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    New Probabilistic Method for Estimation of Equipment Failures and Development of Replacement Strategies

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    06-04.pdf (267.4Kb)
    Date
    2006
    Author
    Begović, Miroslav
    Djuric, Petar
    Perkel, Joshua
    Vidakovic, Brani
    Novosel, Damir
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    Abstract
    When large amount of statistical information about power system component failure rate is available, statistical parametric models can be developed for predictive maintenance. Often times, only partial information is available: installation date and amount, as well as failure and replacement rates. By combining sufficiently large number of yearly populations of the components, estimation of model parameters may be possible. The parametric models may then be used for forecasting of the system’s short term future failure and for formulation of replacement strategies. We employ the Weibull distribution and show how we estimate its parameters from past failure data. Using Monte Carlo simulations, it is possible to assess confidence ranges of the forecasted component performance data.
    URI
    http://hdl.handle.net/1853/25836
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    • Biomedical Engineering Technical Reports [32]

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