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- Yang, C., et al.
(författare)
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Cloud-edge-device Collaboration Mechanisms of Cloud Manufacturing for Customized and Personalized Products
- 2022
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Ingår i: 2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1517-1522
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Konferensbidrag (refereegranskat)abstract
- 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.
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- Yang, C., et al.
(författare)
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Software-defined Cloud Manufacturing in the Context of Industry 4.0
- 2019
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Ingår i: WRC SARA 2019 - World Robot Conference Symposium on Advanced Robotics and Automation 2019. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728155524 ; , s. 184-190
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Konferensbidrag (refereegranskat)abstract
- In the practice of 'Cloud Manufacturing (CMfg)' or 'Industrial Internet', there still exist key problems, including: 1) big data analytics and decision-making in the cloud could not meet the requirements of time-sensitive manufacturing applications, moreover uploading ZettaBytes of future device data to the cloud may cause serious network congestion, 2) the manufacturing system lacks openness and evolvability, thus restricting the rapid optimization and transformation of the system, 3) big data from the shop-floor IoT devices and the internet has not been effectively utilized to guide the optimization and upgrade of the manufacturing system. In view of these key practical problems, we propose an open evolutionary architecture of intelligent CMfg system with collaborative edge and cloud processing capability. Hierarchical gateways near shop-floor things are introduced to enable fast processing for time-sensitive applications. Big data in another dimension from the software defined perspective will be used to decide the efficient operations and highly dynamic upgrade of the system. From the software system view, we also propose a new mode - AI-Mfg-Ops (AI-enabled Cloud Manufacturing Operations) with a supporting framework, which can promote the fast operation and upgrading of CMfg systems with AI enabled monitoring-analysis-planning-execution close loop. This work can improve the universality of CMfg for real-time fast response and operation upgrading.
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