• DocumentCode
    3306108
  • Title

    Application of ontology guided search for improved equipment diagnosis in a vehicle assembly plant

  • Author

    Chougule, Rahul ; Chakrabarty, Sugato

  • Author_Institution
    Gen. Motors R&D, India Sci. Lab., Bangalore, India
  • fYear
    2009
  • fDate
    22-25 Aug. 2009
  • Firstpage
    90
  • Lastpage
    95
  • Abstract
    In the body shop of an automobile assembly plant, having access to correct and timely diagnostic information is very important for solving equipment and tooling maintenance problems. Variation Reduction Adviser (VRA) is an internal General Motors (GM) system that contains information related to the problems encountered in process, their root cause and possible solutions. This paper presents our work on ontology based diagnosis, where, a thesaurus (which is a simple form of ontology) has been used for retrieving diagnostic information. A thesaurus has been developed from existing problem descriptions and their solutions written in a natural language (such as English). A systematic methodology has been developed for the creation of a thesaurus. The results of ontology based diagnostic information retrieval have been compared with dasiaexact matchpsila information retrieval.
  • Keywords
    automobile manufacture; information retrieval; maintenance engineering; ontologies (artificial intelligence); production engineering computing; production equipment; thesauri; General Motors; diagnostic information; equipment diagnosis; equipment maintenance problems; information retrieval; ontology based diagnosis; thesaurus; tooling maintenance problems; vehicle assembly plant; Assembly systems; Automation; Information retrieval; Knowledge management; Natural languages; Ontologies; Research and development; Thesauri; Vehicles; Welding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation Science and Engineering, 2009. CASE 2009. IEEE International Conference on
  • Conference_Location
    Bangalore
  • Print_ISBN
    978-1-4244-4578-3
  • Electronic_ISBN
    978-1-4244-4579-0
  • Type

    conf

  • DOI
    10.1109/COASE.2009.5234132
  • Filename
    5234132