Article ID: | iaor20117237 |
Volume: | 59 |
Issue: | 3 |
Start Page Number: | 684 |
End Page Number: | 695 |
Publication Date: | May 2011 |
Journal: | Operations Research |
Authors: | Maillart Lisa M, Elwany Alaa H, Gebraeel Nagi Z |
Keywords: | engineering, programming: markov decision |
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.