Functional Ontology for Intelligent Instruments

  • Richard Dapoigny
  • Eric Benoit
  • Laurent Foulloy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2871)

Abstract

As a general and challenging task of decisional process in distributed environments, the individual nodes of the network need to exchange specific knowledge in order to achieve their goal. This is the case in distributed instrumentation where a network of intelligent components interact each other to realize some task. A conceptualization of functional knowledge is proposed and we argue that this conceptualization will be represented by ontologies based on mereology and topology. A synthesis of many works in knowledge engineering leads us to propose a knowledge representation with a dual objective. First, it provides instruments designers with a structural and logical framework that allows for easy reuse and secondly, it enable a distributed behavior based on causal representation and on dependencies between functional and behavioral knowledge on each node.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bouras, A., Staroswiecki, M.: How can Intelligent Instruments Interoperate in an Application Framework? A Mechanism for Taking into Account Operating Constraints. In: Proc. of Int. Conf. SICICA 1997, Annecy, France, June 9–11 (1997)Google Scholar
  2. 2.
    Tailland, J., Foulloy, L., Benoit, E.: Automatic Generation of Intelligent Instruments from Internal Model. In: Proc. of 4th IFAC Int.Symp. SICICA 2000, Buenos Aires, Argentina, pp. 337–342 (September 2000)Google Scholar
  3. 3.
    Riviere, J.M., Bayart, M., Thiriet, J.M., Bouras, A., Robert, M.: Intelligent instruments: some modelling approaches. Measurement and Control 29, 179–186 (1996)Google Scholar
  4. 4.
    Hawkins, R., McDowell, J.K., Sticklen, J., Hill, T., Boyer, R.: Function-based modeling and troubleshooting. Int. Journal of Applied Artificial Intelligence 8, 285–302 (1994)CrossRefGoogle Scholar
  5. 5.
    Umeda, Y., Tomiyama, T., Yoshikawa, H.: A design methodology for a self-maintenance machine based on functional redundancy. In: Taylor, D.L., Stauffer, L.A. (eds.) Design Theory and Methodology - DTM 1992. ASME (1992)Google Scholar
  6. 6.
    Kitamura, Y., Mizoguchi, R.: Functional Ontology for Functional Understanding. In: 12th International Workshop on Qualitative Reasoning, Cape Cod, USA, pp. 77–87. AAAI Press, Menlo Park (1998)Google Scholar
  7. 7.
    Lind, M.: Modeling Goals and Functions of Complex Industrial Plant. Journal ofApplied Artificial Intelligence (8), 259–283 (1994)Google Scholar
  8. 8.
    Chandrasekaran, B., Josephson, J.R.: Function in device Representation. Journal of Engineering with Computers, Special Issue on Computer aided Engineering 16, 162–177 (2000)MATHGoogle Scholar
  9. 9.
    Salustri, F.A.: Function Modeling for an Integrated Framework: A progress Report. In: Cook, D. (ed.) Procs. of FLAIRS 1998, pp. 339–343. AAAI, Menlo Park (1998)Google Scholar
  10. 10.
    Umeda, Y., et al.: Supporting conceptualdesign based on thefunction-behavior-state modeler. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10(4), 275–288 (1996)CrossRefGoogle Scholar
  11. 11.
    Qian, L., Gero, I.: Function-behavior-structure paths andtheir role in analogy-based design. ArtificialIntelligence for Engineering Design, Analysis andManufacturing 10(4), 289–292 (1996)CrossRefGoogle Scholar
  12. 12.
    Kitamura, Y., Sano, T., Namba, K., Mizogushi, R.: A Functional Concept Ontology and its Application to Automatic Identification of Functional Structures. Advanced Engineering Informatics 16(2), 145–163 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Richard Dapoigny
    • 1
  • Eric Benoit
    • 1
  • Laurent Foulloy
    • 1
  1. 1.Laboratoire d’Informatique des Systèmes, du Traitement de l’Information et de CommandeUniversity of SavoieANNECY Cedex

Personalised recommendations