Maintenance decision rule with embedded online Bayesian change detection for gradually non-stationary deteriorating systems

International audienceThe aim of a condition-based maintenance policy is to manage the available online information about a component or a (sub)system, usually its degradation level, in order to improve the maintenance decision-making. This paper tackles the problem of maintenance decision rules for stochastically deteriorating systems that are subject to changes of their degradation rate during a life cycle. A well-suited control-limit maintenance decision rule is considered with an embedded online change detection algorithm. The maintenance decision and change detection parameters are optimized with respect to the same global maintenance cost and according to the available information about the degradation process. The obtained policy is compared with more classical control limit condition-based maintenance policies without online change detection. The use of the embedded online detection algorithm shows its efficiency especially for systems subject to significantly different degradation rates