Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/92597
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorZhang, Gen_US
dc.creatorChen, CHen_US
dc.creatorZheng, Pen_US
dc.creatorZhong, RYen_US
dc.date.accessioned2022-04-26T06:45:44Z-
dc.date.available2022-04-26T06:45:44Z-
dc.identifier.issn0959-6526en_US
dc.identifier.urihttp://hdl.handle.net/10397/92597-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2020 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Zhang, G., Chen, C.-H., Zheng, P., & Zhong, R. Y. (2020). An integrated framework for active discovery and optimal allocation of smart manufacturing services. Journal of Cleaner Production, 273, 123144 is available at https://dx.doi.org/10.1016/j.jclepro.2020.123144.en_US
dc.subjectActive discoveryen_US
dc.subjectAnalytical target cascadingen_US
dc.subjectOptimal allocationen_US
dc.subjectSmart manufacturing serviceen_US
dc.titleAn integrated framework for active discovery and optimal allocation of smart manufacturing servicesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume273en_US
dc.identifier.doi10.1016/j.jclepro.2020.123144en_US
dcterms.abstractSmart manufacturing is gradually recognized and widely adopted due to the promising features of sustainability, flexibility, and collaboration. Service discovery and allocation in smart manufacturing aim to provide on-demand manufacturing capabilities for meeting customized production requirements. They are tightly coupled in practice, whereas they are usually considered as two independent processes and investigated separately in most research. Meanwhile, the collaboration relationship and decision autonomy of service providers are rarely taken into account to perform sustainable and flexible production. To deal with these challenges, this paper proposes an integrated framework to holistically describe the active discovery and optimal allocation of smart manufacturing services. A mechanism is designed to consider the collaborative relationship of manufacturing resources and promote collaborative production. The distributed optimization model based on analytical target cascading method is introduced to maintain the decision autonomy of service providers and achieve the optimal allocation of smart manufacturing services. A case study is further provided to demonstrate the effectiveness of the proposed framework.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of cleaner production, 10 Nov. 2020, v. 273, 123144en_US
dcterms.isPartOfJournal of cleaner productionen_US
dcterms.issued2020-11-10-
dc.identifier.scopus2-s2.0-85088117434-
dc.identifier.artn123144en_US
dc.description.validate202204 bcrcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera1288-
dc.identifier.SubFormID44470-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextOthers: National Research Foundation (NRF) of Singaporeen_US
dc.description.pubStatusPublisheden_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
a1288_44470_Zhang_Integrated_Framework_Active.pdf2.55 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

65
Last Week
0
Last month
Citations as of May 19, 2024

Downloads

51
Citations as of May 19, 2024

SCOPUSTM   
Citations

34
Citations as of May 16, 2024

WEB OF SCIENCETM
Citations

30
Citations as of May 16, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.