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A robust mean cumulative function estimator and its application to overhaul time optimization for a fleet of heterogeneous repairable systems

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  • Jiang, Renyan
  • Li, Fengping
  • Xue, Wei
  • Cao, Yu
  • Zhang, Kunpeng

Abstract

Reliability of a fleet of nominally identical repairable systems is usually modeled by a failure point process with a mean cumulative function (MCF). It is found that the Nelson estimator of MCF is not robust in the right tail of the function when the systems have different censoring times. Since the systems often operate in different use conditions and environments, the reliability characteristics of individual systems are different. That is, the fleet can be heterogeneous. The existing methods to model the heterogeneity are population-oriented and involve too many model parameters. As a result, most of existing reliability models do not consider the heterogeneity. This can result in large uncertainties in reliability prediction and maintenance decision. This paper aims to address these issues. The concept of fleet equivalent operating time is introduced and a robust MCF estimator is proposed; a measure is developed for evaluating the fleet's heterogeneity; an overhaul policy with two control limits is defined, a non-parametric objective function is developed and a curve-fitting approach is proposed to obtain optimal policy parameters. Four examples are included to illustrate the proposed methods and their appropriateness.

Suggested Citation

  • Jiang, Renyan & Li, Fengping & Xue, Wei & Cao, Yu & Zhang, Kunpeng, 2023. "A robust mean cumulative function estimator and its application to overhaul time optimization for a fleet of heterogeneous repairable systems," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    • Handle: RePEc:eee:reensy:v:236:y:2023:i:c:s0951832023001801
    DOI: 10.1016/j.ress.2023.109265
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