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首页> 外文期刊>Reliability Engineering & System Safety >Dynamic opportunistic maintenance planning for multi-component redundant systems with various types of opportunities
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Dynamic opportunistic maintenance planning for multi-component redundant systems with various types of opportunities

机译：具有多种机会的多组件冗余系统的动态机会性维护计划

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摘要

Opportunistic maintenance (OM) is a key solution to reduce the maintenance costs or/and to improve the system dependability/performance. However, the existing OM models are mainly developed to specific classes of systems (series structures) with specific types of maintenance opportunities (MOs) such as component failure. The objective of this paper is to develop a dynamic OM approach for multi-component redundant systems such as parallel, parallel-series, series-parallel, and k-out-of-n, etc. Various types of MOs are also considered. To this purpose, a generalized MO model is firstly proposed for the modeling and formulation of existing MOs and new ones. A dynamic OM model with flexible decision rules allowing to consider various types of MOs in maintenance decision-making is then introduced. In addition, a multi-mode logistic support model is also proposed to better incorporate different types of MOs with associated logistic support requirements. To find the best OM scenario, an efficient optimization algorithm using Genetic algorithm with memory is developed. The proposed optimization algorithm allows also updating online an OM maintenance plan in presence of new MOs which may occur with time. The uses and advantages of the proposed OM approach are illustrated through a six-component redundant system.
机译：机会性维护（OM）是降低维护成本或/和/或提高系统可靠性/性能的关键解决方案。但是，现有的OM模型主要是针对具有特定类型的维护机会（MO）（例如组件故障）的特定类型的系统（系列结构）开发的。本文的目的是为多组件冗余系统（例如，并行，并行-串联，串联-并行和n-out-n等）开发一种动态OM方法。还考虑了各种类型的MO。为此，首先提出了一种通用的MO模型，用于对现有MO和新MO进行建模和表示。然后介绍了具有灵活决策规则的动态OM模型，该模型允许在维护决策中考虑各种类型的MO。此外，还提出了一种多模式后勤支持模型，以更好地将不同类型的MO与相关的后勤支持需求结合在一起。为了找到最佳的OM场景，开发了一种使用遗传算法和内存的高效优化算法。所提出的优化算法还允许在可能随时间推移出现新MO的情况下在线更新OM维护计划。通过六组件冗余系统说明了所建议的OM方法的用途和优点。

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