Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services
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. Curren...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/160493 |
| _version_ | 1811697538999255040 |
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| author | Zhang, Geng Wang, Gang Chen, Chun-Hsien Cao, Xiangang Zhang, Yingfeng Zheng, Pai |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Zhang, Geng Wang, Gang Chen, Chun-Hsien Cao, Xiangang Zhang, Yingfeng Zheng, Pai |
| author_sort | Zhang, Geng |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T07:56:52Z |
| format | Journal Article |
| id | ntu-10356/160493 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:56:52Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1604932022-07-25T07:13:09Z Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services Zhang, Geng Wang, Gang Chen, Chun-Hsien Cao, Xiangang Zhang, Yingfeng Zheng, Pai School of Mechanical and Aerospace Engineering School of Electrical and Electronic Engineering Delta-NTU Corporate Laboratory Engineering::Mechanical engineering Engineering::Electrical and electronic engineering Energy Consumption Augmented Lagrangian Coordination 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. Nanyang Technological University National Research Foundation (NRF) The authors wish to acknowledge the financial support from the National Nature Science Foundation of China (U2001201, 51875451), 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. 2022-07-25T07:13:09Z 2022-07-25T07:13:09Z 2021 Journal Article Zhang, G., Wang, G., Chen, C., 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-. https://dx.doi.org/10.1016/j.rcim.2021.102161 0736-5845 https://hdl.handle.net/10356/160493 10.1016/j.rcim.2021.102161 2-s2.0-85103981253 71 102161 en SCO-RP1 RCA-16/434) Robotics and Computer-Integrated Manufacturing © 2021 Elsevier Ltd. All rights reserved. |
| spellingShingle | Engineering::Mechanical engineering Engineering::Electrical and electronic engineering Energy Consumption Augmented Lagrangian Coordination Zhang, Geng Wang, Gang Chen, Chun-Hsien Cao, Xiangang Zhang, Yingfeng Zheng, Pai Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services |
| title | Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services |
| title_full | Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services |
| title_fullStr | Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services |
| title_full_unstemmed | Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services |
| title_short | Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services |
| title_sort | augmented lagrangian coordination for energy optimal allocation of smart manufacturing services |
| topic | Engineering::Mechanical engineering Engineering::Electrical and electronic engineering Energy Consumption Augmented Lagrangian Coordination |
| url | https://hdl.handle.net/10356/160493 |
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