Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/92597
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Industrial and Systems Engineering | en_US |
dc.creator | Zhang, G | en_US |
dc.creator | Chen, CH | en_US |
dc.creator | Zheng, P | en_US |
dc.creator | Zhong, RY | en_US |
dc.date.accessioned | 2022-04-26T06:45:44Z | - |
dc.date.available | 2022-04-26T06:45:44Z | - |
dc.identifier.issn | 0959-6526 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/92597 | - |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_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.rights | The 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.subject | Active discovery | en_US |
dc.subject | Analytical target cascading | en_US |
dc.subject | Optimal allocation | en_US |
dc.subject | Smart manufacturing service | en_US |
dc.title | An integrated framework for active discovery and optimal allocation of smart manufacturing services | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 273 | en_US |
dc.identifier.doi | 10.1016/j.jclepro.2020.123144 | en_US |
dcterms.abstract | Smart 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.accessRights | open access | en_US |
dcterms.bibliographicCitation | Journal of cleaner production, 10 Nov. 2020, v. 273, 123144 | en_US |
dcterms.isPartOf | Journal of cleaner production | en_US |
dcterms.issued | 2020-11-10 | - |
dc.identifier.scopus | 2-s2.0-85088117434 | - |
dc.identifier.artn | 123144 | en_US |
dc.description.validate | 202204 bcrc | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | a1288 | - |
dc.identifier.SubFormID | 44470 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | Others: National Research Foundation (NRF) of Singapore | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
a1288_44470_Zhang_Integrated_Framework_Active.pdf | 2.55 MB | Adobe PDF | View/Open |
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