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Conference Paper: Estimation of lead time in the RFID-enabled real-time shopfloor production with a data mining model

TitleEstimation of lead time in the RFID-enabled real-time shopfloor production with a data mining model
Authors
KeywordsData mining
Lead time
Radio frequency identification (RFID)
Real-time
Shopfloor production
Issue Date2013
PublisherSpringer-Verlag Berlin Heidelgerg.
Citation
The 19th International Conference on Industrial Engineering and Engineering Management, ChangSha, China, 27-29 October 2012. In Conference Proceedings, 2013, Chapter 33, p. 321-331 How to Cite?
AbstractLead time estimation (LTE) is difficult to carry out, especially within the RFID-enabled real-time manufacturing shopfloor environment since large number of factors may greatly affect its precision. This paper proposes a data mining approach with four steps each of which is equipped with suitable mathematical models to analysis the LTE from a real-life case and then to quantitatively examine its key impact factors such as processing routine, batching strategy, scheduling rules and critical parameters of specification. Experiments are carried out for this purpose and results imply that batching strategy, scheduling rules and two specification parameters largely influence the LTE, while, processing routine has less impact in this case.
Persistent Identifierhttp://hdl.handle.net/10722/189941
ISBN

 

DC FieldValueLanguage
dc.contributor.authorZhong, RYen_US
dc.contributor.authorHuang, GQen_US
dc.contributor.authorDai, QYen_US
dc.contributor.authorZhang, Ten_US
dc.date.accessioned2013-09-17T15:03:11Z-
dc.date.available2013-09-17T15:03:11Z-
dc.date.issued2013en_US
dc.identifier.citationThe 19th International Conference on Industrial Engineering and Engineering Management, ChangSha, China, 27-29 October 2012. In Conference Proceedings, 2013, Chapter 33, p. 321-331en_US
dc.identifier.isbn978-3-642-38390-8-
dc.identifier.urihttp://hdl.handle.net/10722/189941-
dc.description.abstractLead time estimation (LTE) is difficult to carry out, especially within the RFID-enabled real-time manufacturing shopfloor environment since large number of factors may greatly affect its precision. This paper proposes a data mining approach with four steps each of which is equipped with suitable mathematical models to analysis the LTE from a real-life case and then to quantitatively examine its key impact factors such as processing routine, batching strategy, scheduling rules and critical parameters of specification. Experiments are carried out for this purpose and results imply that batching strategy, scheduling rules and two specification parameters largely influence the LTE, while, processing routine has less impact in this case.-
dc.languageengen_US
dc.publisherSpringer-Verlag Berlin Heidelgerg.-
dc.relation.ispartofThe 19th International Conference on Industrial Engineering and Engineering Management: assistive technology of industrial engineeringen_US
dc.subjectData mining-
dc.subjectLead time-
dc.subjectRadio frequency identification (RFID)-
dc.subjectReal-time-
dc.subjectShopfloor production-
dc.titleEstimation of lead time in the RFID-enabled real-time shopfloor production with a data mining modelen_US
dc.typeConference_Paperen_US
dc.identifier.emailZhong, RY: zhongzry@hku.hken_US
dc.identifier.emailHuang, GQ: gqhuang@hku.hken_US
dc.identifier.authorityHuang, GQ=rp00118en_US
dc.identifier.doi10.1007/978-3-642-38391-5_33-
dc.identifier.scopuseid_2-s2.0-84891554242-
dc.identifier.hkuros224414en_US
dc.identifier.spage321en_US
dc.identifier.epage331en_US
dc.publisher.placeGermany-
dc.customcontrol.immutablesml 131101-

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