Show simple item record

dc.contributor.authorMaleki, Hameden
dc.contributor.authorYang, Yingjieen
dc.date.accessioned2018-01-24T12:16:37Z
dc.date.available2018-01-24T12:16:37Z
dc.date.issued2017
dc.identifier.citationMaleki, H. and Yang, Y. (2017) An uncertain programming model for preventive maintenance scheduling. Grey Systems: Theory and Application, 7(1), pp.111-122.en
dc.identifier.issn2043-9377
dc.identifier.urihttp://hdl.handle.net/2086/15099
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI linken
dc.description.abstractPurpose: This study aims to illustrate an uncertain programming model for scheduling of preventive maintenance actions. The PM scheduling, in which PM actions are performed under fixed intervals, is solved by Grey systems theory. Design/methodology/approach: The paper applied the grey evaluation method based on triangular whitenization weight functions which includes two classes (1) endpoint evaluation method (2) center-point evaluation method. Findings: Two methods give the same results based on endpoint and center-point triangular whitenization weight functions. For validation, the results were compared by Cassady’s method. Originality/value: The scheduling of preventive maintenance is crucial in reliability and maintenance engineering. Hundreds of parts compose complex machines that require replacement and/or repairing. It is helpful to reduce the outage loss on frequent repair/replacement parts and avoid lack of maintenance of the equipment by controlling the equipment maintenance frequency.en
dc.language.isoenen
dc.publisherEmeralden
dc.subjectGrey Systems Theory, Preventive Maintenance Scheduling, Uncertainty, Failureen
dc.titleAn uncertain programming model for preventive maintenance schedulingen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1108/GS-07-2016-0015
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderLeverhulmeen
dc.projectidIN-2014-020en
dc.cclicenceCC-BY-NCen
dc.date.acceptance2016-08-26en
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record