Simulation-based Reliability Evaluation of Maintenance the Efficiency of A Repairable System

  The aim of this paper is to study the asymptotic behavior of the Arithmetic Reduction of Intensity (ARI) and Arithmetic Reduction of Age (ARA) models as two imperfect maintenance models. These models have been proposed by Doyen & Gaudoin (2011), the failure process with bathtub failure intensity. The maintenance effect is characterized by the change induced by the failure intensity before and after a failure during the degradation period. To simplify the study, the asymptotic properties of the failure process are derived. Then, the asymptotic normality of several maintenance efficiency estimators can be proved in the case where the failure process without maintenance is known. Practically, the coverage rate of the asymptotic confidence intervals issued from those estimators is studied

Ferramenta Automática para Avaliação da Fiabilidade e Disponibilidade de Sistemas Reparáveis

Nesta dissertação apresentam-se as contribuições de um trabalho de investigação que tem como objetivo o desenvolvimento e implementação de uma ferramenta automática que disponibiliza, quase em tempo real, indicadores de fiabilidade e de disponibilidade para um qualquer sistema reparável. A ferramenta recebe dados recolhidos no equipamento em estudo, modela o processo gerador das avarias por recurso a vários modelos matemáticos/estatísticos, seleciona o modelo mais adequado aos dados recolhidos e, como base nesse modelo, apresenta um conjunto de indicadores úteis. Estes indicadores podem ser usados, tanto para prever o comportamento do sistema, como para avaliar como é que este responde a ações externas, como, por exemplo, à respetiva manutenção. Os trabalhos são iniciados com uma revisão dos conceitos e instrumentos fundamentais que suportam, grosso modo, o trabalho desenvolvido, seguindo-se o desenho, implementação e validação da ferramenta. A ferramenta é desenvolvida em ambiente Python e de forma automática. Este automatismo facilita a obtenção de resultados em tempo quase real e permite que o perito do processo tenha acesso a um conjunto de indicadores do estado do sistema sem que tenha conhecimentos específicos sobre modelação de processo geradores de avarias. O resumo dos dados recolhidos, assim como a informação produzida pela ferramenta desenvolvida são apresentados de forma organizada através de um dashboard, também desenvolvido em ambiente Python, de forma que a interpretação dos resultados seja mais rápida e eficiente.This dissertation presents the contributions of a research work that aims to develop and implement an automatic tool that provides, almost in real time, reliability, and availability indicators for any repairable system. The tool receives data collected from the equipment, models the process that generates the faults using various mathematical/statistical models, selects the most appropriate model for the data collected and based on that model, presents a set of useful indicators. These indicators can be used both to predict the behavior of the system and to assess how it responds to external actions, such as, for example, its maintenance. The work begins with a review of the fundamental concepts and instruments that roughly support the work developed, followed by the design, implementation, and validation of the tool. The tool is developed in a Python environment and automatically. This automatism facilitates obtaining results in near real time and allows the process expert to have access to a set of system status indicators without having specific knowledge about modeling fault-generating processes. The summary of the collected data, as well as the information produced by the developed tool, are presented in an organized way through a dashboard, also developed in a Python environment, so that the interpretation of the results is faster and more efficient

Analytical properties of an imperfect repair model and application in preventive maintenance scheduling

International audienceThe paper considers repairable systems under imperfect repair. The failure rate of a new system is assumed to follow a Weibull distribution and the repair efficiency is characterized by a Kijima type II virtual age model named Arithmetic Reduction of Age with infinite memory. An analytical approach to obtain the distribution of the inter-failure times is presented. The existence of a stationary regime is highlighted and the limiting distributions are explicitly derived. In this context, an optimal age-based preventive maintenance policy can be implemented. Three approaches are proposed, considering a static, a dynamic or a failure limit policy. Numerical simulations are presented to illustrate the policies