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Motivated by the cost savings that can be obtained by sharing resources in anetwork context, we consider a stylized, yet representative model, for thecoordination of maintenance and service logistics for a geographic network ofassets. Capital assets, such as wind turbines in a wind park, requiremaintenance throughout their long lifetimes. Two types of preventivemaintenance are considered: planned maintenance at periodic, scheduledopportunities, and opportunistic maintenance at unscheduled opportunities. Thelatter type of maintenance arises due to the network context: when an asset inthe network fails, this constitutes an opportunity for preventive maintenancefor the other assets in the network.  So as to increase the realism of the model at hand and its applicability tovarious sectors, we consider the option of not-deferring and of deferringplanned maintenance after the occurrence of opportunistic maintenance. We alsoassume that preventive maintenance may not always restore the condition of thesystem to `as good as new'. By formulating this problem as a semi-Markovdecision process, we characterize the optimal policy as a control limit policy(depending on the remaining time until the next planned maintenance) thatindicates on the one hand when it is optimal to perform preventive maintenanceand on the other hand when maintenance resources should be shared if anopportunity in the network arises. In order to facilitate managerial insightson the effect of each parameter on the cost, we provide a closed-formexpression for the long-run rate of cost for any given control limit policy(depending on the remaining time until the next planned maintenance) andcompare the costs (under the optimal policy) to these of sub-optimal policiesthat neglect the opportunity for resource sharing. We illustrate our findingsusing data from the wind energy industry.

Condition based maintenance policies under imperfect maintenance at scheduled and unscheduled opportunities