Advertisement

Ontology-Based Process Modelling for Design Optimisation Support

  • Franz Maier
  • Wolfgang Mayer
  • Markus Stumptner
  • Arndt Muehlenfeld

The integration and reuse of simulation and process information is not wellintegrated into current development practices. We introduce a framework to integrate Multidisciplinary Design Optimisation (MDO) processes using ontological engineering. Based on a multi-disciplinary design scenario drawn from the automotive industry, we illustrate how semantic integration of process, artifact and simulation models can contribute to more effective optimisation-driven development. Ontology standards are evaluated to assess where existing work may be applicable and which aspects of MDO processes require further extensions.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bock C, Grueninger M (2005) PSL: A semantic domain for flow models. Software Systems Modeling: 209–231Google Scholar
  2. 2.
    Chandrasekaran B, Josephson J, Benjamins R (1998) The ontology of tasks and methods. Proc. of KAW′98Google Scholar
  3. 3.
    Chen L, Shadbolt R, Tao F (2005) Semantics-assisted problem solving on the semantic grid. Computational Intelligence 21(2): 157–176CrossRefMathSciNetGoogle Scholar
  4. 4.
    Chira C, Roche T, Tormey D, Brennan A (2004) An ontological and agentbased approach to knowledge management within a distributed design environment. In JS Gero (ed), Design Computing and Cogition′04, Kluwer,: 459–478Google Scholar
  5. 5.
    Dartigues C, Ghodous P (2002) Product data exchange using ontologies. In JS Gero (ed.), Artificial Intelligence in Design'02, Kluwer, Dordrecht: 617–636Google Scholar
  6. 6.
    Deshayes L, Foufou S, Grueninger M (2006) An ontology architecture for standards integration and conformance in manufacturing. Proc. of IDMMEGoogle Scholar
  7. 7.
    Felfernig A, Friedrich G, Jannach D, Stumptner M, Zanker M (2003) Configuration knowledge representations for semantic web applications. AI EDAM 17(1): 31–50.Google Scholar
  8. 8.
    Fensel D, Motta E, Decker S, Zdráhal Z (1997) Using ontologies for defining tasks, problem-solving methods and their mappings. Proc. EKAW: 113–128Google Scholar
  9. 9.
    Fowler D et al. (2004) The designers′ workbench: Using ontologies and constraints for configuration. Proc. AI2004/SGAI′04Google Scholar
  10. 10.
    Fruchter R, Demian P (2002) CoMem: designing an interaction experience for reuse of rich contextual knowledge from a corporate memory. AI EDAM 16(3): 127–147Google Scholar
  11. 11.
    Gero JS, Kannengiesser U (2007) A function-behaviour-structure ontology of processes. AI EDAM 21(4): 379–391Google Scholar
  12. 12.
    Gómez-Pérez et al. (2004) Ontological engineering. SpringerGoogle Scholar
  13. 13.
    Haymaker J, Kunz JC, Suter B, Fischer MA (2004) Perspectors. Advanced Engineering Informatics 18(1): 49–67CrossRefGoogle Scholar
  14. 14.
    ISO 10303–11 (1994) Ind. automation systems and integration-Product data representation and exchange-Part 11:The EXPRESS language ref. manual.Google Scholar
  15. 15.
    Kannengiesser U, Gero JS (2006) Towards mass customized interoperability. Computer Aided Design 38(8): 920–936CrossRefGoogle Scholar
  16. 16.
    Kifer M, Lausen G, Wu J (1995) Logical Foundations of Object-Oriented and Frame-Based Languages. Journal of the ACM 42(4): 741–843MATHCrossRefMathSciNetGoogle Scholar
  17. 17.
    Kitamura Y, Koji Y, Mizoguchi R (2006) An ontological model of device function: industrial deployment and lessons learned. Applied Ontology 1(3–4): 237–262Google Scholar
  18. 18.
    Maier A, Schnurr HP, Sure Y (2003) Ontology-based information integration in the automotive industry. Proc. Intl. Sem. Web Conf., LNCS 2870: 897–912Google Scholar
  19. 19.
    Maier F, Stumptner M (2007) Enhancements and ontological use of ISO10303 (STEP) to support the exchange of parameterised product data models. Proc. ISDA′07: 433–440Google Scholar
  20. 20.
    Mizoguchi R, Vanwelkenhuysen J, Ikeda M (1995) Task ontology for reuse of problem solving knowledge. KB&KS: 46–59Google Scholar
  21. 21.
    Oinn T et al. (2006) Taverna: lessons in creating a workflow environment for the life sciences. Concurrency and Computation: Practice and Experience 18(10): 1067–1100CrossRefGoogle Scholar
  22. 22.
    Rachuri S et al. (2005) Information models for product representation: core and assembly models. Int. Journal of Product Development 2(3): 207–235Google Scholar
  23. 23.
    Seeling C (2007) User Manual for the Crash-box MDO reference problemGoogle Scholar
  24. 24.
    Thiagarajan R, Stumptner M, Mayer W (2007) Semantic web service composition by consistency-based model refinement. Proc. 2nd IEEE Asia-Pacific Service Computing Conference (ASPSCC′07): 336–343Google Scholar
  25. 25.
    Wilmering T, Sheppard J (2007) Ontologies for data mining and knowledge discovery to support diagnostic maturation. Proc. 19th Intl. Workshop on Principles of Diagnosis (DX′07): 210–217Google Scholar

Copyright information

© Springer Science+Business Media B.V 2008

Authors and Affiliations

  • Franz Maier
    • 1
  • Wolfgang Mayer
    • 1
  • Markus Stumptner
    • 1
  • Arndt Muehlenfeld
    • 1
  1. 1.University of South AustraliaAustralia

Personalised recommendations