Opportunistic maintenance scheduling with stochastic opportunities duration in a predictive maintenance strategy

Abstract

To guarantee a good level of facilities performance (reliability and availability), maintenance activities have to be planned and scheduled efficiently. Maintenance scheduling decides, in a tactical way, when theses maintenance activities will be carried out according to the appearance of opportunities. Numerous works on opportunistic maintenance have been proposed in order to take profit of stochastic, structural and economic dependence. In the real context, the duration of an opportunity is not known accurately. Very few papers take into account the stochastic nature of opportunities duration. In this paper, we present an opportunistic maintenance scheduling methodology considering the stochastic nature of opportunities duration in a predictive maintenance strategy. The prognostic information is used to select opportunities coming before the failure. The proposed maintenance scheduling methodology is based on an optimal stopping problem algorithm known as Bruss algorithm. The originality of this paper is to consider the stochastic nature of opportunities duration using a Monte-Carlo simulation. A numerical study is finally presented to illustrate the use and the strengths of the proposed strategy.