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A Markov decision process framework for optimal operation of monitored multi-state systems

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Listed:
  • Michele Compare
  • Paolo Marelli
  • Piero Baraldi
  • Enrico Zio

Abstract

We develop a decision support framework based on Markov decision processes to maximize the profit from the operation of a multi-state system. This framework enables a comprehensive management of the multi-state system, which considers the maintenance decisions together with those on the multi-state system operation setting, that is, its loading condition and configuration. The decisions are informed by a condition monitoring system, which estimates the health state of the multi-state system components. The approach is shown with reference to a mechanical system made up of components affected by fatigue.

Suggested Citation

  • Michele Compare & Paolo Marelli & Piero Baraldi & Enrico Zio, 2018. "A Markov decision process framework for optimal operation of monitored multi-state systems," Journal of Risk and Reliability, , vol. 232(6), pages 677-689, December.
    • Handle: RePEc:sae:risrel:v:232:y:2018:i:6:p:677-689
    DOI: 10.1177/1748006X18757077
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    References listed on IDEAS

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    6. Zio, Enrico & Compare, Michele, 2013. "Evaluating maintenance policies by quantitative modeling and analysis," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 53-65.
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