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Preventive Maintenance Interval Optimization for Continuous Multistate Systems

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  • Ruiying Li
  • Xufeng Zhang

Abstract

Preventive maintenance (PM), which is performed periodically on the system to lessen its failing probability, can effectively decrease the loss caused by the system breakdown or the performance degradation. The optimal PM interval has been well studied for both binary-state systems (BSSs) and discrete multistate systems (MSSs). However, in reality, the performance of many systems can change continuously, ranging from complete failure to perfect functioning. Considering such characteristics of systems, two types of performance-based measures, performance availability and probabilistic resilience, are addressed to quantify the system’s behaviour for continuous MSS. A Monte Carlo-based method is given to analyse the performance change process of the system, and an optimization framework is proposed to find the optimal PM interval with the considerations of per-unit-time cost, system breakdown rate, performance availability, and probabilistic resilience. A computer cluster is used as an example to illustrate the effectiveness of our proposed method.

Suggested Citation

  • Ruiying Li & Xufeng Zhang, 2020. "Preventive Maintenance Interval Optimization for Continuous Multistate Systems," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-10, January.
  • Handle: RePEc:hin:jnlmpe:2942940
    DOI: 10.1155/2020/2942940
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    Cited by:

    1. Sánchez-Herguedas, Antonio & Mena-Nieto, Angel & Rodrigo-Muñoz, Francisco, 2021. "A new analytical method to optimise the preventive maintenance interval by using a semi-Markov process and z-transform with an application to marine diesel engines," Reliability Engineering and System Safety, Elsevier, vol. 207(C).

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