A model for determining condition-based maintenance policies for deteriorating multi-component systems

We discuss a method to determine strategies for preventive maintenance of systems consisting of gradually deteriorating components. A model has been developed to compute not only the range of conditions inducing a repair action, but also inspection moments based on the last known condition value so as to minimize expected costs per time unit. ln our cost optimization, we include costs of inspection, repair, failure and operation, while accounting for savings that can be obtained by combining inspection or repair of two or more components. Deterioration is modelled as a stochastic process; an independence assumption allows us to model the decision problem as a (semi-)Markov decision process. The solution procedure for the system as a whole is a heuristic one as we use only aggregate information about the other components while determining a maintenance strategy for a particular component. This strategy is of the opportunistic control-limit type: upper limits induce mandatory actions, lower limits allow anticipatory action if a combination with a mandatory action on at least one other component is possible. ln this paper we describe the principles of this heuristic. We show how other performance indicators can be calculated besides costs and give a numerical example of a system of components made of concrete

Optimum condition-based maintenance policies for deteriorating systems with partial information

Systems are considered which deteriorate as time goes on and whose conditions can be observed. The optimum maintenance policy with respect to cost is determined, based on a continuous deterioration process, by formulating the decision process as a discrete Markov decision problem. Examples from the field of civil engineering are given. The relation between the type of deterioration and condition-based optimum inspection intervals, optimum repair level, minimum average maintenance costs and mean time to repair is shown, using some numerical results. © 1996 Elsevier Science Limited

A spare parts model with cold stand-by redundancy on system level

This paper presents a variant of a spare parts inventory model with cold stand-by redundancy on system level. Redundancy on system level implies that not all systems need to be operational in order to have the whole system operational. The cold stand-by feature implies that only the minimum required systems are operational. In order to determine a cost effective spare parts package such that in a cold stand-by redundancy situation a sufficient number of systems is operational for a specified period we extend the METRIC methodology. To compute the probability that the number of operating systems during the operational period is sufficient, we present both an exact, but time-consuming method, and a fast approximation method based on fitting distributions on the first two moments. This approximation method shows very small differences when compared to the exact method. Finally, we compare both methods to a simulation model in order to test the validity and impact of our modelling