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Robust Selective Maintenance under Imperfect Observations

In: Selective Maintenance Modelling and Optimization

Author

Listed:
  • 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)

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.

Suggested Citation

  • Yu Liu & Hong-Zhong Huang & Tao Jiang, 2023. "Robust Selective Maintenance under Imperfect Observations," Springer Series in Reliability Engineering, in: Selective Maintenance Modelling and Optimization, chapter 0, pages 101-121, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-17323-3_6
    DOI: 10.1007/978-3-031-17323-3_6
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