间歇可及性下退化资产的状态维修

中文摘要 AI 辅助

许多维修模型隐含地假设，只要需要干预，就可以随时进行维修。然而，在实践中，环境不确定性（如天气和海况）可能使维修机会变得间歇性且动态演变。我们考虑一种退化资产，其预防性维修可在故障发生前进行，但只有在资产可及（accessible）时才能进行干预。可及性随时间随机演变，因此不仅影响当前能否进行维修，也影响等待未来机会的价值。我们将此问题建模为长期平均成本准则下的有限状态马尔可夫决策过程，并研究最优维修策略的结构。在单调退化和成本条件下，我们证明最优策略在资产状态上保持阈值形式，但与单一阈值不同，最优阈值随可及性状态而变化。因此，干预决策同时取决于资产状态和未来维修机会的预期演变。通过一项受海上风电机组维修启发的数值研究，我们考察了可及性动态、退化特征和经济参数如何影响最优阈值，并将最优策略与恒定阈值和基于机龄的维修策略进行比较。在一个代表性场景中，将状态阈值适应可及性相比优化的状态维修策略可将长期平均成本降低4.31%。相对于优化的基于机龄的策略，最优策略可将长期平均成本降低33.95%。结果表明，维修阈值并非普遍适用：它们应适应系统的退化和可及性特征，若不考虑这些条件，可能导致成本大幅增加。

英文摘要

Many maintenance models implicitly assume that maintenance can be performed whenever intervention is warranted. In practice, however, environmental uncertainty, such as weather and sea conditions, can make maintenance opportunities intermittent and dynamically evolving. We consider a degrading asset for which preventive maintenance may be performed before failure, but intervention is possible only when the asset is accessible. Accessibility evolves stochastically over time and therefore affects not only whether maintenance can be performed now, but also the value of waiting for future opportunities. We formulate this setting as a finite-state Markov decision process under a long-run average cost criterion and investigate the structure of the optimal maintenance policy. Under monotone degradation and cost conditions, we show that an optimal policy retains a threshold form in asset condition, but unlike a single threshold, the optimal threshold varies with the accessibility state. Thus, intervention depends jointly on the asset condition and the expected evolution of future maintenance opportunities. Through a numerical study motivated by offshore wind turbine maintenance, we examine how accessibility dynamics, degradation characteristics, and economic parameters shape the optimal thresholds and compare the optimal policy with constant-threshold and age-based maintenance policies. In a representative setting, adapting the condition threshold to accessibility reduces long-run average cost by 4.31% relative to an optimized condition-based maintenance policy. Relative to an optimized age-based policy, the optimal policy reduces long-run average cost by 33.95%. The results show that maintenance thresholds are not universal: they should adapt to the degradation and accessibility characteristics of the system, and failing to account for these conditions can lead to substantial cost increases.

发表机构

• Wayne State University（韦恩州立大学）
• University of Groningen（格罗宁根大学）

机构由 AI 辅助整理，请以论文原文为准。