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Determination of Pareto frontier in multi-objective maintenance optimization

机译:多目标维护优化中帕累托边界的确定

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The objective of a maintenance policy generally is the global maintenance cost minimization that involves not only the direct costs for both the maintenance actions and the spare parts, but also those ones due to the system stop for preventive maintenance and the downtime for failure. For some operating systems, the failure event can be dangerous so that they are asked to operate assuring a very high reliability level between two consecutive fixed stops. The present paper attempts to individuate the set of elements on which performing maintenance actions so that the system can assure the required reliability level until the next fixed stop for maintenance, minimizing both the global maintenance cost and the total maintenance time. In order to solve the previous constrained multi-objective optimization problem, an effective approach is proposed to obtain the best solutions (that is the Pareto optimal frontier) among which the decision maker will choose the more suitable one. As well known, describing the whole Pareto optimal frontier generally is a troublesome task. The paper proposes an algorithm able to rapidly overcome this problem and its effectiveness is shown by an application to a case study regarding a complex series-parallel system.
机译:维护策略的目标通常是最大程度地降低全局维护成本,这不仅涉及维护活动和备件的直接成本,还涉及由于系统停止进行预防性维护而导致的停机成本以及由于故障而导致的停机时间。对于某些操作系统,故障事件可能很危险,因此要求它们进行操作以确保在两个连续的固定停止之间具有很高的可靠性。本文尝试对在其上执行维护操作的元素集进行个性化设置,以便系统可以确保所需的可靠性级别,直到进行下一个固定维护为止,从而将总体维护成本和总维护时间最小化。为了解决先前受约束的多目标优化问题,提出了一种有效的方法来获得最佳解决方案(即帕累托最优边界),决策者将从中选择更合适的解决方案。众所周知,描述整个帕累托最优边界通常是一项麻烦的任务。本文提出了一种能够快速克服这一问题的算法,并通过将其应用于有关复杂串并联系统的案例研究中,证明了其有效性。

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