可变冲击与自愈模式下的最优更换策略
An optimal replacement policy under variable shocks and self-healing patterns
AI总结：
研究受微机电系统启发的退化与自愈系统，提出在可变冲击模式下的预防性维护更换策略，通过比较不同自愈变体的最优更换时间，为通用系统设置提供决策支持。
摘要：
我们研究了一个在随机间隔下经历破坏性外部冲击、连续退化和自愈的系统。该系统的动机来源于基于微机电系统（MEMS）的实际应用。如果累积损伤超过随时间变化的阈值，系统就会失效。我们制定了一种预防性维护策略来更换系统，以使其寿命得到谨慎利用。此外，还考虑了自愈模式的三种变体：(i) 冲击在固定持续时间 $τ$ 内自愈；(ii) 固定比例的冲击不可自愈（即 $τ=0$）；(iii) 存在两种类型的冲击——可自愈冲击在有限持续时间内自愈，不可自愈冲击则造成随机系统退化。我们实施了所提出的预防性维护策略，并将这些新情况下的最优更换时间与所有冲击均无限期自愈的原始情况进行比较，从而使系统管理者能够在通用系统设置中做出必要决策。
英文摘要：
We study a system that experiences damaging external shocks at stochastic intervals, continuous degradation, and self-healing. The motivation for such a system comes from real-life applications based on micro-electro-mechanical systems (MEMS). The system fails if the cumulative damage exceeds a time-dependent threshold. We develop a preventive maintenance policy to replace the system such that its lifetime is prudently utilized. Further, three variations on the healing pattern have been considered: (i) shocks heal for a fixed duration $τ$; (ii) a fixed proportion of shocks are non-healable (that is, $τ=0$); (iii) there are two types of shocks -- self healable shocks heal for a finite duration, and nonhealable shocks inflict a random system degradation. We implement a proposed preventive maintenance policy and compare the optimal replacement times in these new cases to that of the original case where all shocks heal indefinitely and thereby enable the system manager to take necessary decisions in generalized system set-ups.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
