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Maintien en conditions opérationnelles pour une flotte de véhicules : étude de la non stabilité des flux de rechange dans le temps

Abstract : This thesis gathers methodologicals contributions to simulate the need of replacement equipment for a vehile fleet. Systems degrade with age or use, and fail when they do not fulfill their mission. The user needs an assurance that the system is operational during its useful life. A support contract obliges the manufacturer to remedy a failure and to keep the system in operational condition for the duration of the MCO contract.The management of support contracts or the extension of support requires knowledge of the equipment lifetime and also the uses condition of vehicles, which depends on the customer. The analysis of customer returns or RetEx is then an important tool to help support the decision of the industrial. In reliability or warranty analysis, engineers must often deal with lifetimes data that are non-homogeneous. Most of the time, this variability is unobserved but has to be taken into account for reliability or warranty cost analysis.A further problem is that in reliability analysis, the data is heavily censored which makes estimations more difficult. We propose to consider the heterogeneity of lifetimes by a mixture and competition model of two Weibull laws. Unfortunately, the performance of classical estimation methods (maximum of likelihood via EM, Bayes approach via MCMC) is jeopardized due to the high number of parameters and the heavy censoring.To overcome the problem of heavy censoring for Weibull mixture parameters estimation, we propose a Bayesian bootstrap method, called Bayesian RestorationMaximization.We use an unsupervised clustering method to identify the profiles of vehicle uses. Our method allows to simulate the needs of spare parts for a vehicles fleet for the duration of the contract or for a contract extension.
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Submitted on : Wednesday, September 19, 2018 - 11:52:06 AM
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Florence Ducros. Maintien en conditions opérationnelles pour une flotte de véhicules : étude de la non stabilité des flux de rechange dans le temps. Statistiques [math.ST]. Université Paris-Saclay, 2018. Français. ⟨NNT : 2018SACLS213⟩. ⟨tel-01877087⟩

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