Skip to main content

Advertisement

Log in

Product design and manufacturing process based ontology for manufacturing knowledge reuse

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • AIAG. (2008). Advanced product quality planning and control plan (APQP). Southfield: Automotive Automotive Industry Action Group.

  • Ameri, F., & Patil, L. (2012). Digital manufacturing market: A semantic web-based framework for agile supply chain deployment. Journal of Intelligent Manufacturing, 23(5), 1817–1832.

    Article  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.

  • Borst, W. (1997). Construction of engineering ontologies. Ph.D. Thesis, University of Tweenty, Enschede, NL.

  • Brachman, R., & Levesque, H. (1986). Knowledge representation and reasoning. Annual review of computer science., 1(1), 255–287.

    Article  Google Scholar 

  • Cassanelli, G., Mura, G., Fantini, F., Vanzi, M., & Plano, B. (2006). Failure analysis-assisted FMEA. Microelectronics Reliability, 46(9), 1795–1799.

    Article  Google Scholar 

  • Chandrasegaran, S., Ramani, K., Sriram, D., Horvath, I., Bernard, A., Harik, F., et al. (2013). The evolution, challenges, and future of knowledge representation in product design systems. Computer-Aided Design, 45(2), 204–228.

    Article  Google Scholar 

  • Chandrasekaran, B., Josephson, J., & Benjamins, V. (1999). What are ontologies and why do we need them? Intelligent Systems and their Applications IEEE, 14(1), 20–26.

    Article  Google Scholar 

  • Chungoora, N., Young, R., Gunendran, G., Palmer, C., Usman, Z., Anjum, A., et al. (2013). A model-driven ontology for manufacturing system interoperability and knowledge sharing. Computers in Industry, 64(4), 392–401.

    Article  Google Scholar 

  • Desouza, K., & Evaristo, R. (2003). Global knowledge management strategies. European Management Journal, 21(1), 62–67.

    Article  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.

  • Ducharme, B. (2013). Learning SPARQL (2nd ed.). Sebastopol: O’Reilly Media Inc.

    Google Scholar 

  • Ebrahimimpour, V., Rezaie, K., & Shokravi, S. (2010). An ontology approach to support FMEA studies. Expert Systems with Applications., 37(1), 671–677.

    Article  Google Scholar 

  • Ettlie, J. E., & Kubarek, M. (2008). Design reuse in manufacturing and services. Journal of Product Innovation Management, 25(5), 457–472.

    Article  Google Scholar 

  • Fabian, B., Kunz, S., Konnegen, M., Muller, S., & Gunther, O. (2012). Access control for semantic data federations in industrial product-lifecyle management. Computers in Industry, 63(9), 930–940.

    Article  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.

  • Hoffman, C., & Joan-Arinyo, R. (1998). CAD and the product master model. Computer-Aided Design, 30(11), 905–918.

    Article  Google Scholar 

  • 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.

  • Imran, M., & Young, B. (2015). The application of common logic based formal ontologies to assembly knowledge sharing. Journal of Intelligent Manufacturing, 26, 139–158.

    Article  Google Scholar 

  • Iyer, N., Subramaniam, J., Kuiyan, L., Yagnanarayanan, K., & Karthik, R. (2005). Shape-based searching for product lifecycle applications. Computer-Aided Design, 37(13), 1435–1446.

    Article  Google Scholar 

  • Jardim-Goncalves, R., Grilo, A., & Popplewell, K. (2016). Novel strategies for global manufacturing systems interoperability. Journal of Intelligent Manufacturing, 27(1), 1–9.

    Article  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.

  • Khilwani, N., & Harding, J. (2016). Managing corporate memory on the semantic web. Journal of Intelligent Manufacturing, 27(1), 101–118.

    Article  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).

  • Lee, B. (2001). Using FMEA models and ontologies to build diagnostic models. AI EDAM, 15(04), 281–293.

    Google Scholar 

  • Liao, Y., Lezoche, M., Panetto, H., Boudjlida, N., & Loures, E. (2015). Semantic annotation for knowledge explicitation in a product lifecycle management context: A survey. Computers in Industry, 71(1), 24–34.

    Article  Google Scholar 

  • Lin, H., & Harding, J. (2007). A manufacturing system engineering ontology model on the semantic web for inter-enterprise collaboration. Computers in Industry, 58(5), 428–437.

    Article  Google Scholar 

  • Lin, H., Harding, J., & Shahbaz, M. (2004). Manufacturing system engineering ontology for semantic interoperability across extended project teams. International Journal of Production Research, 42(24), 5099–5118.

    Article  Google Scholar 

  • Lin, L., Zhang, W., Lou, Y., Chu, C., & Cai, M. (2011). Developing manufacturing ontologies for knowledge reuse in distributed manufacturing environment. International Journal of Production Research, 49(2), 343–359.

    Article  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.

  • Negri, E., Fumagalli, L., Garetti, M., & Tanca, L. (2016). Requirements and languages for the semantic representation of manufacturing systems. Computers in Industry, 81, 55–66.

    Article  Google Scholar 

  • Noy, N., & McGuinness, D. (2001). Ontology development 101: A guide to creating your first ontology. Stanford Medical Informatics.

  • Pinto, H., & Martins, J. (2004). Ontologies: How can they be built? Knowledge and Information Systems, 6(4), 441–464.

    Article  Google Scholar 

  • Royce, W. (1970). Managing the development of large software systems. In Proceedings, IEEE Wescon (pp. 1–9).

  • Sanya, O. I., & Shehab, M. E. (2015). A framework for developing engineering design ontologies within the aerospace industry. International Journal of Production Research, 53(8), 2383–2409.

    Article  Google Scholar 

  • Shearer, R., Motik, B., & Horrocks, I. (2008). HermiT: A highly-efficient OWL reasoner. OWLED, Vol. 432.

  • 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.

  • Thisse, L. (1996). Advanced quality planning: A guide for any organization. Quality Progress, 31(2), 73–77.

    Google Scholar 

  • Tian, G., Yin, G., & Taylor, D. (2002). Internet-based manufacturing: A review and a new infrastructure for distributed intelligent manufacturing. Journal of Intelligent Manufacturing, 13(5), 323–338.

    Article  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.

  • 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.

  • Young, B., Gunendran, A., Cutting-Decelle, A., & Gruninger, M. (2007). Manufacturing knowledge sharing PLM: A progression towards the use of heavy weight ontologies. Internatinoal Journal of Production Research, 45(7), 1505–1519.

    Article  Google Scholar 

  • yWorks GmbH. (2015). Retrieved from www.yworks.com/en/products_yed_about.html.

  • Zhao, X., & Zhu, Y. (2012). Application research of ontology–enabled process FMEA knowledge management method. International Journal of Intelligent Systems and Applications, 4(3), 34–40.

    Article  Google Scholar 

Download references

Acknowledgements

We thank the two anonymous reviewers for their excellent inputs and suggestions that allowed us to significantly enhance the quality of the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ratna Babu Chinnam.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chhim, P., Chinnam, R.B. & Sadawi, N. Product design and manufacturing process based ontology for manufacturing knowledge reuse. J Intell Manuf 30, 905–916 (2019). https://doi.org/10.1007/s10845-016-1290-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10845-016-1290-2

Keywords

Navigation