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Semantic Web Framework for Rule-Based Generation of Knowledge and Simulation of Manufacturing Systems

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Enterprise Interoperability III

Abstract

The development of new products and manufacturing systems is usually performed in the form of projects. Frequently, the conduction of the project takes more time than planned due to inconsistency, incompleteness, and redundancy of data, which delays other project activities influencing the start of production (SOP). This paper proposes a semantic Web framework for cooperation and interoperability within product design and manufacturing engineering projects. Data and knowledge within the manufacturing domain are modelled within ontologies applying rule-based mapping. The framework facilitates the generation of new knowledge through rule based inference that enriches the ontology. This enables a high-level model completeness in the early phase of product design and manufacturing system development, which is a basic prerequisite for the realisation of a proper simulation study and analysis. The simulation results can be integrated into the ontologies as a knowledge that additionally extends the ontology.

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References

  1. Gocev, P., Rabe, M.: Simulation Models for Factory Planning through Connection of ERP and MES Systems. Tagungsband 12. ASIM-Fachtagung Simulation in Produktion und Logistik, pp. 223–232. Kassel (2006)

    Google Scholar 

  2. Gocev, P.: Semantic Web Technologies for Simulation in Production and Logistic-a Survey. Simulation und Visualisierung 2007 — Doktorandenforum Diskrete Simulation, pp. 1–10. Magdeburg (2007)

    Google Scholar 

  3. Silver, G., Hassan, O., Miller, J.: From Domain Ontologies to Modeling Ontologies to Executable Simulation Models. Proceedings of the 2007 Winter Simulation Conference, pp 1108–1117. (2007)

    Google Scholar 

  4. Miller, J., Fischwick, P.: Investigating Ontologies for Simulation Modelling. Proceedings of the 37th Annual Simulation Symposium (ANSS’04). pp 55–63. (2004)

    Google Scholar 

  5. Project Pabadis‘Promise. www.pabadis-promise.org

    Google Scholar 

  6. Development of Product and Production Process Description Language (PPPDL). www.uni-magdeburg.de/iaf/cvs/pabadispromise/dokumente/Del_3_1_Final.pdf

    Google Scholar 

  7. Gruber, T.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5(2), pp. 199–220, (1993)

    Article  Google Scholar 

  8. Lin, H.-K., Harding, J. A., Shahbaz, M. Manufacturing System Engineering Ontology for Semantic Interoperability across Extended Project Teams. International Journal of Production Research, Vol.42, No.24, pp 5099–5118. Tylor & Francis (2004).

    Article  Google Scholar 

  9. Ye, Y., Yang, D., Jiang, Z., Tong, T.: Ontology-based Semantic Models for Supply Chain Management. The International Journal of Advanced Manufacturing Technology. Springer, London (2007)

    Google Scholar 

  10. Borgo, S., Leitao, P.: Foundations for a Core Ontology of Manufacturing. Ontologies — A Handbook of Principles, Concepts and Applications in Information Systems, Vol.14, Part 4, pp 751–775. Springer (2007)

    Google Scholar 

  11. Leitão, P., Colombo, A., Restivo, F.: ADACOR — A Collaborative Production Automation and Control Architecture. IEEE Intelligent Systems, Vol.20, No.1, pp 58–66. (2005)

    Article  Google Scholar 

  12. World Wide Web Consortium. www.w3.org

    Google Scholar 

  13. Extensible Markup Language. http://www.w3.org/XML

    Google Scholar 

  14. Resource Description Framework. www.w3.org/RDF

    Google Scholar 

  15. Resource Description Framework Schema. www.w3.org/TR/rdf-schema

    Google Scholar 

  16. Web Ontology Language-www.w3.org/2004/OWL

    Google Scholar 

  17. Semantic Web Rule Language. www.w3.org/Submission/SWRL

    Google Scholar 

  18. Instrumentation, Systems, and Automation Society, Enterprise-Control System Integration. Parts 1,2,3. Published 2000-2005. www.isa.org

    Google Scholar 

  19. Open Applications Group Integration Specification. www.oagi.org

    Google Scholar 

  20. Standard for the Exchange of Product Model Data. www.tc184-sc4.org/SC4_Open

    Google Scholar 

  21. Machinery Information Management Information Open Systems Alliance. www.mimosa.org

    Google Scholar 

  22. RosettaNet Standards. www.rosettanet.org

    Google Scholar 

  23. Petroleum Industry Data Exchange (PIDX). www.pidx.org

    Google Scholar 

  24. Industrial Automation Systems and Integration — Integration of Life-Cycle Data for Process Plants Including Oil and Gas Production Facilities. www.iso.org; http://15926.org

    Google Scholar 

  25. Industrial Automation Systems and Integration — Diagnostics, Capability Assessment, and Maintenance Applications Integration Part 1. (Under Development), 2006. www.iso.org

    Google Scholar 

  26. Function Blocks for Industrial-Process Measurement and Control Systems. www.iec.ch

    Google Scholar 

  27. Studer R. et al.: Arbeitsgerechte Bereitstellung von Wissen — Ontologien für das Wissensmanagement. Technical Report, Institut AIFB, Universität Karlsruhe. 2001. www.aifb.uni-karlsruhe.de/WBS/ysu/publications/2001_wiif.pdf

    Google Scholar 

  28. Object Management Group (OMG). www.omg.org

    Google Scholar 

  29. Systems Modeling Language (SysML). www.sysml.org

    Google Scholar 

  30. Unified Modeling Language (UML). www.uml.org

    Google Scholar 

  31. XML Metadat Interchange (XMI). www.omg.org/technology/documents/formal/xmi.htm

    Google Scholar 

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Rabe, M., Gocev, P. (2008). Semantic Web Framework for Rule-Based Generation of Knowledge and Simulation of Manufacturing Systems. In: Mertins, K., Ruggaber, R., Popplewell, K., Xu, X. (eds) Enterprise Interoperability III. Springer, London. https://doi.org/10.1007/978-1-84800-221-0_31

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  • DOI: https://doi.org/10.1007/978-1-84800-221-0_31

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84800-220-3

  • Online ISBN: 978-1-84800-221-0

  • eBook Packages: EngineeringEngineering (R0)

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