Selective maintenance scheduling over a finite planning horizon. (April 2016)

• Record Type: Journal Article
• Authors: Pandey, Mayank; Zuo, Ming J; Moghaddass, Ramin
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 230:Number 2(2016:Apr.)
• Page Start: 162
• Page End: 177
• Publication Date: 2016-04
• Subjects: Preventive maintenance -- selective maintenance -- periodic scheduling -- imperfect maintenance -- evolutionary algorithm; Reliability (Engineering) -- Mathematical models -- Periodiclals; Risk assessment -- Mathematical models -- Periodicals; Engineering design -- Mathematical models -- Periodicals; 620.00452
• DOI: 10.1177/1748006X15598914
• Languages: English
• ISSNs: 1748-006X

Abstract

A preventive maintenance scheduling model is proposed in this article. The proposed model includes finite planning horizon and limited available resources to perform maintenance scheduling. A subset of maintenance actions, that is, selective maintenance is needed during maintenance breaks due to limited resources such as time, cost, and repairman availability. Maintenance can not only improve the effective age of a component but also may alter the hazard rate. Therefore, a hybrid imperfect maintenance model is used in this article that considers the combined effect of age reduction and hazard adjustment on a component. For a multi-component system, selective maintenance is performed at periodic intervals. In addition to maintenance and failure costs, we have included the maintenance break duration and the shutdown cost in the proposed scheduling model. A periodic maintenance scheduling problem is solved in this article for a series–parallel system. The optimal number of periodic maintenance breaks in a finite planning horizon is determined. Also, maintenance actions required during each of the maintenance breaks are determined. The number of periodic maintenance breaks and maintenance actions during these breaks is selected in a way that the total maintenance, failure, and shutdown cost are minimum. An evolutionary algorithm is used to solve the problem.