Joint optimization of condition-based performance control and maintenance policies for mission-critical systems

生存能力 可靠性工程 工作量 马尔可夫决策过程 控制(管理) 工程类 过程(计算) 运筹学 启发式 风险分析(工程) 马尔可夫过程 计算机科学 人工智能 数学 操作系统 统计 医学
作者
Xian Zhao,Zongda He,Yaguang Wu,Qingan Qiu
出处
期刊:Reliability Engineering & System Safety [Elsevier BV]
卷期号:226: 108655-108655 被引量:19
标识
DOI:10.1016/j.ress.2022.108655
摘要

The failure behavior of mission-critical systems typically depends on their performance levels, which provides opportunities to control deterioration by adjusting the performance levels. In addition to performance level selection, preventive maintenance decision is another factor affecting system survivability and mission success probability, providing a new train of thought for joint optimization of preventive maintenance and performance control for effective risk control of mission-critical systems. In existing research, mission-based maintenance and performance control decisions are seldom considered. This paper focuses on mission-critical systems and investigates the joint optimization of maintenance and performance control policies to balance mission success probability and system survivability based on the workload and system state. The problem is formulated as a Markov decision process and structural properties are analyzed to determine the optimal maintenance and performance control policies. The maintenance strategies exhibit a threshold structure, which strongly depends on the relationship between the performance level and the degradation process. For the purpose of comparison, the performance of several heuristic strategies is analytically evaluated. The example of the data transmission satellite network is given to demonstrate the superiority of the proposed strategies in reducing operations costs.

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