Structured Replacement Policies for Components with Complex Degradation Processes and Dedicated Sensors

• 成果类型: Article
• 署名作者: Elwany, Alaa H.; Gebraeel, Nagi Z.; Maillart, Lisa M.
• 署名单位: Eindhoven University of Technology; University System of Georgia; Georgia Institute of Technology; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.1110.0912
• 发表日期: 2011
• 页码: 684-695
• 关键词: condition-based maintenance; multistate deteriorating systems; residual-life distributions; geometric brownian-motion; to-failure distribution; periodic inspection; markov-chain; models; reliability; optimization

摘要

Failure of many engineering systems usually results from a gradual and irreversible accumulation of damage, a degradation process. Most degradation processes can be monitored using sensor technology. The resulting degradation signals are usually correlated with the degradation process. A system is considered to have failed once its degradation signal reaches a prespecified failure threshold. This paper considers a replacement problem for components whose degradation process can be monitored using dedicated sensors. First, we present a stochastic degradation modeling framework that characterizes, in real time, the path of a component's degradation signal. These signals are used to predict the evolution of the component's degradation state. Next, we formulate a single-unit replacement problem as a Markov decision process and utilize the real-time signal observations to determine a replacement policy. We focus on exponentially increasing degradation signals and show that the optimal replacement policy for this class of problems is a monotonically nondecreasing control limit policy. Finally, the model is used to determine an optimal replacement policy by utilizing vibration-based degradation signals from a rotating machinery application.