TY - GEN
T1 - Analysis and Design for Intelligent Manufacturing Cloud Control Systems
AU - Yan, Ce
AU - Li, Yiran
AU - Xia, Yuanqing
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11/6
Y1 - 2020/11/6
N2 - New cloud services are being developed to support a varied of technology applications. In this paper, a new cloud service: Intelligent Manufacturing Cloud Control is given, which includes different functionalities of intelligent manufacturing system as a model: cloud feedback control, cloud worflow scheduling, cloud containers. This paper focuses on the fact that cloud control system is most time-critical and demanding functionality. Hence, a novel intelligent manufacturing cloud control systems architecture is proposed, and time savings under such proposed architecture is fully analyzed. It is shown that signficant cost and time savings could be achieved, mainly due to the virtualization of controllers and the reduction of hardware cost. Moreover, a task-based delay triggered cloud worflow scheduling strategy is proposed to minimize the makespan of intelligent manufacturing cloud control worflows. To experimentally evaluate our approach, the controllers are implemented on cloud environment and control industry-standard plant. The experimental results show that the proposed cloud controllers perform indistinguishably from the local controllers.
AB - New cloud services are being developed to support a varied of technology applications. In this paper, a new cloud service: Intelligent Manufacturing Cloud Control is given, which includes different functionalities of intelligent manufacturing system as a model: cloud feedback control, cloud worflow scheduling, cloud containers. This paper focuses on the fact that cloud control system is most time-critical and demanding functionality. Hence, a novel intelligent manufacturing cloud control systems architecture is proposed, and time savings under such proposed architecture is fully analyzed. It is shown that signficant cost and time savings could be achieved, mainly due to the virtualization of controllers and the reduction of hardware cost. Moreover, a task-based delay triggered cloud worflow scheduling strategy is proposed to minimize the makespan of intelligent manufacturing cloud control worflows. To experimentally evaluate our approach, the controllers are implemented on cloud environment and control industry-standard plant. The experimental results show that the proposed cloud controllers perform indistinguishably from the local controllers.
KW - Cloud control systems
KW - cloud control delays
KW - cloud workflow scheduling
KW - docker container
KW - intelligent manufacturing
UR - http://www.scopus.com/inward/record.url?scp=85100919853&partnerID=8YFLogxK
U2 - 10.1109/CAC51589.2020.9327056
DO - 10.1109/CAC51589.2020.9327056
M3 - Conference contribution
AN - SCOPUS:85100919853
T3 - Proceedings - 2020 Chinese Automation Congress, CAC 2020
SP - 7174
EP - 7179
BT - Proceedings - 2020 Chinese Automation Congress, CAC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Chinese Automation Congress, CAC 2020
Y2 - 6 November 2020 through 8 November 2020
ER -