Health management of industrial vehicles and fleet maintenance optimization : taking into account operation constraints and mission planning ; Gestion de l'état de santé de véhicules pour la maintenance de flotte : prise en compte des contraintes opérationnelles et optimisation conjointe des maintenances et des missions

This thesis work deals with the problems of joint scheduling for maintenance operations and missions for industrial vehicle fleets. The aim is to develop a methodology to adapt the joint scheduling of maintenance and missions according to the vehicles health state but also according to the missions features. These features correspond to the conditions of usage severity that have a significant impact on the truck deterioration and must be taken into account to adapt at best the maintenance operations schedule according to the deterioration evolution. The implementation of a decision support methodology to manage a fleet would improve productivity and reduce the maintenance costs while making the most of the fleet capacity. However, the joint scheduling problem for a fleet is a complex problem to solve and three main dimensions has to be considered. The first one is to jointly schedule missions and maintenance operations in a static case. The second one is to integrate the available monitoring information and the different events that can occur to update the schedule and treat the problem in a dynamic way. The third dimension is the fleet dimension that involves managing several vehicles in parallel.The first step is to jointly schedule the maintenance activity and the missions for a truck in a static case. It is assumed that all the missions to be performed are known and that no monitoring information is available. To do this, a vehicle deterioration model is defined to estimate its remaining useful lifetime to make decisions. It is a model with varying parameters since the vehicle operates under different conditions of usage severity according to the missions. It is the central point for setting up a scheduling algorithm to avoid any excessive risk of failure. The scheduling process is naturally optimized according to a criterion based on either the maintenance costs or the operating incomes.Once this methodology has been defined, it must be completed to include information on the vehicle deterioration, failure ...