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Cell formation in a cellular manufacturing system using simulation integrated hybrid genetic algorithm

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dc.contributor.authorImran, Muhammad-
dc.contributor.authorKang, Changwook-
dc.contributor.authorLee, Young Hae-
dc.contributor.authorJahanzaib, Mirza-
dc.contributor.authorAziz, Haris-
dc.date.accessioned2021-06-22T14:24:02Z-
dc.date.available2021-06-22T14:24:02Z-
dc.date.created2021-01-21-
dc.date.issued2017-03-
dc.identifier.issn0360-8352-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/10113-
dc.description.abstractWork-in-process (WIP) is an important performance measure of contemporary manufacturing systems such as cellular manufacturing system (CMS). The term value added WIP (VAWIP) is used because; the value of WIP increased at each stage of production due to the application of resources in the form of machines, time and energy. This research is an attempt of cell formation (CF) in CMS that would minimize the value added work in process. To achieve this objective a mathematical model is formulated and solved using discrete event simulation (DES) integrated hybrid genetic algorithm (SHGA) in which simulation and the genetic algorithm have been integrated to form an approach called SHGA and it has the advantages of using both. The proposed approach has been applied on local automobile part supply industry for cell formation. While solving problem with SHGA each population has been evaluated using the discrete event simulation (DES). The solution was found in the form of assigning machines to cells in a way that resulted in minimum value added work in process. A 8.55% reduction of value added work in process occurred using SHGA. The reduction of value added work in process VAWIP in the system resulted in the reduced waiting and throughput times, whereas increased throughput rate and machine utilization. (C) 2016 Elsevier Ltd. All rights reserved.-
dc.language영어-
dc.language.isoen-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.titleCell formation in a cellular manufacturing system using simulation integrated hybrid genetic algorithm-
dc.typeArticle-
dc.contributor.affiliatedAuthorKang, Changwook-
dc.identifier.doi10.1016/j.cie.2016.12.028-
dc.identifier.scopusid2-s2.0-85009910443-
dc.identifier.wosid000397371900010-
dc.identifier.bibliographicCitationCOMPUTERS & INDUSTRIAL ENGINEERING, v.105, pp.123 - 135-
dc.relation.isPartOfCOMPUTERS & INDUSTRIAL ENGINEERING-
dc.citation.titleCOMPUTERS & INDUSTRIAL ENGINEERING-
dc.citation.volume105-
dc.citation.startPage123-
dc.citation.endPage135-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryEngineering, Industrial-
dc.subject.keywordPlusMATHEMATICAL-MODEL-
dc.subject.keywordPlusOPERATOR ASSIGNMENT-
dc.subject.keywordPlusMACHINE LAYOUT-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordPlusDESIGN-
dc.subject.keywordPlusWIP-
dc.subject.keywordPlusRECONFIGURATION-
dc.subject.keywordAuthorValue added work-in-process (VAWIP)-
dc.subject.keywordAuthorCellular manufacturing system (CMS)-
dc.subject.keywordAuthorCell formation-
dc.subject.keywordAuthorDeterministic simulation-
dc.subject.keywordAuthorSimulation integrated hybrid genetic algorithm (SHGA)-
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S036083521630506X?via%3Dihub-
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