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Opportunistic group maintenance policy for multi-machine system with multi-components
Mishra A.K.,
Published in Curran Associates Inc.
Volume: 2018-December
Opportunistic maintenance (OM) models take the opportunity of economic dependencies among components in the system when it stops due to failure or scheduled preventive maintenance (PM) of a certain equipment. Performing maintenance actions simultaneously can substantially bring down the maintenance costs in terms of reduced downtime costs, production losses, service and labor costs, etc. However, maintaining all components together may be uneconomical due to over or underutilization. Secondly, most of the study on opportunistic maintenance consider the system comprising of either multi-machines with the single component or single machine with multi-components. Based on this motivation, the present paper proposes an effective opportunistic grouping policy for multi-component multi-machine system considering time-based imperfect PM actions. The imperfect PM addresses the most practical issue that PM does not always return the component to as-good-as-new status. To the best of our knowledge, this is the first attempt to develop the multi-machine OM policy with multi-components. The objective is to obtain an optimum group of components and PM times in order to minimize the total system maintenance cost per unit time during the mission. The opportunistic grouping model is based on the individual component’s PM intervals. Two grouping strategies viz. grouping within the machines and grouping between the machines are adopted in order to identify the diversity of the proposed model. A recently developed meta-heuristic named Jaya algorithm is applied to optimize the objective function. The effectiveness of the proposed model is analyzed with an illustrative example. Results reveal that the proposed model shows better economic performance as compared from the individual maintenance practices. © 2018, Curran Associates Inc. All rights reserved.
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Published in Curran Associates Inc.
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