Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/91586
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Industrial and Systems Engineering | en_US |
dc.creator | Zhang, G | en_US |
dc.creator | Wang, G | en_US |
dc.creator | Chen, CH | en_US |
dc.creator | Cao, X | en_US |
dc.creator | Zhang, Y | en_US |
dc.creator | Zheng, P | en_US |
dc.date.accessioned | 2021-11-09T03:07:57Z | - |
dc.date.available | 2021-11-09T03:07:57Z | - |
dc.identifier.issn | 0736-5845 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/91586 | - |
dc.language.iso | en | en_US |
dc.publisher | Pergamon Press | en_US |
dc.rights | © 2021 Elsevier Ltd. All rights reserved. | en_US |
dc.rights | © 2021. 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., Wang, G., Chen, C.-H., Cao, X., Zhang, Y., & Zheng, P. (2021). Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services. Robotics and Computer-Integrated Manufacturing, 71, 102161 is available at https://dx.doi.org/10.1016/j.rcim.2021.102161. | en_US |
dc.subject | Smart manufacturing service (SMS) | en_US |
dc.subject | Energy consumption | en_US |
dc.subject | SMS allocation | en_US |
dc.subject | Augmented Lagrangian coordination (ALC) | en_US |
dc.title | Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 71 | en_US |
dc.identifier.doi | 10.1016/j.rcim.2021.102161 | en_US |
dcterms.abstract | The rapid development of information and communication technologies has triggered the proposition and implementation of smart manufacturing paradigms. In this regard, efficient allocation of smart manufacturing services (SMSs) can provide a sustainable manner for promoting cleaner production. Currently, centralized optimization methods have been widely used to complete the optimal allocation of SMSs. However, personalized manufacturing tasks usually belong to diverse production domains. The centralized optimization methods could hardly include related production knowledge of all manufacturing tasks in an individual decision model. Consequently, it is difficult to provide satisfactory SMSs for meeting customer's requirements. In addition, energy consumption is rarely considered in the SMS allocation process which is unfavorable for performing sustainable manufacturing. To address these challenges, augmented Lagrangian coordination (ALC), a novel distributed optimization method is proposed to deal with the energy-optimal SMS allocation problem in this paper. The energy-optimal SMS allocation model is constructed and decomposed into several loose-coupled and distributed elements. Two variants of the ALC method are implemented to formulate the proposed problem and obtain final SMS allocation results. A case study is employed to verify the superiority of the proposed method in dealing with energy-optimal SMS allocation problems by comparing with the centralized optimization method at last. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Robotics and computer - integrated manufacturing, Oct. 2021, v. 71, 102161 | en_US |
dcterms.isPartOf | Robotics and computer - integrated manufacturing | en_US |
dcterms.issued | 2021-10 | - |
dc.identifier.isi | WOS:000663337200001 | - |
dc.identifier.artn | 102161 | en_US |
dc.description.validate | 202111 bchy | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | a1047-n03 | - |
dc.identifier.SubFormID | 43844 | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Nature Science Foundation of China (U2001201, 51875451, 51834006) and the 111 Project Grant (B13044),the National Research Foundation (NRF) Singapore and Delta Electronics International (Singapore) Pte Ltd., under the Corporate Laboratory@ University Scheme (Ref. SCO-RP1; RCA-16/434) at Nanyang Technological University, Singapore. | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Zhang_Augmented_Lagrangian_Coordination.pdf | Pre-Published version | 2.08 MB | Adobe PDF | View/Open |
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