TY - GEN
T1 - Intelligent Manufacturing Core Enterprise-dominated Collaborative Dataspace Framework for New Energy Vehicle
AU - Zhang, Ruirui
AU - Yan, Hairui
AU - Xiao, Zhongdong
AU - Zhou, Guanghui
AU - Chang, Fengtian
AU - Yang, Shuqi
AU - Fei, Xuedong
AU - Yang, Xinrui
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - With the development of new generation intelligent manufacturing and network technologies, the green manufacturing industry, represented by New Energy Vehicle (EV), is transforming to large-scale collaborative network production under regional industrial zone. It promotes the core manufacturing enterprises and related upstream and downstream enterprises to manage the massive, heterogeneous and scattered collaboration data for the whole life-cycle processes, namely design, manufacturing, services and sales, and thus to provide the collaborative services. However, the traditional data management manners are fixed, single and private, and mainly depend on data models and lack on-demand integration, which is unable to cope with the increasing demands for big data management and collaboration relations. Therefore, this paper focuses on EV domain, and studies on the new generation core enterprise-dominated collaborative dataspace management framework. Firstly, the data management requirements for the whole life cycle business collaboration of EV enterprises zone are given. Then, according to the requirements, the collaboration framework is developed, which includes resource layer, space layer, service layer and subject layer. Finally, the collaborative design case is applied to verify the feasibility and practicability of dataspace framework, which provides theoretical and application references for the data integration and management, and thus to urge the core enterprise-dominated whole life cycle business collaboration.
AB - With the development of new generation intelligent manufacturing and network technologies, the green manufacturing industry, represented by New Energy Vehicle (EV), is transforming to large-scale collaborative network production under regional industrial zone. It promotes the core manufacturing enterprises and related upstream and downstream enterprises to manage the massive, heterogeneous and scattered collaboration data for the whole life-cycle processes, namely design, manufacturing, services and sales, and thus to provide the collaborative services. However, the traditional data management manners are fixed, single and private, and mainly depend on data models and lack on-demand integration, which is unable to cope with the increasing demands for big data management and collaboration relations. Therefore, this paper focuses on EV domain, and studies on the new generation core enterprise-dominated collaborative dataspace management framework. Firstly, the data management requirements for the whole life cycle business collaboration of EV enterprises zone are given. Then, according to the requirements, the collaboration framework is developed, which includes resource layer, space layer, service layer and subject layer. Finally, the collaborative design case is applied to verify the feasibility and practicability of dataspace framework, which provides theoretical and application references for the data integration and management, and thus to urge the core enterprise-dominated whole life cycle business collaboration.
KW - business collaboration
KW - core enterprise
KW - dataspace framework
KW - life cycle
KW - new energy vehicle (EV)
UR - https://www.scopus.com/pages/publications/85145571508
U2 - 10.1109/ICDACAI57211.2022.00037
DO - 10.1109/ICDACAI57211.2022.00037
M3 - 会议稿件
AN - SCOPUS:85145571508
T3 - Proceedings - 2022 International Conference on Data Analytics, Computing and Artificial Intelligence, ICDACAI 2022
SP - 145
EP - 151
BT - Proceedings - 2022 International Conference on Data Analytics, Computing and Artificial Intelligence, ICDACAI 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 International Conference on Data Analytics, Computing and Artificial Intelligence, ICDACAI 2022
Y2 - 15 August 2022 through 16 August 2022
ER -