Computers and Operations Research
Numerical Recipes in C: The Art of Scientific Computing
Numerical Recipes in C: The Art of Scientific Computing
Determining the optimal production-maintenance policy with inspection errors: using a Markov chain
Computers and Operations Research
OPTIMALITY OF CONTROL LIMIT MAINTENANCE POLICIES UNDER NONSTATIONARY DETERIORATION
Probability in the Engineering and Informational Sciences
Optimal maintenance policies for systems subject to a Markovian operating environment
Computers and Industrial Engineering
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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.