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Article: An intelligent factory-wide optimal operation system for continuous production process

TitleAn intelligent factory-wide optimal operation system for continuous production process
Authors
Issue Date2016
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/17517575.asp
Citation
Enterprise Information Systems, 2016, v. 10 n. 3, p. 286-302 How to Cite?
AbstractIn this study, a novel intelligent factory-wide operation system for a continuous production process is designed to optimise the entire production process, which consists of multiple units; furthermore, this system is developed using process operational data to avoid the complexity of mathematical modelling of the continuous production process. The data-driven approach aims to specify the structure of the optimal operation system; in particular, the operational data of the process are used to formulate each part of the system. In this context, the domain knowledge of process engineers is utilised, and a closed-loop dynamic optimisation strategy, which combines feedback, performance prediction, feed-forward, and dynamic tuning schemes into a framework, is employed. The effectiveness of the proposed system has been verified using industrial experimental results. © 2015 Taylor & Francis.
Persistent Identifierhttp://hdl.handle.net/10722/214175
ISSN
2015 Impact Factor: 2.269
2015 SCImago Journal Rankings: 1.287
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorDing, J-
dc.contributor.authorChai, T-
dc.contributor.authorWang, H-
dc.contributor.authorWang, J-
dc.contributor.authorZheng, X-
dc.date.accessioned2015-08-21T10:52:24Z-
dc.date.available2015-08-21T10:52:24Z-
dc.date.issued2016-
dc.identifier.citationEnterprise Information Systems, 2016, v. 10 n. 3, p. 286-302-
dc.identifier.issn1751-7575-
dc.identifier.urihttp://hdl.handle.net/10722/214175-
dc.description.abstractIn this study, a novel intelligent factory-wide operation system for a continuous production process is designed to optimise the entire production process, which consists of multiple units; furthermore, this system is developed using process operational data to avoid the complexity of mathematical modelling of the continuous production process. The data-driven approach aims to specify the structure of the optimal operation system; in particular, the operational data of the process are used to formulate each part of the system. In this context, the domain knowledge of process engineers is utilised, and a closed-loop dynamic optimisation strategy, which combines feedback, performance prediction, feed-forward, and dynamic tuning schemes into a framework, is employed. The effectiveness of the proposed system has been verified using industrial experimental results. © 2015 Taylor & Francis.-
dc.languageeng-
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/17517575.asp-
dc.relation.ispartofEnterprise Information Systems-
dc.rightsPREPRINT This is a preprint of an article whose final and definitive form has been published in the [JOURNAL TITLE] [year of publication] [copyright Taylor & Francis]; [JOURNAL TITLE] is available online at: http://www.informaworld.com/smpp/ with the open URL of your article POSTPRINT This is an Accepted Manuscript of an article published by Taylor & Francis in [JOURNAL TITLE] on [date of publication], available online: http://wwww.tandfonline.com/[Article DOI]-
dc.titleAn intelligent factory-wide optimal operation system for continuous production process-
dc.typeArticle-
dc.identifier.emailDing, J: jldinghk@hku.hk-
dc.identifier.emailWang, H: wanghf@hku.hk-
dc.identifier.emailWang, J: jwwang@hku.hk-
dc.identifier.authorityWang, J=rp01888-
dc.identifier.doi10.1080/17517575.2015.1065346-
dc.identifier.scopuseid_2-s2.0-84953293615-
dc.identifier.hkuros246999-
dc.identifier.hkuros259069-
dc.identifier.volume10-
dc.identifier.issue3-
dc.identifier.spage286-
dc.identifier.epage302-
dc.identifier.isiWOS:000367809300004-
dc.publisher.placeUnited Kingdom-

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