Selective maintenance scheduling over a finite planning horizon
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 lim...
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| Veröffentlicht in: | Proceedings of the Institution of Mechanical Engineers. Part O, Journal of risk and reliability Journal of risk and reliability, 2016-04, Vol.230 (2), p.162-177 |
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| container_title | Proceedings of the Institution of Mechanical Engineers. Part O, Journal of risk and reliability |
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| creator | Pandey, Mayank Zuo, Ming J Moghaddass, Ramin |
| description | 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. |
| doi_str_mv | 10.1177/1748006X15598914 |
| format | Article |
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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.</description><identifier>ISSN: 1748-006X</identifier><identifier>EISSN: 1748-0078</identifier><identifier>DOI: 10.1177/1748006X15598914</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Age factors ; Availability ; Breaking ; Cost analysis ; Cost engineering ; Evolutionary algorithms ; Failure ; Hazards ; Horizon ; Maintenance ; Maintenance management ; Mathematical analysis ; Mathematical models ; Mathematical problems ; Parallel processing ; Preventive maintenance ; Production scheduling ; Resource scheduling ; Shutdowns</subject><ispartof>Proceedings of the Institution of Mechanical Engineers. 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Part O, Journal of risk and reliability</title><description>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.</description><subject>Age factors</subject><subject>Availability</subject><subject>Breaking</subject><subject>Cost analysis</subject><subject>Cost engineering</subject><subject>Evolutionary algorithms</subject><subject>Failure</subject><subject>Hazards</subject><subject>Horizon</subject><subject>Maintenance</subject><subject>Maintenance management</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Mathematical problems</subject><subject>Parallel processing</subject><subject>Preventive maintenance</subject><subject>Production scheduling</subject><subject>Resource scheduling</subject><subject>Shutdowns</subject><issn>1748-006X</issn><issn>1748-0078</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqFkM1Lw0AQxRdRsFbvHgNevERnk012chIpfkHBgwq9hc12tt2SbupuUtC_3oSKSEE8zfD4vcfMY-ycwxXnUl5zKRAgn_EsK7Dg4oCNBikGkHj4s-ezY3YSwgpASJ7DiN28UE26tVuK1sq6lpxymqKglzTvausWUbMlH6nIWGdbija1cm6Ql423n407ZUdG1YHOvueYvd3fvU4e4-nzw9PkdhprkaRtLCo0spBGExYVFcboLJeJ5FWKiaqyinKhUAP0dMWVJkOKCFM9T9GoucZ0zC53uRvfvHcU2nJtg6a6P4eaLpQcASEDLOT_qMQsSRES0aMXe-iq6bzrHxmoPBsq5T0FO0r7JgRPptx4u1b-o-RQDuWX--X3lnhnCWpBv0L_4r8AfdyEaQ</recordid><startdate>20160401</startdate><enddate>20160401</enddate><creator>Pandey, Mayank</creator><creator>Zuo, Ming J</creator><creator>Moghaddass, Ramin</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>7ST</scope><scope>C1K</scope><scope>SOI</scope></search><sort><creationdate>20160401</creationdate><title>Selective maintenance scheduling over a finite planning horizon</title><author>Pandey, Mayank ; Zuo, Ming J ; Moghaddass, Ramin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c423t-4b8f797fce89be9ffc567271b382ab5be64a8c00c42b1acefeaee83cd38fadc83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Age factors</topic><topic>Availability</topic><topic>Breaking</topic><topic>Cost analysis</topic><topic>Cost engineering</topic><topic>Evolutionary algorithms</topic><topic>Failure</topic><topic>Hazards</topic><topic>Horizon</topic><topic>Maintenance</topic><topic>Maintenance management</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Mathematical problems</topic><topic>Parallel processing</topic><topic>Preventive maintenance</topic><topic>Production scheduling</topic><topic>Resource scheduling</topic><topic>Shutdowns</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pandey, Mayank</creatorcontrib><creatorcontrib>Zuo, Ming J</creatorcontrib><creatorcontrib>Moghaddass, Ramin</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Environment Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><jtitle>Proceedings of the Institution of Mechanical Engineers. 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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. 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| subjects | Age factors Availability Breaking Cost analysis Cost engineering Evolutionary algorithms Failure Hazards Horizon Maintenance Maintenance management Mathematical analysis Mathematical models Mathematical problems Parallel processing Preventive maintenance Production scheduling Resource scheduling Shutdowns |
| title | Selective maintenance scheduling over a finite planning horizon |
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