Robust Selective Maintenance under Imperfect Observations

Yu Liu (), Hong-Zhong Huang () and Tao Jiang ()
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Yu Liu: University of Electronic Science and Technology of China
Hong-Zhong Huang: University of Electronic Science and Technology of China
Tao Jiang: University of Electronic Science and Technology of China

Chapter Chapter 6 in Selective Maintenance Modelling and Optimization, 2023, pp 101-121 from Springer

Abstract: Abstract The traditional selective maintenance optimization models have been developed on the premise that the condition of components can be accurately inspected. Nevertheless, this basic assumption may not always hold due to the limited inspection ability and accuracy. This chapter develops a robust selective maintenance optimization model involving the uncertainty produced by imperfect observations. A multi-objective optimization model was formulated with the aims of maximizing the expectation and simultaneously minimizing the variance of a system successfully completing the next mission. Consequently, a set of non-dominated solutions can be identified. Two illustrative examples were presented to validate the advantages of the proposed robust selective optimization model.

Keywords: Selective maintenance; Imperfect maintenance; Uncertainty; Robustness; Multi-objective optimization (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-3-031-17323-3_6

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DOI: 10.1007/978-3-031-17323-3_6

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