Selective Maintenance Optimization Under Uncertainties

Yu Liu (), Tangfan Xiahou and Tao Jiang
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Yu Liu: University of Electronic Science and Technology of China
Tangfan Xiahou: University of Electronic Science and Technology of China
Tao Jiang: University of Electronic Science and Technology of China

A chapter in Multicriteria and Optimization Models for Risk, Reliability, and Maintenance Decision Analysis, 2022, pp 487-508 from Springer

Abstract: Abstract Due to limited maintenance resources, such as budget, time, and manpower, selective maintenance has widespread applications in both industry and military environments. By a selective maintenance strategy, a subset of feasible maintenance actions for a repairable system can be selected to be performed so as to ensure the success of the subsequent mission. However, in engineering practices, various uncertainties are inevitable in selective maintenance. This chapter offers a comprehensive review on the existing selective maintenance models under uncertainties. Additionally, as complements to the existing models, two new selective maintenance models by taking account of the uncertainty associated with the durations of breaks and maintenance actions and the uncertainty associated with imperfect observations are put forth. Two illustrative examples are presented to demonstrate the effectiveness of the proposed models.

Keywords: Selective maintenance; Limited maintenance resources; Uncertainty; Maintenance optimization (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-3-030-89647-8_23

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