Machine breakdowns are one of the main sources of disruption and throughput fluctuation in highly automated production facilities. One element in reducing this disruption is ensuring that the maintenance team responds correctly to machine failures. It is, however, difficult to determine the current practice employed by the maintenance team, let alone suggest improvements to it. ‘Knowledge based improvement’ is a methodology that aims to address this issue, by (a) eliciting knowledge on current practice, (b) evaluating that practice and (c) looking for improvements. The methodology, based on visual interactive simulation and artificial intelligence methods, and its application to a Ford engine assembly facility are described.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Modelling and Improving Maintenance Decisions: Having Foresight with Simulation and Artificial Intelligence


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Alifantis, A. (Autor:in) / Ladbrook, J. (Autor:in) / Edwards, J. S. (Autor:in) / Hurrion, R. D. (Autor:in) / Robinson, S. (Autor:in) / Waller, T. (Autor:in)

    Kongress:

    SAE 2002 World Congress & Exhibition ; 2002



    Erscheinungsdatum :

    2002-03-04




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch