Modélisation et optimisation de la maintenance et de la surveillance des systèmes multi-composants - Applications à la maintenance et à la conception de véhicules industriels

摘要

This thesis research work focuses on the maintenance operations scheduling and the development of a design methodology for maintenance. The aim is to suggest a customized maintenance service offer for each vehicle and able to adapt to user constraints. In the transport industry, these constraints are defined by a limited number of maintenance opportunities and vehicle unplanned stops with significant financial consequences. This service offer should enable both to improve the vehicle uptime and to reduce the maintenance impact on operating costs. In this framework, the developed maintenance policy ensures, with a given risk probability, maintenance free operating periods for a multi-component system. During these periods, the system should be able to carry out all its assigned missions without maintenance actions and system fault. And the end of each period, the considered policy evaluates if a maintenance action is required to ensure maintenance-free and fault-free operation on the next period with a specified confidence level. When a maintenance action is mandatory, decision criteria considering the maintenance costs and the maintenance efficiency are used to select the operations to be performed. This form of dynamic clustering, called time-driven clustering, integrates both the component reliability models, the system structure and the available monitoring information. In our case, the monitoring information refers to the component state information and information on the component operating conditions. The process flexibility makes possible to make a maintenance decision in using different information levels for system components. The policy parameters, namely the period length and the confidence level value, are optimized based on the total maintenance cost. This cost, evaluated on a finite horizon, is composed of directs costs related to maintenance operations and indirect costs generated by system immobilizations. In order to reach a significant operating costs reduction, the maintenance policy optimization alone is not sufficient. It is essential to have a broader approach to involve the system and its maintenance since the conception. In this context, the developed design methodology suggests to prioritize the components impact on the operating costs. This prioritization is performed thanks to a defined importance factor. Then, multiple design options are evaluated by simulation in priority component. The selected options lead to reduce the operating costs. This work contains simulation results that illustrate the methods mentioned above. Moreover, a heavy vehicle sub-system is used as a test-case.