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The simulation design and analysis of a Flexible Manufacturing System with Automated Guided Vehicle System

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dc.contributor.authorUm, Insup-
dc.contributor.authorCheon, Hyeonjae-
dc.contributor.authorLee, Hongchul-
dc.date.accessioned2021-09-08T10:57:47Z-
dc.date.available2021-09-08T10:57:47Z-
dc.date.created2021-06-11-
dc.date.issued2009-12-
dc.identifier.issn0278-6125-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/118793-
dc.description.abstractThis paper presents the Simulation design and analysis of a Flexible Manufacturing System (FMS) with an Automated Guided Vehicle system (AGVs). To maximize the operating performance of FMS with AGVs, many parameters must be considered, including the number, velocity, and dispatching rule of AGV, part-types. scheduling, and buffer sizes. Of the various critical factors, we consider the following three: (1) minimizing the congestion; (2) minimizing the vehicle utilization; and (3) maximizing the throughput. In this paper, we consider the systematic analysis methods that combine a simulation-based analytic and optimization technique that is Multi-Objective Non-Linear Programming (MONLP) and Evolution Strategy (ES). MONLP determines the design parameters of the system through multi-factorial and regression analyses ES is used to verify each parameter for simulation-based optimization A validation test for the two methods is conducted This method-based approach towards design yields the correct experimental results, ensures confidence in the specification of design parameters and supports a robust framework for analysis. Crown Copyright (C) 2010 Published by Elsevier Ltd on behalf of The Society of Manufacturing Engineers. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherELSEVIER SCI LTD-
dc.subjectINTELLIGENT DECISION-SUPPORT-
dc.subjectFMS-
dc.titleThe simulation design and analysis of a Flexible Manufacturing System with Automated Guided Vehicle System-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Hongchul-
dc.identifier.doi10.1016/j.jmsy.2010.06.001-
dc.identifier.scopusid2-s2.0-77955421552-
dc.identifier.wosid000281491800004-
dc.identifier.bibliographicCitationJOURNAL OF MANUFACTURING SYSTEMS, v.28, no.4, pp.115 - 122-
dc.relation.isPartOfJOURNAL OF MANUFACTURING SYSTEMS-
dc.citation.titleJOURNAL OF MANUFACTURING SYSTEMS-
dc.citation.volume28-
dc.citation.number4-
dc.citation.startPage115-
dc.citation.endPage122-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaOperations Research & Management Science-
dc.relation.journalWebOfScienceCategoryEngineering, Industrial-
dc.relation.journalWebOfScienceCategoryEngineering, Manufacturing-
dc.relation.journalWebOfScienceCategoryOperations Research & Management Science-
dc.subject.keywordPlusINTELLIGENT DECISION-SUPPORT-
dc.subject.keywordPlusFMS-
dc.subject.keywordAuthorSimulation-
dc.subject.keywordAuthorFlexible Manufacturing System-
dc.subject.keywordAuthorAutomated Guided Vehicle System-
dc.subject.keywordAuthorMulti Objective Nonlinear Programming-
dc.subject.keywordAuthorEvolution Strategy-
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