A Methodology to Develop Taxonomy of Additive Manufacturing using Formal Attributes Specification Template
Additive Manufacturing (AM) is referring to technology that offers design creativity and freedom in developing the 3D product. AM generates and accumulates a large number of design information on geometrical part, materials, and processes. This is time-consuming for a designer in searching the right information about AM process. In this paper, the additive manufacturing processes have been classified according to their attributes information that is based on a systematic guideline, called Formal Attributes and Specification Template (FAST). FAST is used in the taxonomy generation for formal attribute identification which is later used in Formal Concept Analysis (FCA) to generate a lattice. The resulting lattice and formal attribute information obtained with FCA are later used to create taxonomy. The developed taxonomy was evaluated by homogeneous cluster analysis. The results of the evaluation show that the FAST method provides design rationale in developing AM taxonomy.
C. Klahn, B. Leutenecker and M. Meboldt, “Design strategies for the process of additive manufacturing,” Procedia CIRP, vol. 36, pp. 230-235, 2015.
B.P. Conner, G.P. Manogharan, A.N. Martof, L.M. Rodomsky, C.M. Rodomsky, D.C. Jordan and J.W. Limperos, “Making sense of 3-D printing: creating a map of additive manufacturing products and services,” Additive Manufacturing, vol. 1, pp. 64-76, 2014.
A.B. Spierings, N. Herres and G. Levy, “Influence of the particle size distribution on surface quality and mechanical properties in AM steel parts,” Rapid Prototyping Journal, vol. 17, no. 3, pp. 195-202, 2011.
E. Bassoli, A. Gatto and L. Luliano, “Joining mechanisms and mechanical properties of PA composites obtained by selective laser sintering,” Rapid Prototyping Journal, vol. 18, no. 2, pp. 100-108, 2012.
J.J. Martin, B.E. Fiore and R.M. Erb, “Designing bioinspired composite reinforcement architectures via 3D magnetic printing,” Nature Communications, vol. 6, 2015.
A. Boschetto and L. Bottini, “Accuracy prediction in fused deposition modeling,” The International Journal of Advance Manufacturing Technology, vol. 73, pp. 913 – 928, 2014.
I. Gibson, D.W. Rosen and B. Stucker, Additive Manufacturing Technologies (Rapid Prototyping to Direct Digital Manufacturing,” 2nd Edition. New York: Springer-Verlag, 2010.
Loughborough University. (2013). About additive manufacturing [Online]. Available: http://www.lboro.ac.uk/research/amrg/about/the7categoriesofadditivemanufacturing/
M. Grüninger and A. Delaval, “A first-order cutting process ontology for sheet metal parts,” in 4th Workshop Formal Ontologies Meet Industry, Berlin, 2009, pp. 22–33.
Y. Lu, H. Panetto, Y. Ni and X. Gu, “Ontology alignment for networked enterprises information systems interoperability in supply chain environment,” International Journal of Computer Integrated Manufacturing, vol. 26, no. 1-2, 2013.
S. Lemaignan, A. Siadat, J.Y. Dantan and A. Semenenko, “MASON: A proposal for an ontology of manufacturing domain,” in IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications, Prague, 2006, pp. 195-200.
S. Borgo and P. Leitao, “The role of foundational ontologies in manufacturing domain applications,” Lecture Notes Computer Science, vol. 3290, 670–688, 2004.
S. Akmal and R. Batres, “A methodology for developing manufacturing process ontologies,” Journal of Japan Industrial Management Association, vol. 64, pp. 303-316, 2013.
X. Liu and D.W. Rosen, “Ontology based knowledge modeling and reuse approach of supporting process planning in layer-based additive manufacturing,” in the 2010 International Conference on Manufacturing Automation, Hong Kong, 2010, pp. 261-262.
S. Akmal, L.-H. Shih and R. Batres, “Ontology-based similarity for product information retrieval,” Computers in Industry, vol. 65, pp. 91-107, 2014.
S. Akmal, M. Kamalrudin, S. Sidek, N.A. Zulkifli, and T.N.F. Kamarudin, “Formal attribute specification template to elicit accurate automotive requirements,” International Journal of Multidisciplanary Approach Studies, pp. 184-189, 2015.
S. Yevtushenko. (2009). Concept Explorer, Open source java software. Explorer (Release 1.3) [Online]. Available: http://sourceforge.net/projects/conexp/