An optimal joint maintenance and mission abort policy for a system executing multi-attempt missions

IF 11 1区 工程技术 Q1 ENGINEERING, INDUSTRIAL
Sangqi Zhao , Yian Wei , Yang Li , Yao Cheng
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引用次数: 0

Abstract

Mission-critical systems are subject to deterioration-induced failures that induce not only mission failure cost but also system failure penalty. Deciding whether and when to abort the mission is crucial for overall cost minimization. When a mission’s success is evaluated in terms of the cumulative execution time and can be achieved by multiple attempts, operators can implement maintenance to increase the mission success probability. This calls upon the need to decide the system maintenance timing together with mission abort decisions, which is challenging due to not only the complex multi-layer interactions between these two decision variables but also the large state and action spaces. In this paper, we develop a Markov decision process (MDP) framework to determine the optimal system maintenance and mission abort timing. First, we propose a joint maintenance and mission abort policy that enables the operator to include the impact of the maintenance cost into decision-making and implement system maintenance and mission abort throughout the mission execution process, which thereby outperforms existing alternatives in overall cost minimization. Second, we develop an MDP-based optimization framework and analytically obtain the structural properties of the optimal policy, including the existence of the state-dependent control limits for system maintenance and mission abort decisions and their interdependence. Third, we develop an enhanced value iteration algorithm that exploits the developed structural properties to significantly improve the computational efficiency over the standard approach. The advantages of the proposed policy and algorithm are demonstrated by a case study of a UAV performing a surveillance mission.
多任务系统的最佳联合维护和任务中止策略
关键任务系统容易受到退化引起的故障的影响,这不仅会导致任务失效成本,还会导致系统失效惩罚。决定是否以及何时中止任务对总体成本最小化至关重要。当任务的成功以累积执行时间来评估,并且可以通过多次尝试来实现时,操作员可以实施维护以增加任务成功的概率。这就需要决定系统维护时间和任务中止决策,这不仅是由于这两个决策变量之间复杂的多层相互作用,而且是大的状态和行动空间。本文建立了一个马尔可夫决策过程框架来确定最优的系统维护和任务中止时机。首先,我们提出了一种联合维护和任务中止策略,使运营商能够将维护成本的影响纳入决策,并在整个任务执行过程中实施系统维护和任务中止,从而在总体成本最小化方面优于现有的替代方案。其次,我们建立了一个基于mdp的优化框架,并解析得到了最优策略的结构性质,包括系统维护和任务中止决策的状态依赖控制极限的存在性及其相互依赖性。第三,我们开发了一种增强值迭代算法,该算法利用开发的结构特性显著提高了标准方法的计算效率。通过对无人机执行监视任务的案例研究,验证了所提策略和算法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Reliability Engineering & System Safety
Reliability Engineering & System Safety 管理科学-工程:工业
CiteScore
15.20
自引率
39.50%
发文量
621
审稿时长
67 days
期刊介绍: Elsevier publishes Reliability Engineering & System Safety in association with the European Safety and Reliability Association and the Safety Engineering and Risk Analysis Division. The international journal is devoted to developing and applying methods to enhance the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to balance academic material and practical applications.
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