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A sequential condition‐based repair/replacement policy with non‐periodic inspections for a system subject to continuous wear

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  • B. Castanier
  • C. Bérenguer
  • A. Grall

Abstract

This paper studies a condition‐based maintenance policy for a repairable system subject to a continuous‐state gradual deterioration monitored by sequential non‐periodic inspections. The system can be maintained using different maintenance operations (partial repair, as good as new replacement) with different effects (on the system state), costs and durations. A parametric decision framework (multi‐threshold policy) is proposed to choose sequentially the best maintenance actions and to schedule the future inspections, using the on‐line monitoring information on the system deterioration level gained from the current inspection. Taking advantage of the semi‐regenerative (or Markov renewal) properties of the maintained system state, we construct a stochastic model of the time behaviour of the maintained system at steady state. This stochastic model allows to evaluate several performance criteria for the maintenance policy such as the long‐run system availability and the long‐run expected maintenance cost. Numerical experiments illustrate the behaviour of the proposed condition‐based maintenance policy. Copyright © 2003 John Wiley & Sons, Ltd.

Suggested Citation

  • B. Castanier & C. Bérenguer & A. Grall, 2003. "A sequential condition‐based repair/replacement policy with non‐periodic inspections for a system subject to continuous wear," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 19(4), pages 327-347, October.
    • Handle: RePEc:wly:apsmbi:v:19:y:2003:i:4:p:327-347
    DOI: 10.1002/asmb.493
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    Cited by:

    1. Finkelstein, Maxim & Cha, Ji Hwan & Bedford, Tim, 2023. "Optimal preventive maintenance strategy for populations of systems that generate outputs," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    2. P Vrignat & M Avila & F Duculty & S Aupetit & M Slimane & F Kratz, 2012. "Maintenance policy: degradation laws versus hidden Markov model availability indicator," Journal of Risk and Reliability, , vol. 226(2), pages 137-155, April.
    3. Andriotis, C.P. & Papakonstantinou, K.G., 2021. "Deep reinforcement learning driven inspection and maintenance planning under incomplete information and constraints," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    4. Giorgio, Massimiliano & Pulcini, Gianpaolo, 2024. "The effect of model misspecification of the bounded transformed gamma process on maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    5. Yan, Tao & Lei, Yaguo & Wang, Biao & Han, Tianyu & Si, Xiaosheng & Li, Naipeng, 2020. "Joint maintenance and spare parts inventory optimization for multi-unit systems considering imperfect maintenance actions," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    6. T F Lipi & J-H Lim & M J Zuo & W Wang, 2012. "A condition- and age-based replacement model using delay time modelling," Journal of Risk and Reliability, , vol. 226(2), pages 221-233, April.
    7. Esposito, Nicola & Mele, Agostino & Castanier, Bruno & GIORGIO, Massimiliano, 2023. "A hybrid maintenance policy for a deteriorating unit in the presence of three forms of variability," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    8. Na, Kyumin & Yoon, Heonjun & Kim, Jaedong & Kim, Sungjong & Youn, Byeng D., 2023. "PERL: Probabilistic energy-ratio-based localization for boiler tube leaks using descriptors of acoustic emission signals," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    9. Andriotis, C.P. & Papakonstantinou, K.G., 2019. "Managing engineering systems with large state and action spaces through deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    10. Huynh, K.T., 2021. "An adaptive predictive maintenance model for repairable deteriorating systems using inverse Gaussian degradation process," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    11. Nguyen, Khanh T. P. & Do, Phuc & Huynh, Khac Tuan & Bérenguer, Christophe & Grall, Antoine, 2019. "Joint optimization of monitoring quality and replacement decisions in condition-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 177-195.

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