Optimizing selective maintenance problem in mission-oriented systems under repairpersons availability

Mission-oriented industrial systems are designed to operate a sequence of alternate missions and scheduled breaks. During breaks, maintenance tasks are usually carried out to improve the system's performance for the next missions. Given the limited length of breaks as well as other maintenance resources, only a subset of components set can be maintained. Therefore, there is a need to select components to maintain in order to meet the required performance of the system during the next mission. This maintenance strategy is referred to in the literature as the selective maintenance problem (SMP). The existing selective maintenance models assume that repairpersons are always available to carry out their tasks. The present work aims to relax this assumption and to develop a novel SMP formulation for mission-oriented systems under a planing horizon composed of several missions. Genetic algorithm is used to solve the resulting integrated non-linear programming model. To show the validity and the accuracy of the proposed approach, numerical experiments are provided. The results obtained indeed show that taking into account repairpersons availability impacts both the selective maintenance and repairpersons assignment decisions, while ensuring good estimation of the system reliability