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Utility based maintenance analysis using a Random Sign censoring model

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  • Andrés Christen, J.
  • Ruggeri, Fabrizio
  • Villa, Enrique

Abstract

Industrial systems subject to failures are usually inspected when there are evident signs of an imminent failure. Maintenance is therefore performed at a random time, somehow dependent on the failure mechanism. A competing risk model, namely a Random Sign model, is considered to relate failure and maintenance times. We propose a novel Bayesian analysis of the model and apply it to actual data from a water pump in an oil refinery. The design of an optimal maintenance policy is then discussed under a formal decision theoretic approach, analyzing the goodness of the current maintenance policy and making decisions about the optimal maintenance time.

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  • Andrés Christen, J. & Ruggeri, Fabrizio & Villa, Enrique, 2011. "Utility based maintenance analysis using a Random Sign censoring model," Reliability Engineering and System Safety, Elsevier, vol. 96(3), pages 425-431.
    • Handle: RePEc:eee:reensy:v:96:y:2011:i:3:p:425-431
    DOI: 10.1016/j.ress.2010.11.001
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    References listed on IDEAS

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    Cited by:

    1. Antonio Pievatolo & Fabrizio Ruggeri & Refik Soyer & Simon Wilson, 2021. "Decisions in Risk and Reliability: An Explanatory Perspective," Stats, MDPI, vol. 4(2), pages 1-23, March.
    2. Márcio das Chagas Moura & Enrique López Droguett & Paulo Renato Alves Firmino & Ricardo José Ferreira, 2014. "A competing risk model for dependent and imperfect condition–based preventive and corrective maintenances," Journal of Risk and Reliability, , vol. 228(6), pages 590-605, December.
    3. Beate Sildnes & Bo Henry Lindqvist, 2018. "Modeling of semi-competing risks by means of first passage times of a stochastic process," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(1), pages 153-175, January.

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