Abstract

The depth development and widespread application of edge intelligence technology based on the Internet of Things has led to edge-cloud collaboration and related research. In recent years, with the rapid development of the Internet of Things and the formation of super-city groups, the management characteristics of enterprises with multiple manufacturing plants served for headquarters have become increasingly obvious. The problem of order dynamic fluctuations caused by personalized customization requirements has become more prominent, which makes it impossible to do global long-period prediction or real-time short-period response relied solely on the cloud or edge. Therefore, this paper proposes a production system scheduling framework under the edge-cloud collaborative paradigm based on the dynamic fluctuation of orders under these background, and builds an edge-cloud collaborative scheduling model, which guarantees real-time distributed scheduling at the edge. It enabled the cloud to periodically predict the total completion time of production tasks at the headquarters based on the value-added data uploaded by the edge, and to support more accurate and efficient scheduling at the edge based on the prediction results. Finally, an example analysis proved the rationality of the scheduling mechanism and the effectiveness of the scheduling model. The proposed method can provide a certain reference for task scheduling in the edge-cloud collaborative production paradigm.

Highlights

  • Since the first industrial revolution, production paradigms have been emerged and developed with the changes of market demand and advancing of technology

  • With the development and deep integration of cloud computing, Internet of Things (IoT), big data, service-oriented, and other advanced technologies, cloud manufacturing has emerged and developed into an emerging networked manufacturing mode that integrates various manufacturing resources [1]. It is mapped as a cloud service, and provides users with cloud manufacturing services on demand, which makes up for the shortcomings of existing manufacturing modes [2]

  • LITERATURE REVIEW This paper focuses on the scheduling problem of the edge-cloud collaborative (ECC) production paradigm

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Summary

INTRODUCTION

Since the first industrial revolution, production paradigms have been emerged and developed with the changes of market demand and advancing of technology. With the development and deep integration of cloud computing, Internet of Things (IoT), big data, service-oriented, and other advanced technologies, cloud manufacturing has emerged and developed into an emerging networked manufacturing mode that integrates various manufacturing resources [1]. In view of the highly decentralized manufacturing resources and data explosion in the IoT environment, cloud-side scheduling or manufacturing edge-side scheduling can no longer effectively support the one headquarters and multi factory business mode and respond to the problem of orders dynamic fluctuation caused by personalized customization demands (research issues). The emergence of the ECC production paradigm enables production systems to have the advantages of super-computing and prediction capabilities in the cloud, and real-time response, high service quality, and data security at the manufacturing edge-side [7]. Conclusions are drawn and the future works are discussed

LITERATURE REVIEW
MODELLING AND CASE VERIFICATION
EDGE-SIDE SCHEDULING OPTIMIZATION MODEL
CONCLUSION AND FUTURE WORK
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