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Modeling, simulation and optimization of maintenance cost aspects on multi-unit systems by stochastic Petri nets with predicates

机译:随机培养网与谓词多单位系统维护成本方面的建模,仿真与优化

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The paper addresses repairable multi-unit systems with a series-parallel configuration for which maintenance strategies are modeled by generalized stochastic Petri nets (GSPN) with predicates coupled with Monte Carlo simulation. Four maintenance strategies consisting of basic periodic preventive and corrective maintenance, and both combined with opportunistic maintenance (OM) strategies, are considered. Failure and repair distributions of the system components are independent, and repairs are considered to be perfect. Times to failure of degraded components follow a Weibull distribution with increasing failure rate over time. The maintenance strategies are optimized so as to minimize the total maintenance costs of the system while maximizing availability. A comparison is drawn between OM and non-OM. The aim is to show that GSPN with predicates, in combination with Monte Carlo simulation, is a powerful, flexible, efficient, and intuitive approach for modeling and optimizing practical maintenance strategies on multi-unit complex systems, modeling the dynamic behavior resulting from the interaction between system components and economic dependencies. The merits and advantages of GSPN coupled with Monte Carlo simulation are enhanced relative to other, analytical, approaches.
机译:该纸张涉及具有系列并行配置的可修复的多单元系统,该配置是由普通的随机Petri网(GSPN)建模的维护策略,其中谓词耦合与蒙特卡罗模拟。四项维护策略包括基本定期预防和纠正性维护,以及与机会主义维护(OM)策略组成。系统组件的故障和修复分布是独立的,并且认为维修是完美的。减少组件失效的时间遵循Weibull分布随着时间的推移而增加的失败率。维护策略经过优化,以最大限度地减少系统的总维护成本,同时最大限度地提高可用性。在OM和非OM之间绘制比较。目的是表明,与蒙特卡罗模拟结合谓词的GSPN是一种强大,灵活,高效,直观的建模和优化了多单元复杂系统的实用维护策略,建模了互动产生的动态行为系统组件与经济依赖关系之间。 GSPN与Monte Carlo模拟的优点和优点相对于其他,分析,方法增强。

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