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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/65058

    Title: A Neural Network Application for Reliability Modeling and Condition-Based Predictive Maintenance
    Authors: Lin, Chang-ching;Tseng, Hsien-yu
    Contributors: 淡江大學經營決策學系
    Keywords: Cerebellar model articulation controller;Neural network;Predictive maintenance;Weibull proportional hazards model
    Date: 2005-01
    Issue Date: 2011-10-20 16:31:59 (UTC+8)
    Abstract: Traditionally, decisions on the use of machinery are based on previous experience, historical data and common sense. However, carrying out an effective predictive maintenance plan, information about current machine conditions must be made known to the decision-maker. In this paper, a new method of obtaining maintenance information has been proposed. By integrating traditional reliability modelling techniques with a real-time, online performance estimation model, machine reliability information such as hazard rate and mean time between failures can be calculated. Essentially, this paper presents an innovative method to synthesise low level information (such as vibration signals) with high level information (like reliability statistics) to form a rigorous theoretical base for better machine maintenance.
    Relation: The International Journal of Advanced Manufacturing Technology 25(1-2), pp.174-179
    DOI: 10.1007/s00170-003-1835-3
    Appears in Collections:[Department of Management Sciences] Journal Article

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