降级(电信)
计算机科学
过程(计算)
信号(编程语言)
组分(热力学)
马尔可夫决策过程
控制理论(社会学)
信号处理
马尔可夫过程
数学优化
控制(管理)
数学
人工智能
电信
统计
物理
雷达
热力学
程序设计语言
操作系统
作者
Alaa Elwany,Nagi Gebraeel,Lisa M. Maillart
出处
期刊:Operations Research
[Institute for Operations Research and the Management Sciences]
日期:2011-06-01
卷期号:59 (3): 684-695
被引量:141
标识
DOI:10.1287/opre.1110.0912
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI