Optimisation de la politique de maintenance pour un système à dégradation graduelle stressé

International audienceThis paper investigates a maintenance policy allowing the maintenance cost optimization per unit of time combining statistical process control (SPC) and condition-based maintenance (CBM) policy. We consider a single-unit system with two failure modes which can be partially explained by several covariates. Failure modes are a continuous-state deterioration and a stress. A CBM policy is used for inspecting and replacing the system in order to balance the impacts of an excessive deterioration level whereas a control a classical control chart is used to monitor the stress covariate. Sensitivity analysis based on numerical results is proposed

Predictive maintenance policy for a gradually deteriorating system subject to stress

International audienceThis paper deals with a predictive maintenance policy for a continuously deteriorating system subject to stress. We consider a system with two failure mechanisms which are, respectively, due to an excessive deterioration level and a shock. To optimize the maintenance policy of the system, an approach combining statistical process control (SPC) and condition-based maintenance (CBM) is proposed. CBM policy is used to inspect and replace the system according to the observed deterioration level. SPC is used to monitor the stress covariate. In order to assess the performance of the proposed maintenance policy and to minimize the long-run expected maintenance cost per unit of time, a mathematical model for the maintained system cost is derived. Analysis based on numerical results are conducted to highlight the properties of the proposed maintenance policy in respect to the different maintenance parameters

Optimisation de la politique de maintenance pour un système à dégradation graduelle stressé

International audienceThis paper investigates a maintenance policy allowing the maintenance cost optimization per unit of time combining statistical process control (SPC) and condition-based maintenance (CBM) policy. We consider a single-unit system with two failure modes which can be partially explained by several covariates. Failure modes are a continuous-state deterioration and a stress. A CBM policy is used for inspecting and replacing the system in order to balance the impacts of an excessive deterioration level whereas a control a classical control chart is used to monitor the stress covariate. Sensitivity analysis based on numerical results is proposed

POLITIQUES DE MAINTENANCE CONDITIONNELLE POUR UN SYSTEME A DEGRADATION CONTINUE SOUMIS A UN ENVIRONNEMENT STRESSANT

One of the challenges of maintenance optimisation is the development of decision-making models combining performance at the strategic level and at the operational level. A classic hypothesis is to consider that the degradation level of the system can be modelled by a stochastic process characterized in stationary state without taking into account the effects of the operating environment on the system. This hypothesis can be seen as one of the factors leading to gaps between expected performance and measured performance of maintenance policies. However, many works have been developed in the reliability field for the integration of the impact of these environmental conditions. The main objective of this manuscript is to develop maintenance decision tools for gradually deteriorating systems evolving in a stressful environment. First, we propose different ways to model the environment and its impact since it can directly influence the system failure or the degradation process. We express mutual relationships between environment and the degradation processes. Next, we propose and compare different adaptive maintenance policies which are based not only on the degradation level, but also on the stressful environment level. In addition, the proposed policies can be based either on an a priori knowledge of the system, or integrate the available online information on the environment. We will try throughout this manuscript to propose new maintenance approaches which combine theoretical expected performance on one side and operational reality and pragmatism on the other.L'un des challenges de l'optimisation de la maintenance est la production de modèles décisionnels conjuguant performance au niveau stratégique et au niveau opérationnel. Une hypothèse classique est de considérer que le niveau de dégradation du système peut être modélisé par un processus stochastique particulier caractérisé en régime stationnaire sans tenir compte des effets de l'environnement d'exploitation du système. Cette hypothèse peut être vue comme un des facteurs entraînant des écarts entre les performances attendues et celles mesurées. Par contre, de nombreux travaux sont développés dans le cadre de la fiabilité pour l'intégration de l'impact de l'environnement. L'objectif de ce manuscrit est de développer des outils d'aide à la décision de maintenance pour des systèmes à dégradation graduelle évoluant dans un environnement aléatoire stressant. Nous proposons différentes modélisations de l'environnement et de son impact sachant qu'il peut influencer soit la défaillance du système, soit le processus de dégradation. Nous explicitons les relations mutuelles entre l'environnement et le processus de dégradation et nous construisons différentes politiques de maintenance adaptatives qui se basent sur l'état de dégradation du système mais également sur l'évolution de l'environnement. De plus, les politiques proposées permettent de se baser soit uniquement sur une connaissance a priori du système, soit d'intégrer l'information disponible en ligne concernant l'environnement. Nous chercherons dans ce manuscrit à proposer de nouvelles approches de maintenance combinant performances théoriques attendues d'un côté et réalité et pragmatisme opérationnels d'un autre

Condition-based maintenance policies for multi-component systems with stochastic, structural and economic dependencies

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Politiques de maintenance conditionnelle pour un système à dégradation continue soumis à un environnement stressant

L un des challenges de l optimisation de la maintenance est la production de modèles décisionnels conjuguant performance au niveau stratégique et au niveau opérationnel. Une hypothèse classique est de considérer que le niveau de dégradation du système peut être modélisé par un processus stochastique particulier caractérisé en régime stationnaire sans tenir compte des effets de l environnement d exploitation du système. Cette hypothèse peut être vue comme un des facteurs entraînant des e carts entre les performances attendues et celles mesurées. Par contre, de nombreux travaux sont développés dans le cadre de la fiabilité pour l intégration de l impact de l environnement. L objectif de ce manuscrit est de développer des outils d aide à la décision de maintenance pour des systèmes à dégradation graduelle évoluant dans un environnement aléatoire stressant. Nous proposons différentes modélisations de l environnement et de son impact sachant qu il peut influencer soit la défaillance du système, soit le processus de dégradation. Nous explicitons les relations mutuelles entre l environnement et le processus de dégradation et nous construisons différentes politiques de maintenance adaptatives qui se basent sur l état de dégradation du système mais également sur l évolution de l environnement. De plus, les politiques proposées permettent de se baser soit uniquement sur une connaissance a priori du système, soit d intégrer l information disponible en ligne concernant l environnement. Nous chercherons dans ce manuscrit à proposer de nouvelles approches de maintenance combinant performances théoriques attendues d un côté et réalité et pragmatisme opérationnels d un autreOne of the challenges of maintenance optimisation is the development of decision-making models combining performance at the strategic level and at the operational level. A classic hypothesis is to consider that the degradation level of the system can be modelled by a stochastic process characterized in stationary state without taking into account the effects of the operating environment on the system. This hypothesis can be seen as one of the factors leading to gaps between expected performance and measured performance of maintenance policies. However, many works have been developed in the reliability field for the integration of the impact of these environmental conditions. The main objective of this manuscript is to develop maintenance decision tools for gradually deteriorating systems evolving in a stressful environment. First, we propose different ways to model the environment and its impact since it can directly influence the system failure or the degradation process. We express mutual relationships between environment and the degradation processes. Next, we propose and compare different adaptive maintenance policies which are based not only on the degradation level, but also on the stressful environment level. In addition, the proposed policies can be based either on an a priori knowledge of the system, or integrate the available online information on the environment. We will try throughout this manuscript to propose new maintenance approaches which combine theoretical expected performance on one side and operational reality and pragmatism on the otherNANTES-BU Sciences (441092104) / SudocSudocFranceF

Generalization of the proportional hazards model for maintenance modelling and optimization

International audienceA non-observable monotonically deteriorating system is considered. The observed data are the maintenance times and the kinds of maintenance performed. The aim of this paper is to propose a model of the dependency between all kinds of maintenance by considering imperfect maintenance efficiency. Furthermore, we present an additional planned preventive maintenance policy that reduces a finite horizon average total maintenance cost. To deal with such a problem a competing risks model is considered. A general class of models, denoted generalized proportional hazards, is presented and a particular model is derived. An estimation method is detailed for the proposed model. Finally, by numerical implementation, a maintenance policy that leads to the lowest finite horizon average total maintenance cost is proposed

Generalization of the proportional hazards model for maintenance optimization

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Combining statistical process control and condition-based maintenance for gradually deteriorating systems subject to stress

International audienc

Maintenance scheduling for multi-unit systems with hierarchical dependences

International audienceIn this paper, we consider the issue of multi-component systems with hierarchical dependences which is unexplored in literature. Complex systems often can be divided into several subsystems where dependences between components are non-symmetrical due to stronger dependences within subsystems than those between subsystems. The nested Levy copulas can be used in such a case. In addition, the economic dependence which provides grouping opportunities to reduce the maintenance cost is also considered. Five condition-based maintenance policies are proposed and evaluated to minimize the expected long-run maintenance cost