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Article: Task-driven e-manufacturing resource configurable model

TitleTask-driven e-manufacturing resource configurable model
Authors
KeywordsE-manufacturing
E-manufacturing cell
Real-time manufacturing
Rfid
Traceability and visibility
Issue Date2012
PublisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0956-5515
Citation
Journal of Intelligent Manufacturing, 2012, v. 23 n. 5, p. 1681-1694 How to Cite?
AbstractManufacturing resource configuration (MRC) plays a very important role in an e-Manufacturing system. Higher requirements for optimal configuration under online resource visibility and traceability have led to two main challenges. One is that more features of manufacturing tasks affecting the optimization results should be taken into considerationwhen establishing theMRCmathematical model for a manufacturing cell. The other is that manufacturing information should be given equal attention as MRC to realize realtime visibility and traceability of the resultingmanufacturing cells. This paper presents a comprehensive mathematical model which considers more practical features of manufacturing tasks (e.g. batch volume and alternative processing routes) for manufacturing cell formation. This model adopts a fuzzy clustering method to group the manufacturing tasks and machines. Moreover, it is enabled by a smart equipment model to realize the configurable model of real-time manufacturing information and corresponding visualization and tracing methods. A case study is given to demonstrate the proposed models and methods. © Springer Science+Business Media, LLC 2010.
Persistent Identifierhttp://hdl.handle.net/10722/134651
ISSN
2015 Impact Factor: 1.995
2015 SCImago Journal Rankings: 1.397
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Yen_HK
dc.contributor.authorJiang, Pen_HK
dc.contributor.authorHuang, GQen_HK
dc.contributor.authorQu, Ten_HK
dc.contributor.authorHong, Jen_HK
dc.date.accessioned2011-07-05T08:23:12Z-
dc.date.available2011-07-05T08:23:12Z-
dc.date.issued2012en_HK
dc.identifier.citationJournal of Intelligent Manufacturing, 2012, v. 23 n. 5, p. 1681-1694en_HK
dc.identifier.issn0956-5515en_HK
dc.identifier.urihttp://hdl.handle.net/10722/134651-
dc.description.abstractManufacturing resource configuration (MRC) plays a very important role in an e-Manufacturing system. Higher requirements for optimal configuration under online resource visibility and traceability have led to two main challenges. One is that more features of manufacturing tasks affecting the optimization results should be taken into considerationwhen establishing theMRCmathematical model for a manufacturing cell. The other is that manufacturing information should be given equal attention as MRC to realize realtime visibility and traceability of the resultingmanufacturing cells. This paper presents a comprehensive mathematical model which considers more practical features of manufacturing tasks (e.g. batch volume and alternative processing routes) for manufacturing cell formation. This model adopts a fuzzy clustering method to group the manufacturing tasks and machines. Moreover, it is enabled by a smart equipment model to realize the configurable model of real-time manufacturing information and corresponding visualization and tracing methods. A case study is given to demonstrate the proposed models and methods. © Springer Science+Business Media, LLC 2010.en_HK
dc.languageengen_US
dc.publisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0956-5515en_HK
dc.relation.ispartofJournal of Intelligent Manufacturingen_HK
dc.rightsThe original publication is available at www.springerlink.com-
dc.subjectE-manufacturingen_HK
dc.subjectE-manufacturing cellen_HK
dc.subjectReal-time manufacturingen_HK
dc.subjectRfiden_HK
dc.subjectTraceability and visibilityen_HK
dc.titleTask-driven e-manufacturing resource configurable modelen_HK
dc.typeArticleen_HK
dc.identifier.emailHuang, GQ: gqhuang@hku.hken_HK
dc.identifier.emailQu, T: quting@hku.hken_HK
dc.identifier.authorityHuang, GQ=rp00118en_HK
dc.identifier.authorityQu, T=rp01500en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/s10845-010-0470-8en_HK
dc.identifier.scopuseid_2-s2.0-84870952334en_HK
dc.identifier.hkuros198515-
dc.identifier.volume23-
dc.identifier.issue5-
dc.identifier.spage1681en_HK
dc.identifier.epage1694en_HK
dc.identifier.eissn1572-8145-
dc.identifier.isiWOS:000308820200017-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridHong, J=7404118243en_HK
dc.identifier.scopusauthoridQu, T=35590322600en_HK
dc.identifier.scopusauthoridHuang, GQ=7403425048en_HK
dc.identifier.scopusauthoridJiang, P=7201470064en_HK
dc.identifier.scopusauthoridZhang, Y=8305738300en_HK
dc.identifier.citeulike8214915-

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