Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91586
Title: Augmented Lagrangian coordination for energy-optimal allocation of smart manufacturing services
Authors: Zhang, G
Wang, G
Chen, CH
Cao, X
Zhang, Y
Zheng, P 
Issue Date: Oct-2021
Source: Robotics and computer - integrated manufacturing, Oct. 2021, v. 71, 102161
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.
Keywords: Smart manufacturing service (SMS)
Energy consumption
SMS allocation
Augmented Lagrangian coordination (ALC)
Publisher: Pergamon Press
Journal: Robotics and computer - integrated manufacturing 
ISSN: 0736-5845
DOI: 10.1016/j.rcim.2021.102161
Appears in Collections:Journal/Magazine Article

Open Access Information
Status embargoed access
Embargo End Date 2023-10-31
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

32
Citations as of May 22, 2022

SCOPUSTM   
Citations

4
Citations as of May 12, 2022

WEB OF SCIENCETM
Citations

1
Citations as of May 26, 2022

Google ScholarTM

Check

Altmetric


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