• DocumentCode
    1720643
  • Title

    Knowledge-based handling of design expertise

  • Author

    Morizet-Mahoudeaux, Pierre ; Suzuki, Einoshin ; Ohsuga, Setsuo

  • Author_Institution
    Res. Center for Adv. Sci. & Technol., Tokyo Univ., Japan
  • fYear
    1994
  • Firstpage
    368
  • Lastpage
    374
  • Abstract
    Research issues in the domain of AI for design can be organized in three categories: decision making, representation and knowledge handling. In the area of knowledge handling, this paper addresses issues concerning the management of design experience to guide a priori the generation of candidate solutions. The approach is based on keeping the trace of a previous design experience as a hierarchical knowledge base. A level in the hierarchy can be viewed as a level of granularity of the description of the design process. A general framework for defining a partial order function between the granularity levels in the knowledge bases of design expertise is proposed. It is then possible to compute the sets of the elements belonging to smaller granularity levels, which are linked to any component of the hierarchy. Thus, it makes it possible to compute the level in the hierarchy that can be reused without modification for the design of a new product. Computation of the appropriate level is mainly based on matching the data corresponding to the new requirements with these sets. The approach has been tested by using a multiple expert systems structure based on using interactively two systems, an expert system development tool for design, KAUS, and an expert system development tool for diagnosing engineering processes, SUPER. The intrinsic properties of SUPER have also been used for improving the design procedure when qualitative and quantitative knowledge is involved
  • Keywords
    CAD; artificial intelligence; expert systems; knowledge based systems; AI; KAUS; SUPER; design expertise; granularity; hierarchical knowledge base; knowledge-based handling; multiple expert systems structure; partial order function; Artificial intelligence; Computer science; Decision making; Design engineering; Diagnostic expert systems; Knowledge management; Power system reliability; Problem-solving; Process design; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Engineering, 1994. Proceedings.10th International Conference
  • Conference_Location
    Houston, TX
  • Print_ISBN
    0-8186-5402-3
  • Type

    conf

  • DOI
    10.1109/ICDE.1994.283053
  • Filename
    283053