Abstract
Motivated by the cost savings that can be obtained by sharing resources in a network context, we consider a stylized, yet representative, model for the coordination of maintenance and service logistics for a geographic network of assets. Capital assets, such as wind turbines in a wind park, require maintenance throughout their long lifetimes. Two types of preventive maintenance are considered: planned maintenance at periodic, scheduled opportunities, and opportunistic maintenance at unscheduled opportunities. The latter type of maintenance arises due to the network context: When an asset in the network fails, this constitutes an opportunity for preventive maintenance for the other assets in the network. So as to increase the realism of the model at hand and its applicability to various sectors, we consider the option of not-deferring and of deferring planned maintenance after the occurrence of opportunistic maintenance. We also assume that preventive maintenance may not always restore the condition of the system to ‘as good as new.’ By formulating this problem as a semi-Markov decision process, we characterize the optimal policy as a control limit policy (depending on the remaining time until the next planned maintenance) that indicates on the one hand when it is optimal to perform preventive maintenance and on the other hand when maintenance resources should be shared if an opportunity in the network arises. In order to facilitate managerial insights on the effect of each parameter on the cost, we provide a closed-form expression for the long-run rate of cost for any given control limit policy (depending on the remaining time until the next planned maintenance) and compare the costs (under the optimal policy) to those of suboptimal policies that neglect the opportunity for resource sharing. We illustrate our findings using data from the wind energy industry.
Highlights
High-value capital assets, such as energy systems, medical systems, lithography machines in semiconductor fabrication plants, and baggage handling systems at airports require maintenance throughout their lifetimes
We considered the maintenance policy for a three-state component degrading over time with corrective replacements at failures and preventive replacements at both scheduled and unscheduled opportunities under imperfect repair
By formulating this problem as a semi-Markov decision process, we were able to characterize the structure of the optimal maintenance policy as a control limit policy, where the control limit depends on the time until the planned maintenance opportunity
Summary
High-value capital assets, such as energy systems (for example, wind turbines), medical systems (for example, interventional X-ray machines), lithography machines in semiconductor fabrication plants, and baggage handling systems at airports require maintenance throughout their (long) lifetimes. In order to avoid or to minimize failures, asset owners perform preventive maintenance activities, with the objective to retain or to restore a system back to a satisfactory operating condition. The costs of both these maintenance activities, and of their respective unscheduled downtimes, represent one of the key drivers of an organization’s total costs. In the event that a failure occurs, its corrective maintenance instance can be viewed as an unscheduled opportunity for preventive maintenance for the other assets in the network. (v) When should preventive maintenance be performed (so as to minimize the longrun rate of cost)?
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