramic tools are generally used as an alternative toCBN in the manufacturing sector for machining of hard materials suchas alloy steels; bearing steels, die steels, graphite cast iron, high‐speedsteels and white cast iron [1‐5]. Therefore hard turning is considered asan alternative process to grinding in a bid to reduce the setup changes,setup cost, setup time, process flexibility, compatible performancecharacteristics and higher material removal rate and less environmentalproblems.Various studies have been conducted to investigate the performanceof CBN tool in the machining of tool steels. Bouacha et al. [6] examineeffect of cutting parameters on cutting parameters on cutting forceand surface roughness in hard turning of AISI 52100 with CBN toolusing response surface methodology. The results show that the surfaceroughness is influenced by feed rate and cutting speed. Aouici et al.[7] conduct extensive experiments on AISI D3 cold steel with mixedCeramic CC 6050 (with a tool nose radius 0.8 mm, chamfered insert 0.1mm × 20°), hence, the surface roughness is strongly influenced by thefeed rate (87.334 %) and followed by square of feed rate (6.455 %). Thesurface finish has improved as speed of cutting increases to an extentof 5.03% and deteriorates with the feed rate of 36.672 followed by DOC(27.541%). Initially, cutting force enhances with an increase in feed rateand DOC and reduces with an increase in cutting speed. The lesseningin the forces is probably due to temperature increase in the shear planearea, which resulted in the drop in shear strength of the material.The experimental studies conducted byAouici et al. [8] yield that the feedforce and tangential force are strongly influenced by DOC and cuttingspeed has negligible influence on these forces while the machining ofAISI H11 hardened steels (40, 45, and 50 HRC) is using CBN 7020. Al‐Ahmari [9] present empirical models for surface roughness and cuttingforce in turning operation. The process parameters namely speed, feed,DOC and nose radius are used to develop the machinability model. Twomethods used for developing aforesaid models are RSM and NeuralNetworks (NN). The effect of cutting conditions in a hard turningoperation is analyzed by Dilbag and Venkateswara [10]. El Wardany etal. [11] study the quality and integrity of the surface produced duringhigh speed turning of AISI D2 cold work tool steel in its hardened state(60 ‐ 62 HRC) using CBN tool. Kirby et al. [12] predict surface roughnessin turning operation using different prediction models. A regressionmodel is developed by a single cutting parameter and vibrations alongthree axes are chosen for in process surface roughness predictionsystem. Linear relationship among the parameters and the response iscarried out using multiple regression and ANOVA. The results reveal108 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Investigation of Forces, Power and Surface Roughness in Hard Turning with Mixed Ceramic Toolthat for attaining an effective surface roughness prediction model, thecutting speed and DOC may not be necessarily fixed.Horng et al. [13] present a model by applying RSM and ANOVAtechniques to evaluate the machinability of Hadfield steel. Aouici et al.[14] conduct experiments on machining of X38CrMoV5‐1 steel treatedat 50 HRC by a CBN7020 tool to reveal the influence of the followingcutting parameters: cutting speed, feed rate and DOC on surfaceroughness. They conclude that the surface roughness is sensitive tothe variation of feed. Kribes et al. [15] present a statistical analysisto study the influence of cutting conditions on surface roughness inhard turning of 42CrMo4 steel using coated mixed ceramic inserts.Doniavi et al. [16] apply RSM in order to develop empirical model forthe prediction of surface roughness by deciding the optimum cuttingcondition in turning. It is reported that the feed rate influences surfaceroughness remarkably. With the increase in the feed rate, surfaceroughness increases. ANOVA results show that feed and speed havemore influence on surface roughness than DOC.Quiza et al. [17] predict ceramic cutting tool wear in hard machining ofAISI D2 steel using NN. The models are adjusted to predict tool wearfor different values of cutting speed, feed rate, and machining time.One of them is based on statistical regression and the other is basedon a multilayer perception neural network. The NN model has a betterperformance than the regression model in its ability to make accuratepredictions of tool wear. Neseli et al. [18] use RSM to optimize the effectof tool geometry parameters on surface roughness in hard turning ofAISI 1040 with P25 tool. Gaitonde VN et al. [19] conduct experimentsto analyze the effects of DOC and machining time on machinabilityaspects such as machining force, power, specific cutting force, surfaceroughness, and tool wear during turning of AISI D2 cold work toolsteel using traditional and wiper ceramic inserts.The present work investigate the influence of process parameters inhard turning of AISI D3 cold work tool steel (62 HRC) using mixedceramic tool insert (CC6050) on specific cutting force, power andsurface roughness. A little work is reported so far in the literature forthis combination of tool and work piece material.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 109

JoJouurnrnaal loof fAAddvvanancecded MMananuufafcatcuturirninggTTecehcnhnoloolgoygy  22..00        EEXXPPEERRIIMENT PROOCCEEDDUURREE   TThhee  wwoorrkk  ppiieeccee  material  used  for experimentation was AAIISSII DD33 sstteeeell..  TThhee ccirirccuulalarr bbaarr ooff ddiiaammeetteerr 7700 mmmm x 360 mm long was  pprreeppaarreedd.. TTeesstt  ssaammpplele wwaass ttrruueedd,, cceenntteerreedd aanndd cleaned by removing a  2  mmmm ddeepptthh ooff  ccuut tfrfroomm ththee oouutstsididee ssuurrfafaccee, ,pprrioiorr toto aacctutuaal lmmaacchhinininingg tetesststs. .    22.1.1 MMaateterriaial,l ,wwoorrkk ppieieccee aanndd totoool l  DDuuee  ttoo  its hhiigghhw  weeaarrr erseissitsatnancec,eA,  AISIISDI 3Dm3 amteartiearliiaslu  isu  uaslluyaellmy pelmoypeldoyfoerd  fothre  tmhea numfacntuufraectoufrbel aonfk inbgla;ndkrianwg;i ngdrdaiwesi,npgu  ndcihese,s , proulnlecrhseps,r orfoillelresr,s  psrtoafmileprisn,g  satnamd pwinogo datnodo lswaonodd otohoerls . aAndn ewothinersse.r tAw anseewm  pinloseyretd  wfoars  eemacphloryuendo foerx peaercihm reunnts oinf eoxrpderitmo epnrotsv ind eocrodmerp tleot eplryoivdiednet iccoaml cpultetitnelgy  idedengteiccaoln  dciutitotinnsgf oredegaech  cteosnt.dTithioencs hefmori cael accohm  ptoesti.t ioTnhoef  thcheewmoicrkal  cpoimecpeomsitaitoenr iaolf itshge ivweonrkin  pTieacbele  m1.atTehriealw  ios rgkivpeienc einw  Taasbhlee a1t. tTrehaet ewdotrok  paitetcaein w6a2sH hReaCt .tTrehaetepdr otcoe assttoaifnh 6e2a tHtrReaCt.m Tehnet pwraosceasssf olfl ohweast, trheeatwmoernkt  wpaiesc aesw foalsloowil‐sq, utheen cwhoedrkf rpoiemce9 w80aᵒsC ofiol‐lqlouwenedchbeyd tferommp e9r8in0gᵒCa fto2ll0o0woCed.   bIyts  themarpdenreisnsgv  aatl u2e00woCas.  Imtse  ahnarodfntehsrse  evarleuaed  iwnags  mtakeaen aotf tthhrreeee dreifafedrienngts  talokceant ioant sthorneet hdeifmfearcehnitn  leodcastuiorfnasc eo.nF itghuer em1acshhionweds  tshuerfeaxcpe.e rFiimguenreta  l1  ssheotwups. the experimental setup.    Table 1: Chemical composition of AISI D3 (wt %)  C Si Mn P S Cr Ni Mo Al Cu Zn Fe 2.06 0.55 0.449 0.036 0.056 11.09 0.277 0.207 0.0034 0.13 0.27 Balance                        FFigiguurree1 1::E Exxppeerrimimeennttaalls seettuupp  TThhee tteessttss oonn tthhee work piece were conducted  under  ddrryy eennvviirroonnmmeenntt oonn  tthhee  llaatthhee  KKiirrlloosskkaarr;;  mmooddeell  Turn  Master‐35, spindle  ppoowweerr 66..66KKWW.. TThhee  ccuutttiinngg  ffoorrcceess  were  measured  by  Kistler  ppiieezzooeelleeccttrriicc ddyynnaammoommeetteerr  ((mmooddeell  99225577BB))..T  hTishdisy  ndaymnoammeotmerectaern  mcaenas  umreefaosrucrees infotrhcreese  minu tutharlleye  mpeurtpueanlldyi cpuelraprednidreiccutiloanr sdii.ree.cFtixo,nFsy  i(.e0. tFox,5 0F0y 0(N0 )toa n5d00F0zN(0)  atond1 0F0z0 0(0N  t)o.   K1Tca0hich0sqate0ulr0egciNrshe iac)ta.ihr omgTanehrpgesgle yiecf sinhaetmeaerrrmpag(mteleic fdgooiedenarnes teil(stmrt5has0oete7oddd0feyA laa n)t5.a p0tmThe7erh0os Aedmoy)nse.n iatgTleanhrmcaeowlo msmawispgeaunatseamterla  rpcwwqlaiaaufsissie c radaoemcdnbqptyurbloiiyafrlileeeKaddri ds babtanylyet d araa   data  acquisition  system  consists  of  a  personal  computer  as  controller   110 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Investigation of Forces, Power and Surface Roughness in Hard Turning with Mixed Ceramic Toolcable for PC to charge amplifier connection. The Dyno ware softwareinstalled in the PC acquires the force data generated during turningin all three directions. The average value of this force data was usedfor further analysis. Surface roughness was measured using MitutoyoSurftest SJ 210 with measuring range of 17.5mm and skid force less than400mN. The sample length was 0.8 mm. Average of four readings ofsurface roughness was recorded on different places of sample surface.These values were obtained without disturbing the assembly of thework piece in order to reduce uncertainties.The cutting tool used for machining was mixed ceramic tool designatedas SNGA 120408 T01020 (Sandvik make) that is CC6050. The high hot‐hardness and the good level of toughness make the grade suitable asthe first choice for hardened steel (50 – 65HRC) in applications withgood stability or with light interrupted cuts. Commercial tool holderdesignated as PSBNR 2525 M 12 (ISO) with the geometry of active partcharacterized by the following angles: χ = 75°; α = 6°; γ = −6°; λ = −6°.2.2 Experiments DesignRSM is a DOE technique used to optimize the number of experimentsbased on the number of process parameters and their levels onperformance characteristics. The RSM is useful for emerging, refiningand optimizing the processes, which provides an overall perceptionof the system outputs within the design space [20]. In order to knowperformance characteristics in advance, it is necessary to employempirical models making it feasible to do predictions as a function ofoperational conditions. Using DOE and applying the regression analysis,the modelling of the desired output against several independent processparameters can be obtained. The RSM is exploited to designate andidentify the impact of interactions of different process parameters onthe performance characteristics when these are varied simultaneously.In the present investigation, the second‐order RSM based mathematicalmodels for surface roughness (Ra) is developed with cutting speed (Vc),feed rate (f), and DOC (ap) as the process parameters. Figure 2 shows aflow diagram of methodology adopted for the present work.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 111

Journal of Advanced Manufacturing Technology   Journal of Advanced Manufacturing Technology Jo Juorunranla olf oAf dAvdavnacnecde Md ManaunfuacfatuctruinrignTgeTchecnhonloogloygy  Figure 2: Proposed methodology    WIcpthna   tc IppWdpWcIptrhnhne naaeh   rooret een sn eh ehhepIcWptvwwttbdeh nsshar    eheeeordbbedneeeeeee nrehre lew teeensn crtoeer ers h e Yisc, ub,dset cetprer reiYu Yiiuep rneeereenr isirri spe,pds rrc etdnsrn vpeirp iYriedudre sr esv rnveeeseetiesrp r e nwenhsntceterpecssirtrdrh tstsienhsveeieetseseieiftf   etspgns tnnitteesicisstirhcpouegtcpgah stoiettteoudf e ou ueotadtanoensisuididdsut cntdptgy cottnsbi pptiu youe tsoueay,poonbsbyF Fp uede,utd nte,tctnnu,yiy tie iutat ht  gtg uiy,ots,baih  td pnn a hutte unea,tnny heFt  gaunt drter gnaht,iqd iheeoen a h tdq n g ndeq u  efdni2 2teuu gfaid n uh Rfa:o:ni dr∅a n Rocn dqØPnRePaerS d nu∅rd dS uc nfretriMS2c iettooi one MpisReati:ettMpis∅p rpit aidpsn eP tSacn teo o tatne ahebtreMtini tghsabsiotipvnsndhba eteeivdn(eap ave  eddsdaeed teasdeoate ne hnsbae eifn nmmsc dafe vdcnoaetdeofksdtc d k e seoreetsdur kin, a emit n atunnr  manhrfh inomcdmlaoforntspflogok powe afg luworepudodgae  ineuwcmeatrnoflubcoftoedhle o etbfl efpeltlbrlgtao tdw eporohdp o hautcrdea dgggprrheifgarelebtoiroc oy ey gmo r cei motrl rurcdocapmoch aeue emerr ncgegegmreilleonsgemecsoan dhyam olsunss tohrtcattn   odsieigetdment pofDopef  ld iensuheuea  ponfsnaao ls Oeutlnnsts  snnrsars s  d lis n ace ahC shpofrcs    eut ms  afmcth hin fia  i loipsp ot mnhof siroas  i  eorep   r a oncahv n  bb tter   t mhvfne.ie e .  bceeitc o p  roaere (. uI ttuIcee r s1 s nw wrvna( uIt tbbt t) s1nws teet. [[ (btceeee  i )it t221 r t(nnuI[ hteeheeeistt100)2nwngnnnheghbteee )]]0 tng[   n  eeeeit]2ne   h e  0ngne]      adpcdp[a foe2atcvaewi4ctoadfvreit]aeaocnloeeoicrmtln rvs,itopps oo eeap epanlr[stcode2srea pcda p4 pru[ems]a2weawcs .md4irtiesiTfo]ai t tit ehhammciewhtsc  er eecsisasrtcaptud.psch euc.escTe r bkttueeTshstoyndi.sdphe nmotT e oeogwaoee hfm caddflcek ecfe  u bodcknadotuyrngotcf cibt k mownetycniwg nleu oe(nlgatVwdettn(idgcnlda)egm,gp dmf(pe egsn,eeaum ndtrfr eete fa( nane,fpa ctd)tppfe abeap anelpruaddr epreoaneDpaunntrrg Od etibh nan CblnntuDtl e(dufebOaosp elpsrCupD)r itaernOhhipsntraC rtethvfi enofee ortf a a arsftccb oh  tterthiroaohe erstnneeesh    etrh eee   facto  rs [24] is accustomed by  (2)   W   h  e  r e    Y    i s   d  e  s  i r  e  d   r  e  s  p  o  n   s e   a  n   d    a  0  i s   t  h  e   f r  e  e   t  e r  m     o  f   t h  e    r e(2g)r e  s  sion We  qeT2tqeWai  ne  qh .qunuh   rt   huTeueWadaa  rme    r  qneetadha  r    e  i   eshrauttd  o er     ie i.  qcea  a ono   Yl    l  turte  t   nenY,i    ie  iq vn  a c  voi,,   t    s u  de g  hetniY     t t  slh a   rlhee  d,s   t  s  a  de  e r  ei d  et  t sac  morrh    c  ise   o mra  ccf  oi e  dse   eort      e iv  i,see   f  ercc  f i  .aftds  e rfdf   o ie     riife  dc    erecr  ii   sirt   cae  m ifne  e   epef  ir db  n  tre is  en  s i  clm   pn t  sfe,c  t ir  s i   pse  totee   s  sai   n  nosd,a  rv   r      petns1  , ee  s  ,   sefo  ls r,    oap y  c ee  n     ,2a rh  ,es     ,s  ,  n ,ap  co  we a e     tn  des   a 3  i    h  ,eadcv   c a   a     ntn ih  e  n  iln  a   dlve    da yn di  c  e   ss ,a  udai a l    s yn  1t p1   h t1 2,wdit ei,  s he ,n  ra  ,h   e gwa t2 f,r ih 2  1 rl e,f hv eee3 r ca , i ae e,  o 3l,. f  r 3ee.  mra,…a ti     eae 12 t m ebr e2…3 a, m    rl…, 1 ete  m ae…. 2 n   r…rao ,aa  d  em r… s1…fo  a e . 3af t   tgt  h. ,…at1ho i  .ti ho .er3 avhfe a ene  ., r ee 2 . ti e(rs. nanlh 3ta2 e ir hrt mne2) tgeeie  he 3 en gr ra(ra  e aet 2arelrd h Trsie)ceglane seasti a rrinie  sbneon eblai telsi nodyghernasn  eriteoh   aner     anthdei nctqueutrtaaincdtgrianttgoico t lermtmearsmn. usf, acrteusrpeer.ctTivherelye, vawrihaiblele  s ao1f2c, utati1n3g,..aat2t3h  reaerel evtehles   interacting terms.   112 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

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Journal of Advanced Manufacturing Technology Journal of Advanced Manufacturing Technology  Table 3: Values of cutting forces, power, specific cutting force and Table 3: Values of cutting forces,s puorfwaceer,r sopuegchifnice scsutting force and surface roughness      (µm) Sl. No.   Speed (m/min) Feed (mm/rev) DOC (mm) Specific Cutting Force (kN/mm2) Power P (kW)   1 145 0.050 0.3 106.0 138.0 113.0 7.5333 0.273 1.33   2 165 0.050 0.3 098.0 206.7 102.7 9.6000 0.396 1.88   3 145 0.100 0.3 115.0 242.0 150.0 5.2500 0.381 0.90 4 165 0.100 0.3 122.0 254.1 194.6 6.4866 0.535 0.82  5 145 0.050 0.9 321.5 300.0 289.0 6.4222 0.698 2.06  6 165 0.050 0.9 283.7 325.2 312.1 7.6888 0.951 2.11 7 145 0.100 0.9 341.2 340.0 335.0 3.7222 0.809 1.10  8 165 0.100 0.9 332.0 290.0 280.5 3.1206 0.772 0.91  9 145 0.075 0.6 212.6 279.0 220.0 4.8889 0.531 0.84 10 165 0.075 0.6 228.3 290.7 245.3 5.4511 0.674 0.93  11 155 0.050 0.6 213.1 256.0 216.4 7.2133 0.559 2.27  12 155 0.100 0.6 250.3 325.0 310.5 5.1750 0.802 0.93 13 155 0.075 0.3 104.9 170.0 125.0 5.5555 0.322 1.05  14 155 0.075 0.9 298.5 273.4 263.1 3.8996 0.679 0.83  15 155 0.075 0.6 230.0 284.7 252.2 5.6044 0.651 0.71 16 155 0.075 0.6 235.0 274.0 260.0 5.7777 0.671 0.71  17 155 0.075 0.6 245.0 282.0 258.0 5.7333 0.666 0.73  18 155 0.075 0.6 252.0 278.0 248.0 5.5111 0.640 0.75 19 155 0.075 0.6 253.0 280.0 262.0 5.8222 0.676 0.88  20 155 0.075 0.6 260.0 282.0 255.0 5.6666 0.658 0.92   3.1 Statistical Analysis Tss3T  uhh.h1oreef w a  r rc ee etsShsuruteaolltttudsisgse otohtifafcn iAaleAslsN NsAoOf(OnRVeaVaslA)Aytiasm firfoseoar rtse phpdooowwrweengerrrie (n(PsPsT))i,ao, sbnsplpeececo5cie,iffif7icfcica ccinueudtntttti9nsin..ggTT afhfoboirslrceceae4n (,(aK6lzya)s)n iasadnnid8sd  dsuonrfeacoeu rtofuogr han5es%s (sig)n aifriec asnhcoewlnev ienl ,Tia.eb.l,ef o5r, 7a a9n5d% 9. cToanbfilde e  n4c, e6 laenvdel 8.   AshNoOwV  tAheh  daestabielse nofa  epsptliimedatetod crehgerceksstihoen acdoeeqffuicaiceyntos.f  Tthheis daenvaelylospise dis  mdoondee los.utA fNorO aV 5A %t asbiglenicfiocnasnicsets leovfels,u im.e., ofof rs aq u9a5r e%s caonndfiddeengcree elesvoefl.  fAreNedOoVmA. Thhaes sbuemeno  fapsqpuliaerde stois  cpheercfokr mtheed  aidnetoqucoacnytr iobfu  thioen  sdefrvoemloptheed  pmoolydneolsm.  iAalNmOoVdAel  atanbdleth  ceoenxspisetrsi moef nstaulmv aoluf es. quares  and  degrees  of  freedom. The sum of squares is performed into contributions from the  qPe pquoouwalyadetnrriaootimnisc(iia5mnl)f .olmuTdaoeebndl lcefeeol d5ranPrbedoyp wtrhSeepesr eeePenxdt(psk,eWtDrhimOe).ACeTnNhateaOnlvd VvaAalDuluOetaeCob. fl2e“aPfonrrdobrie.s”speinoxnpTsraeebsslseuerd5fafbocyer mPoowdeelr iiss leinsfslutheannce0d. 0b5yw  Shpiecehds, pDecOifCie santhda  tDtOheC2m  aondde liiss  enxoptreewssoerdth  byy,   weqhuicahtioisn a(5p)p. rToapbrliea t5e raespriet sdeinrtesc ttsheth AaNt tOhVe Ate rtmabslei nfotrh reesmpoodnseel  hsuarvfeacae  mquaajodrreaftfiec cmt oondethl efooru Ptopwute.r P (kW). The value of “Prob.” in Table 5 for  model  is  less  than  0.05  which  specifies  that  the  model  is  noteworthy,  Pwohwiecrh( Pis) =ap0p.6r1o2p4r6ia5t+e 0a.s0 6it3 6d0i5rexctSsp  tehedat+  t0h.e2 0t0er3m86s xinD  tOhCe ‐m0o.0d9e8l1  h5a5vxe  a  DmOajCo2r  effect  on the  outp ut.   (5)   Power (P) = 0.612465 + 0.063605 x Speed + 0.200386 x DOC ‐ 0.098155 x  DOC2                                                                                                             (5)  114 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 

Investigation of Forces, Power and Surface Roughness in Hard Turning with Mixed Ceramic Tool Table 4: Estimated Regression Coefficients for Power (kW)   Term Coef SE Coef T P   Constant 0.612465 0.02408 25.434 0.000  Speed 0.063605 0.02215 2.871 0.017  Feed 0.042165 0.02215 1.904 0.086  DOC 0.200386 0.02215 9.046 0.000  Speed*Speed 0.003540 0.04224 0.084 0.935  Feed*Feed 0.080999 0.04224 1.918 0.084  DOC*DOC - 0.098155 0.04224 -2.324 0.043  Speed*Feed -0.032357 0.02477 -1.307 0.221  Speed*DOC -0.007718 0.02477 -0.312 0.762 Source Feed*DOC -0.039353 0.02477 -1.589 0.143 Regression S = 0.0700472 PRESS = 0.464736 R-Sq = 91.29% R-Sq(pred) =17.46% R-Sq(adj) = 83.44% Table 5: Analysis of Variance for Power (kW)  DF Seq SS Adj SS Adj MS F P %Con Remarks Significant 9 0.513993 0.513993 0.057110 11.64 0.000 Speed 1 0.040456 0.040456 0.040456 8.25 0.017 7 Significant Feed 1 0.017779 0.017779 0.017779 3.62 0.086 3 Insignificant DOC 1 0.401545 0.401545 0.401545 81.84 0.000 72 Significant Speed*Speed 1 0.000228 0.000034 0.000034 0.01 0.935 0 Insignificant Feed*Feed 1 0.006249 0.018042 0.018042 3.68 0.084 1 Insignificant DOC*DOC 1 0.026495 0.026495 0.026495 5.40 0.043 5 Significant Speed*Feed 1 0.008376 0.008376 0.008376 1.71 0.221 2 Insignificant Speed*DOC 1 0.000477 0.000477 0.000477 0.10 0.762 0 Insignificant Feed*DOC 1 0.012389 0.012389 0.012389 2.53 0.143 2 Insignificant Residual Error 10 0.049066 0.049066 0.004907 8 100 Total 19 0.563059           Table 6: Estimated Regression Coefficients for Ks (kN/mm2)  Term Coef SE Coef T P Constant 5.2230 0.1665 31.362 0.000 Speed 0.453 0.1532 2.957 0.014 Feed -1.4704 0.1532 -9.598 0.000 DOC -0.9573 0.1532 -6.249 0.000 Speed*Speed 0.1262 0.2921 0.432 0.675 Feed*Feed 1.1504 0.2921 3.938 0.003 DOC*DOC -0.3164 0.2921 -1.083 0.304 Speed*Feed -0.3374 0.1713 -1.97 0.077 Speed*DOC -0.3299 0.1713 -1.926 0.083 Feed*DOC -0.234 0.1713 -1.366 0.202 S = 0.484431 PRESS = 10.8935 R-Sq = 94.55% R-Sq(pred) = 74.69% R-Sq(adj) = 89.64%    ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 115

Journal of Advanced Manufacturing Technology  JouKrsn a=l o5f.A22dv3a +nc 0ed.4M53an xu faScptuereidn g‐ T1e.c4h7n0ol4o gxy Feed ‐ 0.9573 x DOC + 1.1504 x Feed2                         (6)   K  s = 5.223 + 0.453 x Speed ‐ 1.4704 x Feed ‐ 0.9573 x DOC + 1.1504 x Feed2 (6) From the analysis of Table 7, it can be seen that the Speed, Feed, DOC  Farnodm  Fteheeda2n  halayvseis  soigf nTiafbiclaen7t,  ietffceacnt boen setheen  tshpaetcitfhice  Scpuetteindg,  Ffeoerdc,e D(KOsC).  aSnpdecFifeice dc2uthtianvge  fsoigrcneif iicnacnrteaesfefesc  twoitnh tthhee sipneccriefiacsec uitnt infegedfo  rrcaete( Kasn)d.   SDpOecCif.i cTcaubtltein  9g fsohrocewisn ctrheea sAesNwOiVthAth  teaibnlcer efaosre  riensfpeoendsrea  tseuarnfadceD. OTCh.e  Tmabajloer9 esfhfeocwt osnth seuArfNacOe VroAutgahbnleesfso rforlelsopwosn Fseeesdu r(ffa) caen. dT htheem parjoodr uecffte fc2t.  mo Fneoessdut  ri(mffa) cpieso rrthotaeun gmthfonascetts oismrfoaplfolfoertwcatinsntFg feasecudtro(frfa )caaefnfredocuttihgnehgnp seruosrsdf.auccet rf2o.uFgehende(sfs). i s the SSuurrfafacceer oruoguhgnhensses(sR (aR) =a)0 =.8 051.86541‐604. 4‐9 09.4x9F9e exd F+e0e.d0 6+4 509.016x45F9ee1d 2x  F eed2         ((77))    Table 7: Analysis of Variance for Ks (kN/mm2)  Source DF Seq SS Adj SS Adj MS F P %Con Remarks Regression 9 40.7003 40.7003 4.5223 19.27 0.000 Significant Speed 1 2.0521 2.0521 2.0521 8.74 0.014 5 Significant Feed 1 21.6204 21.6204 21.6204 92.13 0.000 50 Significant DOC 1 9.1642 9.1642 9.1642 39.05 0.000 21 Significant Speed*Speed 1 1.963 0.0438 0.0438 0.19 0.675 5 Insignificant Feed*Feed 1 3.4062 3.6392 3.6392 15.51 0.003 8 Significant DOC*DOC 1 0.2753 0.2753 0.2753 1.17 0.304 1 Insignificant Speed*Feed 1 0.9105 0.9105 0.9105 3.88 0.077 2 Insignificant Speed*DOC 1 0.8705 0.8705 0.8705 3.71 0.202 2 Insignificant Feed*DOC 1 0.4382 0.4382 0.4382 1.87 0.202 1 Insignificant Residual Error 10 2.3467 2.3467 0.2347 5 Total 19 43.047 100   Table 8: Estimated Regression Coefficients for Ra    Term Coef SE Coef T P   Constant 0.85164   0.06381 13.347 0.000     Speed 0.042 0.0587 0.716 0.491     Feed -0.499 0.0587 -8.502 0.000   DOC 0.103 0.0587 1.755 0.110 Speed*Speed -0.06909 0.11193 -0.617 0.551 Feed*Feed 0.64591 0.11193 5.771 0.000 DOC*DOC -0.01441 0.11193 -0.126 0.902 Speed*Feed -0.10875 0.06562 -1.657 0.128 Speed*DOC -0.07625 0.06562 -1.162 0.272 Feed*DOC -0.08375 0.06562 -1.276 0.231 S = 0.185611 PRESS = 2.34923 R-Sq = 93.04% R-Sq(pred) = 52.54% R-Sq(adj) = 86.78%  116 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Investigation of Forces, Power and Surface Roughness in Hard Turning with Mixed Ceramic Tool Table 9: Analysis of Variance for surface roughness  Source DF Seq SS Adj SS Adj MS F P %Con Remarks Regression 9 4.6053 0.000 Significant 4.6053 51170 14.85 Speed 1 0.01764 0.01764 0.01764 0.51 0.491 0 Insignificant Feed 1 2.49001 2.49001 2.49001 72.28 0.000 50 Significant DOC 1 0.10609 0.10609 0.10609 3.08 0.110 2 Insignificant Speed*Speed 1 0.4805 0.01313 0.01313 0.38 0.551 10 Insignificant Feed*Feed 1 1.31328 1.1473 1.1473 33.3 0.000 26 Significant DOC*DOC 1 0.00055 0.00055 0.00055 0.02 0.902 0 Insignificant Speed*Feed 1 0.09461 0.09461 0.09461 2.75 0.128 2 Insignificant Speed*DOC 1 0.04651 0.04651 0.04651 1.35 0.272 1 Insignificant Feed*DOC 1 0.05611 0.05611 0.05611 1.63 0.231 1 Insignificant Residual Error 10 0.34452 0.34452 0.03445 8 Total 19 4.94982 100   FFrroomm tthhee aabboovvee ttaabblleess tthhee R2  vvaalluuee ffoorr PPoowweerr ((PP)),, SSppeecciiffiicc ccuuttttiinngg  ffoorrccee  (Kz )  and  Surface  roughness  (Ra )  iiss 9911..2299%%,, 9944..5555%% aanndd 9933..0044%%  rreessppeeccttiivveellyy..      3.2 Contour Plots P3  o.2w  e  r  ,CSopnetcoifuicr Pculotttisn g force and Surface roughness should be should bPeokweeprt, toSapemciifnicim  cuumttiwngh ilefomrcaec hainnidn gS. Aurnfaacnea  lyrosiusgohfnaellssp esrhfoorumlda ncbee  cshhaorualcdte breis tkicespth atvoe  ab meeinnimcounmdu  wctehdilew  mithacthhineinhgel. pAonf  aconnatlyosuirs polfo  tasl.l  Cpscpoeooefrnnrtfwftotoooraruumrmrrea apfnpnolclcoroeettr sce.hcs shhaCparoooarwnnacstctseoeteruaisrsrui tsdriptcfyilascno.scta Be mhysaahinccvoraewelr yaesbtsp iienasre,e gndst cheyocnenontaoantmotpdiutouiicrnmc ptrueilendompt rstwerhueseiesgthininso ttgantuhtdmiieosy innlh ooieitcfnlaap bttt eh1hod6eef   bsytucdhya roafc ttehreiz  ipnegrfothremsahnacpe echoaf rtahcetesruisrtfiacsc.e .BCy irccruelaatrinsgh acpoendtoucor nptoloutrs  ruespirnegs emntins ithabe1i6n dsoefptewnadren fcoer orefsfpaocntosre esfufrefcatcsea anndaleylslips,t itchael ocopntitmouurms   mreagyioinn disi claotceatfeadc tboyr   icnhtaerraacctteiorinz.inTgh  tehec osnhtaopuer sofo  tfhteh  seurefascpeo. nCseirscualraer  sshhoawpendi ncFoingtuoruers  r3eap, r3ebseantds 3tch.eF rionmdetpheenfdoellnocwe inogf  ffiagcutroers  eitffiescctlse aarnlyd  uenlldipetrisctaolo cdonthtoaut rps omwaeyr iinsdmiciantiem fuacmtoar tinlotewrascptieoend. Tahned cmonetdoiuurms ofef ethde,   mreisnpimonusmes aatrleo wshvoawlune sino fFsipgeuerdesa n3da, D3Ob Canandd  3mc. aFxrimomu mthaet  hfoigllhowfeiendg  afnigduhreigs hitD isO cCle. arly understood that power is minimum at low speed  and  medium  feed,  minimum  at  low  values  of  speed  and  DOC  and  maximum at high feed and high DOC.     ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 117

Journal of Advanced Manufacturing Technology Power(k W ) 1.0Journal of Advanced Manufacturing Technology < 0.3 0.5 0.0  0.3 – 0.4 0.4 – 0.5 1.0 1.0 0.5 – 0.6 0.6 – 0.7 Power(k W ) Power(k W ) > 0.7 < 0.3 < 0.55 0.3 – 0.4 0.5 0.55 – 0.60 0.5 0.4 – 0.5 0.60 – 0.65 0.5 – 0.6 0.6 – 0.7 0.65 – 0.70 0.7 – 0.8 0.70 – 0.75 > 0.8 > 0.75 0.0 0.0B C C -0.5 -0.5 -0.5 -1.0 -1.0 -1.0 -0.5 0.0 -1.0 -0.5 0.0 0.5 1.0 -1.0 0.5 1.0 -1.0 -0.5 0.0 0.5 1.0 A A BFigure 3(a): Power Vs Speed  Figure 3(b): Power Vs Speed  Figure 3(c): Power Vs Feed (A) and Feed (B)  (A) and DOC (C)  (B) and DOC (C)        Figure 4(a): Specific cutting  Figure 4(b): Specific cutting   Figure 4(c): Specific cutting force Vs Speed (A) and Feed  force Vs Speed (A) and DOC force (Ks) Vs Feed (B) and (B)  (C)  DOC (C)       Figure  5(a):  Surface  Figure  5(b):  Surface  Figure 5(c): Surface roughnesroughness  (Ra)  Vs  Speed  roughness  (Ra)  Vs  Speed  (Ra) Vs Feed (B) and DOC (A) and Feed (B)  (A) and DOC (C)  (C)         118 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016

Investigation of Forces, Power and Surface Roughness in Hard Turning with Mixed Ceramic Tool4.0 CONCLUSIONSIn conclusion, few significant findings from the experiments are asfollows;1) The DOC (72%) has the highest physical as well statistical influence on the cutting power followed by Speed (7%) to perform the machining.2) Specific cutting force (Ks) is mostly influenced by feed (50%) followed by DOC (21%), then Feed2 (8%) and speed (5%).3) The surface roughness is strongly influenced by the feed (50%) and followed by feed2 (26%).From the results, most favorable parameter setting for superior surfacefinish is acquired at a medium speed of cutting, medium feed and lowDOC.REFERENCES[1] D. I. Lawarni, N. K. Mehta, and P. K. Jain, “Experimental investigations of cutting parameters influence on cutting forces and surface roughness in finish hard turning of MDN 250 steel,” J. Mater. Process Technol. 209, pp. 1092 – 104, 2009.[2] R. Suresh, S. Basavarajappa, and G. L. Samuel, “Some studies on hard turning of AISI 4340 steel using multilayer coated carbide tool,” Measurement 45 (7), pp. 1872 – 1884, 2012.[3] B. Fnides, M. A. Yallese, T. Mabrouki, and J. F. Rigal, “Application of response surface methodology for determining cutting force model in turning hardened AISI H11 hot work tool steel,” Sadhana 36(1), pp. 109 – 123, 2011.[4] M. W. Azizi, A. Belbah, M. A. Yallese, T. Mabrouki, and J. F. Rigal, “Surface roughness and cutting forces modeling for optimization of machining condition in finish hard turning of AISI 52100 steel,” J. Mech. Sci. Technol. 25 (12), pp. 4105 – 4114, 2012.[5] Z. Hessainia, M. A. Yallese, K. Chaoui, T. Mabrouki, and J. F. Rigal, “On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations,” Measurement 46(5), pp. 1671 – 1681, 2013.[6] K. Bouacha, M. A. Yallese, T. Mabrouki, and J. F. Rigal, “Statistical analysis of surface roughness and cutting forces using response surface methodology in hard turning of AISI 52100 bearing steel with CBN tool,” J. Refract. Met. Hard Mater. 28, pp. 349 – 361, 2010.[7] H. Aouici, H. Bouchelaghem, M. A. Yallese, M. Elbah, and B. Fnide, “Machinability investigation in hard turning of AISI D3 cold work steel with ceramic tool using response surface methodology,” Int. J. Adv. Manuf. Technol., Vol. 73, Issue 9‐12, pp. 1768 ‐ 1775, 2014.ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016 119

Journal of Advanced Manufacturing Technology [8] H. Aouici, M. A. Yallese, B. Findes, K. Chaoui, and T. Mabrouki, “Modeling and optimization of hard turning of X38CrMoV5‐1 steel with CBN tool: machining parameters effects on flank wear and surface roughness,” J. Mech. Sci. Technol. 25(11), pp. 2843 – 2851, 2011. [9] A. M. Al‐Ahmari, “Predictive machinability models for a selected hard material in turning operations,” J. Mater. Process Technol. 190, pp. 305 ‐ 311, 2007. [10] S. P. Dilbag and R. Venkateswara, “Surface roughness prediction model for hard turning process,” J. Adv. Manuf. Technol. 32, pp. 1115 – 1124, 2007. [11] T. I. El‐Wardany, H. A. Kishawy, M. A. Elsbestawi, “Surface integrity of die material in high‐speed hard machining. Part 1. Micro hardness various and residual stresses,” J. Manuf. Eng. 4(122), pp. 32 – 41, 2000. [12] E. D. Kirby, Z. Zhang, and J. C. Chen, “Development of an accelerometer based surface roughness prediction system in turning operation using multiple regression techniques,” J. Ind. Technol. 4(20), pp. 1 – 8, 2004. [13] J. T. Horng, N. M. Liu, and K. T. Chiang, “Investigating the machinability of Hadfield steel in hard turning with Al2O3/TiC mixed ceramic tool based on response surface methodology,” J. Mater. Process Technol. 208, pp. 532 – 541, 2008. [14] H. Aouici, M. A. Yallese, K. Chaoui, T. Mabrouki, and J. F. Rigal, “Analysis of surface roughness and cutting force components in hard turning with CBN tool: prediction model and cutting conditions optimization,” Measurement 45, pp. 344 – 353, 2012. [15] N. Kribes, Z. Hessainia, M. A. Yallese, N. Ouelaa, “Statistical analysis of surface roughness by design experiments in hard turning,” Mechanika 18 (5), pp. 605 – 611, 2012. [16] A. Doniavi, M. Eskanderzade, and M. Tahmsebian, “Empirical modeling of surface roughness in turning process of 1060 steel using factorial design methodology,” J. Appl. Sci. 7 (17), pp. 2509 – 2513, 2007. [17] R. Quiza, L. Figueira, and J. P. Davim, “Comparing statistical models and artificial neural networks on predicting the tool wear in hard machining D2 AISI steel,” J. Adv. Manuf. Technol. 37 (7 – 8), pp. 641 – 648, 2008. [18] S. Neseli, S. Yaldız, and E. Türkes, “Optimization of tool geometry parameters for turning based on the response surface methodology,” Measurement 44, pp. 580 – 587, 2011. [19] V. N. Gaitonde, S. R. Karnik, L. Figueira, J. P. Davim, “Analysis of machinability during hard turning of cold work tool steel (type: AISI D2),” Mater. Manuf. Process Taylor Francis 24 (12), pp. 1373 – 1382, 2009. [20] D. C. Montgomery, Design and Analysis of Experiments. New York: John Wiley & Sons, pp. 395 – 476, 1997.120 ISSN: 1985-3157 Vol. 10 No. 1 January - June 2016