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A condition-based maintenance policy for continuously monitored multi-component systems with economic and failure dependence

Lookup NU author(s): Dr Jordan Oakley, Professor Kevin Wilson, Dr Pete PhilipsonORCiD

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

In this paper we propose a condition-based maintenance policy for continuously monitored multi-component systems subject to failure dependence through load sharing and economic dependence throughmaintenance set-up costs. Failure dependence provides an incentive to replace failed components as soonas possible, since component failures increase the load, and hence the deterioration rates, of the remainingcomponents. In contrast, economic dependence encourages the clustering of component replacements toreduce maintenance frequency, resulting in less downtime and fewer maintenance set-up costs. In thispaper, we propose a novel, condition-based maintenance policy to obtain the optimal replacement decisions at maintenance opportunities. Through numerical studies we see the importance of a policy thatincorporates both types of system dependence. The policy incorporates a utility/reward function that isa combination of interpretable penalties that encapsulate the costs of failure and economic dependence.The utility function trades off the rewards of clustering components with the loss due to load sharing.The policy minimizes the overall cost of the system by choosing actions that minimize the total long-termpenalty. We show that the proposed policy outperforms various alternative policies by reducing systemlife-cycle costs.


Publication metadata

Author(s): Oakley JL, Wilson KJ, Philipson P

Publication type: Article

Publication status: Published

Journal: Reliability Engineering and System Safety

Year: 2022

Volume: 222

Print publication date: 01/06/2022

Online publication date: 05/02/2022

Acceptance date: 10/01/2022

Date deposited: 10/01/2022

ISSN (print): 0951-8320

ISSN (electronic): 1879-0836

Publisher: Elsevier

URL: https://doi.org/10.1016/j.ress.2022.108321

DOI: 10.1016/j.ress.2022.108321

ePrints DOI: 10.57711/s4sk-5q33


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