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Opportunistic maintenance scheduling with stochastic opportunities duration in a predictive maintenance strategy

机译:在预测性维护策略中具有随机机会持续时间的机会性维护计划

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To guarantee a good level of facilities performance (reliability and availability), maintenance activities have to be planned and scheduled efficiently. Maintenance scheduling decides, in a tactical way, when theses maintenance activities will be carried out according to the appearance of opportunities. Numerous works on opportunistic maintenance have been proposed in order to take profit of stochastic, structural and economic dependence. In the real context, the duration of an opportunity is not known accurately. Very few papers take into account the stochastic nature of opportunities duration. In this paper, we present an opportunistic maintenance scheduling methodology considering the stochastic nature of opportunities duration in a predictive maintenance strategy. The prognostic information is used to select opportunities coming before the failure. The proposed maintenance scheduling methodology is based on an optimal stopping problem algorithm known as Bruss algorithm. The originality of this paper is to consider the stochastic nature of opportunities duration using a Monte-Carlo simulation. A numerical study is finally presented to illustrate the use and the strengths of the proposed strategy.
机译:为了保证良好的设施性能水平(可靠性和可用性),必须有效地计划和安排维护活动。维护计划以战术方式根据机会的出现来决定何时进行这些维护活动。为了利用随机,结构和经济上的依赖,已经提出了许多关于机会性维护的工作。在实际情况下,机会的持续时间无法准确得知。很少有论文考虑机会持续时间的随机性。在本文中,我们提出了一种机会性维护计划方法,该方法考虑了预测性维护策略中机会持续时间的随机性。预后信息用于选择发生故障之前的机会。所提出的维护调度方法是基于称为Bruss算法的最佳停车问题算法。本文的独创性是使用蒙特卡洛模拟来考虑机会持续时间的随机性。最后进行了数值研究,以说明所提出策略的用途和优势。

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