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Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations

机译:选择性维护的优化,适用于串并联系统交替任务和随机工期的计划性休息

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摘要

This paper deals with the selective maintenance problem for a multi-component system performing consecutive missions separated by scheduled breaks. To increase the probability of successfully completing its next mission, the system components are maintained during the break. A list of potential imperfect maintenance actions on each component, ranging from minimal repair to replacement is available. The general hybrid hazard rate approach is used to model the reliability improvement of the system components. Durations of the maintenance actions, the mission and the breaks are stochastic with known probability distributions. The resulting optimisation problem is modelled as a non-linear stochastic programme. Its objective is to determine a cost-optimal subset of maintenance actions to be performed on the components given the limited stochastic duration of the break and the minimum system reliability level required to complete the next mission. The fundamental concepts and relevant parameters of this decision-making problem are developed and discussed. Numerical experiments are provided to demonstrate the added value of solving this selective maintenance problem as a stochastic optimisation programme.
机译:本文讨论了执行由计划的休息分隔的连续任务的多组件系统的选择性维护问题。为了增加成功完成下一个任务的可能性,在休息期间维护系统组件。列出了每个组件上潜在的不完善的维护措施,从最小的维修到更换。通用混合风险率方法用于对系统组件的可靠性改进进行建模。维护行动,任务和中断的持续时间是随机的,具有已知的概率分布。由此产生的优化问题被建模为非线性随机程序。它的目的是在给定的有限随机中断时间和完成下一个任务所需的最小系统可靠性级别的基础上,确定要在组件上执行的维护操作的成本最佳子集。制定并讨论了此决策问题的基本概念和相关参数。提供数值实验以证明解决此选择性维护问题的随机优化程序的附加价值。

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