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Utility-Based Maintenance Optimization for Complex Water-Distribution Systems Using Bayesian Networks

机译:利用贝叶斯网络的基于实用程序的复杂水分配系统维护优化

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摘要

Water supply systems (WSS), as well as other real-world systems, are characterized by complex configurations. For these systems, it is essential to ensure appropriate utility through optimal maintenance planning. The difficulties in decision-making are much increased by lack of information regarding the operation and failure conditions. When maintenance optimization is considered for systems configured as networks, comprising a large number of components, the main challenge is to model the reliability characteristics, such as availability, taking account of the interactions and dependencies between different components. The aim of this paper is to provide an optimal Preventive Maintenance (PM) plan with a view to maximizing the utility of a complex repairable system using Bayesian Networks (BNs). For each node of the BN, the optimal PM periodicity is obtained, in accordance with the policy of periodic imperfect PM with minimal repair at failure. The system availability is then computed, by Bayesian inference, for various combinations of nodes, or subsystems, periodicities and partial renewals before the complete renewal of the whole system. A utility function is then introduced to provide the maintenance plan for the system, leading to the implementation of the best policy. The methodology is illustrated by numerical application on WSS.
机译:供水系统(WSS)以及其他实际系统的特点是配置复杂。对于这些系统,至关重要的是通过最佳的维护计划来确保适当的实用性。由于缺乏有关操作和故障情况的信息,决策难度大大增加。当考虑对配置为网络的系统(包括大量组件)进行维护优化时,主要挑战是对可靠性特征(例如可用性)进行建模,同时考虑不同组件之间的交互作用和依赖性。本文的目的是提供最佳的预防性维护(PM)计划,以最大程度地利用贝叶斯网络(BN)来解决复杂的可修复系统的问题。对于BN的每个节点,根据周期不完善的PM的策略获得了最佳的PM周期,故障修复最少。然后,通过贝叶斯推断,在整个系统完全更新之前,针对节点或子系统,周期性和部分更新的各种组合,计算系统可用性。然后引入了实用程序功能来为系统提供维护计划,从而实施最佳策略。通过在WSS上的数值应用来说明该方法。

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