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Cited 9 time in webofscience Cited 14 time in scopus
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dc.contributor.authorSinggih, Ivan Kristianto-
dc.contributor.authorYu, Onyu-
dc.contributor.authorKim, Byung-In-
dc.contributor.authorKoo, Jeongin-
dc.contributor.authorLee, Seungdoe-
dc.date.accessioned2020-02-25T06:50:04Z-
dc.date.available2020-02-25T06:50:04Z-
dc.date.created2020-01-21-
dc.date.issued2020-01-
dc.identifier.issn0956-5515-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/101075-
dc.description.abstractIn a factory of automobile component primer painting, various automobile parts are attached to overhead hangers in a conveyor line and undergo a series of coating processes. Thereafter, the components are wrapped at a packaging station. The packaging process should be fully balanced by an appropriate sequence of components to prevent the bottleneck effect because each component requires different packaging times and materials. An overhead hanger has a capacity limit and can hold varying numbers of components depending on the component type. Capacity loss can occur if the hanger capacity is not fully utilized. To increase hanger utilization, companies sometimes mix two or more component types on the same hangers, and these hangers are called mixed hangers. However, mixed hangers generally cause heavy workload because different items require additional setup times during hanging and packing processes. Hence, having many mixed hangers is not recommended. A good production schedule requires a small number of mixed hangers and maximizes hanger utilization and packaging workload balance. We show that the scheduling problem is NP-hard and develop a mathematical programming model and efficient solution approaches for the problem. When applying the methods to solve real problems, we also use an initial solution-generating method that minimizes the mixing cost, set a rule for hanging the items on hangers considering eligibility constraint, and decrease the size of tabu list in proportion to the remaining computational time for assuring intensification in the final iterations of the search. Experimental results demonstrate the effectiveness of the proposed approaches.-
dc.languageEnglish-
dc.publisherSPRINGER-
dc.relation.isPartOfJOURNAL OF INTELLIGENT MANUFACTURING-
dc.subjectAutomobiles-
dc.subjectHeuristic algorithms-
dc.subjectHeuristic programming-
dc.subjectInteger programming-
dc.subjectPackaging-
dc.subjectPackaging materials-
dc.subjectProduction control-
dc.subjectScheduling-
dc.subjectScheduling algorithms-
dc.subjectTabu search-
dc.subjectAutomobile components-
dc.subjectBottleneck effects-
dc.subjectComputational time-
dc.subjectFlow-shop scheduling-
dc.subjectMathematical programming models-
dc.subjectMixed integer programming-
dc.subjectProduction schedule-
dc.subjectProduction scheduling problems-
dc.subjectCoatings-
dc.titleProduction scheduling problem in a factory of automobile component primer painting-
dc.typeArticle-
dc.identifier.doi10.1007/s10845-019-01524-6-
dc.type.rimsART-
dc.identifier.bibliographicCitationJOURNAL OF INTELLIGENT MANUFACTURING-
dc.identifier.wosid000505375600002-
dc.citation.titleJOURNAL OF INTELLIGENT MANUFACTURING-
dc.contributor.affiliatedAuthorSinggih, Ivan Kristianto-
dc.contributor.affiliatedAuthorYu, Onyu-
dc.contributor.affiliatedAuthorKim, Byung-In-
dc.identifier.scopusid2-s2.0-85077248962-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.type.docTypeArticle; Early Access-
dc.subject.keywordPlusBATCH-PROCESSING MACHINES-
dc.subject.keywordPlusNO-WAIT FLOWSHOP-
dc.subject.keywordPlusDEPENDENT SETUP TIMES-
dc.subject.keywordPlusTOTAL COMPLETION-TIME-
dc.subject.keywordPlusMAKESPAN MINIMIZATION-
dc.subject.keywordPlus2-MACHINE FLOWSHOP-
dc.subject.keywordPlusSHOP PROBLEM-
dc.subject.keywordPlusTABU SEARCH-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordPlusALGORITHMS-
dc.subject.keywordAuthorFlow shop scheduling-
dc.subject.keywordAuthorAutomobile component primer painting-
dc.subject.keywordAuthorMixed-integer programming-
dc.subject.keywordAuthorHeuristic algorithms-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Manufacturing-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-

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김병인KIM, BYUNG IN
Dept. of Industrial & Management Eng.
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