A hybrid condition-based maintenance policy for continuously monitored components with two degradation thresholds

Joeri Poppe, Robert Boute and Marc Lambrecht

No 537235, Working Papers of Department of Decision Sciences and Information Management, Leuven from KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven

Abstract: Condition-based maintenance (CBM) is a maintenance strategy that makes use of the actual condition (degradation level) of the component to decide when the maintenance and/or replacement of the component is executed, thereby maximising the lifetime of the machine, while minimising the number of maintenance interventions. In this paper, we combine CBM on one (monitored) component, with periodic preventive maintenance (PM) and corrective maintenance (CM) on the other components of the same machine/system. We implement two thresholds on the degradation level to decide when to service the monitored component: when the degradation level of the monitored component surpasses a first ’opportunistic’ threshold, the monitored component will be serviced together with the other components, for instance with a (planned) PM intervention, or upon breakdown of another component, requiring CM. In case none of these opportunities have taken place, and the degradation level surpasses a second ’intervention’ threshold, an additional maintenance intervention is planned for the monitored component in order to prevent a failure. Both thresholds are optimized to minimise the total expected maintenance costs of the monitored component, or to minimise the downtime of the machine due to maintenance on the monitored component. We perform an extensive numerical experiment to demonstrate the potential gains of this hybrid policy compared to using a traditional periodic PM policy, and we identify its key drivers of performance. We also benchmark our results when only one threshold is implemented. Our model is validated and applied at an OEM in the compressed air and generator industry.

Date: 2016-03
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Published in FEB Research Report KBI_1609

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