Selective Maintenance of Multi-Component Systems with Multiple Failure Modes

Cesar Ruiz, E. Pohl, H. Liao
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引用次数: 1

Abstract

In this paper, we develop a novel selective maintenance framework for optimizing the reliability or economic performance of a multi-component system subject to multiple failure modes. We classify the failure modes into soft failures and hard failures (possibly dependent). Soft failures are defined as occurring when a degradation process under condition monitoring surpasses a predefined threshold while hard failures are spontaneous failures that cannot be monitored. To optimize the system performance, different levels of maintenance actions on multiple components are considered. In particular, imperfect maintenance actions reduce the effective age and degradation level of a component while increasing the component’s frailty. We solve the optimization problem using standard Differential Evolution (DE) and Genetic Algorithm (GA) heuristics. A numerical example shows that the proposed selective maintenance framework provides an effective tool for making the optimal maintenance decisions by considering hard failures and the correlation among degradation processes.
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具有多种故障模式的多部件系统的选择性维护
在本文中,我们开发了一种新的选择性维护框架,用于优化多部件系统在多种故障模式下的可靠性或经济性能。我们将故障模式分为软故障和硬故障(可能依赖)。软故障被定义为在状态监测下的退化过程超过预定义的阈值时发生的故障,而硬故障是无法监测的自发故障。为了优化系统性能,考虑对多个组件进行不同级别的维护操作。特别是,不完善的维护行为减少了组件的有效寿命和退化水平,同时增加了组件的脆弱性。我们使用标准的差分进化(DE)和遗传算法(GA)启发式来解决优化问题。数值算例表明,所提出的选择性维修框架为考虑硬故障和退化过程之间的相关性,做出最优维修决策提供了有效的工具。
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