Product design and manufacturing process based ontology for manufacturing knowledge reuse
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This paper presents an effective product design and manufacturing process based ontology for manufacturing knowledge reuse. While a number of related efforts exist in the literature, there lacks a granular, interconnected product design and manufacturing process based ontology that can lead to greater industry adoption and knowledge reuse. In particular, the proposed ontology leverages an established industry standard to connect product design and manufacturing process knowledge in a logical and effective manner. The resulting effort is a general ontological framework that can be widely employed by the manufacturing industry. Additionally, the feasibility of implementing the ontology enabled knowledge reuse framework is demonstrated through a real-world case study.
KeywordsAPQP Knowledge management Manufacturing ontology Semantic web SPARQL
- AIAG. (2008). Advanced product quality planning and control plan (APQP). Southfield: Automotive Automotive Industry Action Group.Google Scholar
- Bobrek, M., & Sokovic, M. (2005). Implementation of APQP—Concept in design of QMS. In 13th International scientific conference on achievements in mechanical and materials engineering. Gliwice-Wista, Poland.Google Scholar
- Borst, W. (1997). Construction of engineering ontologies. Ph.D. Thesis, University of Tweenty, Enschede, NL.Google Scholar
- Dittmann, L., Rademacher, T., & Zelewski, S. (2004). Performing FMEA using ontologies. In 18th International workshop on qualitative reasoning (pp. 209-216). Evanston, USA.Google Scholar
- Ducharme, B. (2013). Learning SPARQL (2nd ed.). Sebastopol: O’Reilly Media Inc.Google Scholar
- Hill, K., Menk, D., & Cooper, A. (2016). Contribution of the automotive industry to the economies of all fifty state and the United States—See more at: http://www.cargroup.org/?module=Publications&event=View&pubID=16#sthash.gsYjhu4I.dpuf. Retrieved from Center for Automotive Research: http://www.cargroup.org/?module=Publications&event=View&pubID=16.
- Horridge, M. (2004). A practical guide to building OWL ontologies using the protege-OWL plugin and CO-ODE tools (1.3rd ed.). Manchester: The University Of Manchester.Google Scholar
- Iarovy, S., Ramis, B., Xiangbin, X., Sampath, A., Lobov, A., & Lastra, J. (2015). Representation of manufacturing equipment and services for OKD-MES: From service descriptions to ontology. In In 2015 IEEE 13th international conference on industrial informatics (INDIN) (pp. 1069–1074). IEEE.Google Scholar
- Khadilkar, V., Kantarcioglu, M., Thuraisingham, B., & Castagna, P. (2012). Jena-HBase: A distributed, scalable and efficient RDF triple store. In Proceedings of the 11th international semantic web conference posters & demonstrations track 12 (pp. 85–88). ISWC-PD.Google Scholar
- Laaroussi, A., Fies, B., Vankeisbelckt, R., & Hans, J. (2007). Ontology-aided FMEA for construction products. In 24th W78 Conference Maribor 26 (pp. 189–194).Google Scholar
- Lee, B. (2001). Using FMEA models and ontologies to build diagnostic models. AI EDAM, 15(04), 281–293.Google Scholar
- Molhanec, M., Mach, P., Asamoah, D., & Mensah, B. (2011). The ontology based FMEA of lead free soldering process. In 34th International spring seminar (pp. 267–273). IEEE.Google Scholar
- Noy, N., & McGuinness, D. (2001). Ontology development 101: A guide to creating your first ontology. Stanford Medical Informatics.Google Scholar
- Royce, W. (1970). Managing the development of large software systems. In Proceedings, IEEE Wescon (pp. 1–9).Google Scholar
- Shearer, R., Motik, B., & Horrocks, I. (2008). HermiT: A highly-efficient OWL reasoner. OWLED, Vol. 432.Google Scholar
- Stanford Center for Biomedical Research. (2015). Protege. Retrieved from http://protege.stanford.edu/.
- Swartout, B., Patil, R., Knight, K., & Russ, T. (1996). Toward distributed use of large scale ontologies. In Proceedings of 10th knowledge acquisition for knowledge—based systems workshop. Banff, Canada.Google Scholar
- Thisse, L. (1996). Advanced quality planning: A guide for any organization. Quality Progress, 31(2), 73–77.Google Scholar
- Tsarkov, D., & Horrocks, I. (2006). FaCT++ description logic reasonser: System description. Berlin: Springer.Google Scholar
- Tsia, C. a. (2014). The State of Knowledge Management: 2014. San Diego, CA: TSIA.Google Scholar
- Uschold, M., & King, M. (1995). Towards a methodology for building ontologies. In Workshop on basic ontological issues in knowledge sharing D (IJCAI’95), (pp. 6.1–6.10). Montreal, Canada.Google Scholar
- yWorks GmbH. (2015). Retrieved from www.yworks.com/en/products_yed_about.html.