Semi-dynamic maintenance scheduling for multi-station series systems in multi-specification and small-batch production

•A semi-dynamic OM policy is proposed for multi-station series systems in MSSB production.•It combines the advantages of the opportunity-window-based policy and the dynamic policy.•A constant MTW is defined firstly to decrease the complexity of the solution space.•The OM scheme is obtained on the co...

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Veröffentlicht in:Reliability engineering & system safety 2020-03, Vol.195, p.106753, Article 106753
Hauptverfasser: Zhou, Xiaojun, Yu, Mengqi
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description •A semi-dynamic OM policy is proposed for multi-station series systems in MSSB production.•It combines the advantages of the opportunity-window-based policy and the dynamic policy.•A constant MTW is defined firstly to decrease the complexity of the solution space.•The OM scheme is obtained on the constant MTW and the dynamic production environment.•For this OM policy, the probability to achieve a better performance is close to 90%. This paper proposes a new semi-dynamic Opportunistic Maintenance (OM) policy for multi-station series systems, with considering the changing production environment brought by the multi-specification and small-batch production mode. It combines the advantages of the time-window-based OM policy, which can decrease the complexity of the solution space for PM grouping, and the dynamic OM policy, which is capable of adapting to the changing production environment. Whenever one of the stations reaches its original Preventive Maintenance (PM) moment, an OM decision cycle of the system begins. During this decision cycle, all the stations, whose original PM moments are within the presented dynamic Maintenance Time Window (MTW), form a PM group. This dynamic MTW is different for each station, and it is obtained based on the predetermined static MTW and the dynamic impacts from the current production task. The static MTW is constant, and it is derived according to the expected production plan without considering the changing production environment. To balance the maintenance cost for the obtained PM group, the PM is not performed right at the time when one of the stations reaches its original PM moment, and it is postponed. The optimal duration of the postponement is dynamically obtained by minimizing the total maintenance cost within this duration. Finally, numerical examples and comparisons are illustrated to show the effectiveness of the proposed semi-dynamic OM policy.
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This paper proposes a new semi-dynamic Opportunistic Maintenance (OM) policy for multi-station series systems, with considering the changing production environment brought by the multi-specification and small-batch production mode. It combines the advantages of the time-window-based OM policy, which can decrease the complexity of the solution space for PM grouping, and the dynamic OM policy, which is capable of adapting to the changing production environment. Whenever one of the stations reaches its original Preventive Maintenance (PM) moment, an OM decision cycle of the system begins. During this decision cycle, all the stations, whose original PM moments are within the presented dynamic Maintenance Time Window (MTW), form a PM group. This dynamic MTW is different for each station, and it is obtained based on the predetermined static MTW and the dynamic impacts from the current production task. The static MTW is constant, and it is derived according to the expected production plan without considering the changing production environment. To balance the maintenance cost for the obtained PM group, the PM is not performed right at the time when one of the stations reaches its original PM moment, and it is postponed. The optimal duration of the postponement is dynamically obtained by minimizing the total maintenance cost within this duration. 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This paper proposes a new semi-dynamic Opportunistic Maintenance (OM) policy for multi-station series systems, with considering the changing production environment brought by the multi-specification and small-batch production mode. It combines the advantages of the time-window-based OM policy, which can decrease the complexity of the solution space for PM grouping, and the dynamic OM policy, which is capable of adapting to the changing production environment. Whenever one of the stations reaches its original Preventive Maintenance (PM) moment, an OM decision cycle of the system begins. During this decision cycle, all the stations, whose original PM moments are within the presented dynamic Maintenance Time Window (MTW), form a PM group. This dynamic MTW is different for each station, and it is obtained based on the predetermined static MTW and the dynamic impacts from the current production task. 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Finally, numerical examples and comparisons are illustrated to show the effectiveness of the proposed semi-dynamic OM policy.</description><subject>Batch production</subject><subject>Maintenance costs</subject><subject>Maintenance management</subject><subject>Maintenance scheduling</subject><subject>Maintenance time window</subject><subject>Multi-specification and small-batch</subject><subject>Multi-station series system</subject><subject>Opportunistic maintenance</subject><subject>Preventive maintenance</subject><subject>Reliability engineering</subject><subject>Solution space</subject><subject>Specifications</subject><subject>Stations</subject><subject>Windows (intervals)</subject><issn>0951-8320</issn><issn>1879-0836</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kE1r4zAQhsXShU2z-wd6EvTsrD5sS4ZeSukXBHpoexZaadwo2HKqkQv591Vw99rTwMz7zrzzEHLB2YYz3v7dbxIgbgTjXWm0qpE_yIpr1VVMy_aMrFjX8EpLwX6Rc8Q9Y6zuGrUiH88whsofox2Do6MNMUO00QFFtwM_DyG-0X5KdJyHHCrMNocpUoQUACkeMcOINMT_8wO40Ae3qGz0FEc7DNU_m92OHtLkZ3ca_SY_ezsg_Pmqa_J6d_ty81Btn-4fb663lZNC54qX2FqIpql5q2rdeGnb2rfey67nri6Pylo44LXQXEOn616BtKrnvQNoJcg1uVz2ltPvM2A2-2lOsZw0QiqulBK6LSqxqFyaEBP05pDCaNPRcGZOfM3enPiaE1-z8C2mq8UEJf9HgGTQBSjkfEjgsvFT-M7-CaFShc0</recordid><startdate>202003</startdate><enddate>202003</enddate><creator>Zhou, Xiaojun</creator><creator>Yu, Mengqi</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>SOI</scope></search><sort><creationdate>202003</creationdate><title>Semi-dynamic maintenance scheduling for multi-station series systems in multi-specification and small-batch production</title><author>Zhou, Xiaojun ; Yu, Mengqi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c328t-1095822554167485d3a64d6dd39f1c4067342ce142818e984f7e3a7f1fcee63e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Batch production</topic><topic>Maintenance costs</topic><topic>Maintenance management</topic><topic>Maintenance scheduling</topic><topic>Maintenance time window</topic><topic>Multi-specification and small-batch</topic><topic>Multi-station series system</topic><topic>Opportunistic maintenance</topic><topic>Preventive maintenance</topic><topic>Reliability engineering</topic><topic>Solution space</topic><topic>Specifications</topic><topic>Stations</topic><topic>Windows (intervals)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhou, Xiaojun</creatorcontrib><creatorcontrib>Yu, Mengqi</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Environment Abstracts</collection><jtitle>Reliability engineering &amp; system safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhou, Xiaojun</au><au>Yu, Mengqi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Semi-dynamic maintenance scheduling for multi-station series systems in multi-specification and small-batch production</atitle><jtitle>Reliability engineering &amp; system safety</jtitle><date>2020-03</date><risdate>2020</risdate><volume>195</volume><spage>106753</spage><pages>106753-</pages><artnum>106753</artnum><issn>0951-8320</issn><eissn>1879-0836</eissn><abstract>•A semi-dynamic OM policy is proposed for multi-station series systems in MSSB production.•It combines the advantages of the opportunity-window-based policy and the dynamic policy.•A constant MTW is defined firstly to decrease the complexity of the solution space.•The OM scheme is obtained on the constant MTW and the dynamic production environment.•For this OM policy, the probability to achieve a better performance is close to 90%. 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subjects Batch production
Maintenance costs
Maintenance management
Maintenance scheduling
Maintenance time window
Multi-specification and small-batch
Multi-station series system
Opportunistic maintenance
Preventive maintenance
Reliability engineering
Solution space
Specifications
Stations
Windows (intervals)
title Semi-dynamic maintenance scheduling for multi-station series systems in multi-specification and small-batch production
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