Advertisement

Towards an Ontology for Small Series Production

  • Udo Inden
  • Nikolay Mehandjiev
  • Lars Mönch
  • Pavel Vrba
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8062)

Abstract

We describe the derivation of ontology to capture knowledge regarding small series manufacturing. This work is motivated by use-cases ranging from the assembly of large aircraft built from about 6 million parts to the production of galley inserts, both plagued by problems for arising from the same interplay between product and production engineering. During ramp-up stages of such production, there are challenges of innovative technologies, high quality and safety standards or the structural complexity of products which frequently cause supply-chain problems or require revisions of the designs that result in significant financial losses. These conditions differ significantly from standard production scenarios. Based on a detailed domain analysis, we identify five requirements for the type of knowledge to be captured in ontology, and then proceed to propose a first version of such an ontology addressing these requirements, thus providing an appropriate semantic base for intelligent, associative tools that can effectively support ramp-up management.

Keywords

Ontology Small series production Holonic Manufacturing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Borgo, S., Leitão, P.: The role of foundational ontologies in manufacturing domain applications. In: Meersman, R., Tari, Z. (eds.) CoopIS/DOA/ODBASE 2004. LNCS, vol. 3290, pp. 670–688. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  2. 2.
    Borgo, S., Leitao, P.: Foundations for a Core Ontology of Manufacturing. In: Sharman, R., Kishore, R., Ramesh, R. (eds.) Ontologies: A Handbook of Principles, Concepts and Applications in Information Systems. Integrated Series in Information Systems, vol. 14, pp. 751–776 (2007)Google Scholar
  3. 3.
    Gruber, T.R.: Towards Principles for the Design of Ontologies Used for Knowledge Sharing. Int. J. Hum. Comp. Studies 43(5/6), 907–928 (1995)CrossRefGoogle Scholar
  4. 4.
    Heike, G., Ramulu, M., Sorenson, E., Shanahan, P., Moinzadeh, K.: Mixed Model Assembly Alternatives for Low-volume Manufacturing: The Case of the Aerospace Industry. Int. J. Production Economics 72, 103–120 (2001)CrossRefGoogle Scholar
  5. 5.
    Lose, N., Hirani, H., Ratchev, S., Turitto, M.: An Ontology for the Definition and Validation of Assembly Processes for Evolvable Assembly Systems. In: Proceedings of the 6th IEEE International Symposium on Assembly and Task Planning: From Nano to Macro Assembly and Manufacturing, pp. 242–247 (2005)Google Scholar
  6. 6.
    Malone, T.W., Crowston, K.: The Interdisciplinary Study of Coordination. ACM Computing Surveys 26(1), 87–119 (1994)CrossRefGoogle Scholar
  7. 7.
    Mas, F., Rios, J., Menendez, J.L., Gomez, A.: A Process-oriented Approach to Modeling the Conceptual design of Aircraft Assembly Lines. International Journal of Advanced Manufacturing Technology 67(1-4), 771–784 (2012)CrossRefGoogle Scholar
  8. 8.
    Mehandjiev, N.D., Stalker, I.D., Carpenter, M.R.: Recursive Construction and Evolution of Collaborative Business Processes. In: Ardagna, D., Mecella, M., Yang, J. (eds.) BPM 2008 Workshops. LNBIP, vol. 17, pp. 573–584. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  9. 9.
    Mönch, L., Zimmermann, J.: An Ontology to Support Adaptive Agents for Complex Manufacturing Systems. In: Proceedings 3rd IEEE International Conference on Computer Software and Applications, pp. 531–536 (2008)Google Scholar
  10. 10.
    Noack, D., Rose, O.: A Simulation Based Optimization Algorithm for Slack Reduction and Workforce Scheduling. In: Proceedings of the 2008 Winter Simulation Conference, pp. 1989–1994 (2008)Google Scholar
  11. 11.
    Obitko, M., Mařík, V.: Adding OWL Semantics to Ontologies Used in Multi-agent Systems for Manufacturing. In: Mařík, V., McFarlane, D.C., Valckenaers, P. (eds.) HoloMAS 2003. LNCS (LNAI), vol. 2744, pp. 189–200. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  12. 12.
    Rios, J., Mas, F., Menendez, J.L.: Aircraft Final Assembly Line Balancing and Workload Smoothing: A Methodical Analysis. Key Engineering Materials 502, 19–24 (2012)CrossRefGoogle Scholar
  13. 13.
    Storch, R.L., Lim, S.: Improving Flow to Achieve Lean Manufacturing in Shipbuilding. Production Planning & Control 10(2), 127–137 (1999)CrossRefGoogle Scholar
  14. 14.
    Uschold, M., King, M., Moralee, S., Zorgios, Y.: The Enterprise Ontology. The Knowledge Engineering Review 13(1), 31–89 (1998)CrossRefGoogle Scholar
  15. 15.
    Van Brussel, H., Wyns, J., Valckenaers, P., Bongaerts, L., Peeters, P.: Reference Architecture for Holonic Manufacturing Systems: PROSA. Computers in Industry 37(3), 225–276 (1998)Google Scholar
  16. 16.
    Vrba, P., Radakovič, M., Obitko, M., Mařík, V.: Semantic Technologies: Latest Advances in Agent-based Manufacturing Control Systems. Int. J. of Production Research 49(5), 1483–1496 (2011)CrossRefGoogle Scholar
  17. 17.
    Tudorache, T.: Employing Ontologies for an Improved Development Process in Collaborative Engineering. Dissertation, Fakultät IV – Elektrotechnik und Informatik der Technischen Universität Berlin (2006), http://opus.kobv.de/tuberlin/volltexte/2006/1437/pdf/tudorache_tania.pdf, Reference: http://protegewiki.stanford.edu/wiki/Engineering_ontologies (accessed September 12, 2012)
  18. 18.
    Gruber, T.R., Olsen, G.R.: An Ontology for Engineering Mathematics. In: Doyle, J., Torasso, P., Sandewall, E. (eds.) Fourth International Conference on Principles of Knowledge Representation and Reasoning (1994)Google Scholar
  19. 19.
    Siang, K.D., Duffy, A.H.B.: Towards an ontology of generic engineering design activities. Research in Engineering Design 14(4), 200–223 (2003)CrossRefGoogle Scholar
  20. 20.
    Arnold, D., Isermann, H., Kuhn, A., Tempelmeier, H., Furmans, K. (Hrsg.): Handbuch Logistik 3. Auflage. Springer, Heidelberg (2008)Google Scholar
  21. 21.
    747 Fun Facts, http://www.boeing.com/boeing/commercial/747family/pf/pf_facts.page (accessed November 2, 2011)
  22. 22.
    Terwiesch, C., Bohn, R.E.: Learning and process improvement during production ramp-up. International Journal of Production Economics 70(1), 1–19 (2001)CrossRefGoogle Scholar
  23. 23.
    Dreamliner Grounded Until At Least End Of May. Sky News (February 25, 2013), http://news.sky.com/story/1056514/dreamliner-grounded-until-at-least-end-of-may (accessed March 27, 2013)
  24. 24.
    Kingsley, J.M.: Airbus slows A380 final assembly ramp-up. Flightglobal (May 14, 2009), www.flightglobal.com/news/articles/airbus-slows-a380-final-assembly-ramp-up-326416/ (access February 25, 2013)
  25. 25.
    Takeishi, A., Fujimoto, T.: Modularisation in the auto industry: interlinked multiple hierarchies of product, production, and supplier Systems. Int. J. of Automotive Technology and Management 1(4), 379–396 (2001)CrossRefGoogle Scholar
  26. 26.
    European Aviation Safety Agency (EASA), accessed September 30, 2012: Commission Regulation (EC) No 1702/2003, September 2003: Implementing Rules of Airworthiness, http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CONSLEG:2003R1702:20091228:EN:PDF
  27. 27.
    Automotive Regulatory framework for type-approvals, http://ec.europa.eu/enterprise/sectors/automotive/technical-harmonisation/regulatory-framework/ (accessed March 12, 2013)
  28. 28.
    Hellingrath, B., Witthaut, M., Böhle, C., Brügger, S.: An Organizational Knowledge Ontology for Automotive Supply Chains. In: Mařík, V., Strasser, T., Zoitl, A. (eds.) HoloMAS 2009. LNCS, vol. 5696, pp. 37–46. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  29. 29.
    Cândido, G., Barata, J.: A Multiagent Control System for Shop Floor Assembly. In: Mařík, V., Vyatkin, V., Colombo, A.W. (eds.) HoloMAS 2007. LNCS (LNAI), vol. 4659, pp. 293–302. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  30. 30.
    Merdan, M.: Knowledge-based multi-agent architecture applied in the assembly domain. Dissertation thesis (PhD). Vienna University of Technology (2009)Google Scholar
  31. 31.
    Al-Safi, Y., Vyatkin, V.: An Ontology-Based Reconfiguration Agent for Intelligent Mechatronic Systems. In: Mařík, V., Vyatkin, V., Colombo, A.W. (eds.) HoloMAS 2007. LNCS (LNAI), vol. 4659, pp. 114–126. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Udo Inden
    • 1
  • Nikolay Mehandjiev
    • 2
  • Lars Mönch
    • 3
  • Pavel Vrba
    • 4
  1. 1.Cologne University of Applied SciencesKölnGermany
  2. 2.Manchester Business SchoolManchesterUK
  3. 3.University of HagenHagenGermany
  4. 4.Czech Technical University in PraguePrague 6Czech Republic

Personalised recommendations