Abstract
The paper describes decision making about monitoring and maintenance of systems described by a general stochastic process. The system is monitored and preventive and corrective maintenance actions are carried out in response to the observed system state. The decision process is simplified by using an associated process as well as the underlying state as decision variables. The bivariate approach allows a wide class of models to be considered including long term memory within a simple probability structure. Both average cost and life-cycle cost models are used as the basis for decision making. The models generalize age replacement and other simple maintenance strategies. The approach can deal with failures that prevent the system functioning further, failures defined by regulation, or by economic considerations. The unified framework developed allows the inclusion of covariates and imperfect inspection or repair.
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