The equipment maintenance community traditionally has faced a variety of problems and challenges ranging from the scarcity of properly trained personnel, to less-than-ideal testing conditions. An evaluation of these problems identified equipment maintenance as an area that is ideally suited for the application of expert systems technology. Expert systems capture the problem solving capability of the experts and thus provide a diversity of knowledge when the experts are unavailable. However, capturing the experts knowledge in the expert system's rule-base can be a challenging task. A software architecture, developed at Raytheon for this purpose, is discussed below. This architecture was used successfully on two Raytheon-specific diagnostic expert systems, the Expert Missile Maintenance Aid (EMMA) and the Pod Expert Automated Troubleshooting (PEAT) System.


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    Title :

    Equipment maintenance applications of artificial intelligence


    Additional title:

    Expertensysteme unterstützen Wartung bei Militärgeräten


    Contributors:
    Hintz, J.C. (author) / Wasiuk, N.W. (author)

    Published in:

    Electronic Progress ; 32 , 1 ; 28-33


    Publication date :

    1992


    Size :

    6 Seiten



    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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