TY - GEN
T1 - Cloud-edge-device Collaboration Mechanisms of Cloud Manufacturing for Customized and Personalized Products
AU - Yang, Chen
AU - Wang, Yingchao
AU - Tang, Runze
AU - Lan, Shulin
AU - Wang, Lihui
AU - Shen, Weiming
AU - Huang, George Q.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - With the increasingly developed industry and more comprehensive product offerings, customized and personalized products (CPPs) gradually become a main business model of many enterprises. However, the characteristics of CPPs, such as large differences in product modules and short product delivery cycles, put forward very high demands for the intelligence, flexibility and real-time performance of cloud manufacturing (CMfg). To satisfy the above typical demands, a cloud-edge-device collaborative framework of CMfg is proposed to support distributed data processing and fast decision-making. In the context of Cloud-edge-device collaboration, the vertically and horizontally distributed deployment and update mechanisms of deep learning models (DLMs) are brought forward and analyzed in detail to provide rapid response and high-performance decision-making services for CPPs. In addition, related key technologies are presented to provide references for the technical research direction.
AB - With the increasingly developed industry and more comprehensive product offerings, customized and personalized products (CPPs) gradually become a main business model of many enterprises. However, the characteristics of CPPs, such as large differences in product modules and short product delivery cycles, put forward very high demands for the intelligence, flexibility and real-time performance of cloud manufacturing (CMfg). To satisfy the above typical demands, a cloud-edge-device collaborative framework of CMfg is proposed to support distributed data processing and fast decision-making. In the context of Cloud-edge-device collaboration, the vertically and horizontally distributed deployment and update mechanisms of deep learning models (DLMs) are brought forward and analyzed in detail to provide rapid response and high-performance decision-making services for CPPs. In addition, related key technologies are presented to provide references for the technical research direction.
KW - cloud computing
KW - cloud manufacturing
KW - cloud-edge-thing collaboration
KW - distributed computing
KW - edge computing
UR - http://www.scopus.com/inward/record.url?scp=85130787024&partnerID=8YFLogxK
U2 - 10.1109/CSCWD54268.2022.9776267
DO - 10.1109/CSCWD54268.2022.9776267
M3 - Conference contribution
AN - SCOPUS:85130787024
T3 - 2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022
SP - 1517
EP - 1522
BT - 2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022
Y2 - 4 May 2022 through 6 May 2022
ER -