This report will be of interest to transit railcar maintenance professionals concerned with improving railcar maintenance fault-diagnostic capabilities through the use of artificial intelligence (AI) technologies. For the purpose of this report. AI is defined as a computer program that uses human problem-solving techniques to assist and augment the diagnostic process. Seven AI technologies--expert systems, case-based reasoning, model-based reasoning, artificial neural networks, computer vision, fuzzy logic, and knowledge-based systems-are investigated to determine their potential for application to the diagnosis of transit railcar systems and subsystems. The report concludes that AI technology is sufficiently mature for cost-effective application in the transit railcar diagnostic process and provides recommendations for implementation of the technology.


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    Title :

    Artificial Intelligence for Transit Railcar Diagnostics


    Contributors:

    Publication date :

    1994


    Size :

    72 pages



    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




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