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Condition-based maintenance for long-life assets with exposure to operational and environmental risks

机译:基于条件的长寿命维护,具有风险和环境风险的风险

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摘要

This paper presents a new condition-based maintenance (CBM) model for long-life assets to address the potential risk caused by the decline of the operating environment. Two types of maintenance are formulated in the CBM model. Minor maintenance can mitigate the operational and environmental risk, and major maintenance can eliminate the accumulated damage within the asset. A continuous-time semi-Markov chain (CTSMC) is used for modeling the aging of the asset as well as the stochastic decline of the operating environment. To optimize the CBM policy in a mathematically tractable manner, we introduce a hypo-exponential approximation approach to match the first four moments of the sojourn time distribution of CTSMC. This approach guarantees a minimum representation of the CTSMC with non-fictitious surrogated Markov chain. The model provides both good mathematical tractability and sufficient generalizability. The practical impact of this research is demonstrated by applying it to a real industrial case of concrete bridge maintenance. It is observed that this approach results in a CBM plan with a lower asset lifecycle cost compared to current techniques.
机译:本文介绍了一种新的基于条件的维护(CBM)模型,用于长寿命资产,以解决经营环境衰落的潜在风险。在CBM模型中配制了两种维护。轻微的维护可以减轻操作和环境风险,主要的维护可以消除资产内的累积损坏。连续时间半马尔可夫链(CTSMC)用于建模资产老化以及操作环境的随机衰退。为了以数学上易行的方式优化CBM策略,我们介绍了一种低指数近似方法,以匹配CTSMC的测定时间分布的前四个时刻。这种方法保证了CTSMC与非虚拟代理马尔可夫链的最低代表性。该模型提供了良好的数学途径和足够的相互性。通过将其应用于混凝土桥维护的真正工业案例,证明了这项研究的实际影响。观察到,与当前技术相比,该方法产生了较低的资产生命周期成本的CBM计划。

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