• DocumentCode
    1681536
  • Title

    Evidence-based Bayesian networks approach to airplane maintenance

  • Author

    Kipersztok, Oscar ; Dildy, Glenn A.

  • Author_Institution
    Math. & Comput. Technol., Boeing Co., Seattle, WA, USA
  • Volume
    3
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    2887
  • Lastpage
    2891
  • Abstract
    A system that facilitates airplane maintenance provides decision support for finding the root-cause of a failure from observed symptoms and findings. Such system provides diagnostic advice listing the most probable causes and recommending possible remedial actions. Furthermore, its goal is to reduce the number of delays and cancellations and unnecessary parts removal, which add significant costs to airplane maintenance operations. A Bayesian belief network, model-based approach is presently being used for building such diagnostic models. The paper describes the pertinent issues in using such models
  • Keywords
    aerospace computing; aircraft maintenance; belief networks; case-based reasoning; decision support systems; diagnostic expert systems; neural nets; DSS; airplane maintenance; decision support system; diagnostic advice; evidence-based Bayesian networks; failure cause finding; remedial actions; root-cause; Air safety; Airplanes; Bayesian methods; Computational modeling; Computers; Costs; Delay; Maintenance; Mathematics; Medical simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1007607
  • Filename
    1007607