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The Journal of Supercomputing

, Volume 74, Issue 9, pp 4339–4357 | Cite as

Cloud-based smart manufacturing for personalized candy packing application

  • Shiyong Wang
  • Jiafu WanEmail author
  • Muhammad Imran
  • Di Li
  • Chunhua Zhang
Article

Abstract

Industry 4.0 has been proposed to address personalized consumption demands by building cyber-physical production systems for smart manufacturing. Although cloud manufacturing and some integrated frameworks for smart factory have been presented in literatures, it still lacks industrial applications. In this paper, we use personalized candy packing application as a demonstration to illustrate our smart factory design. We first describe the component layers of the smart factory, i.e., physical devices, private cloud, client terminals, and network, to enable the smart factory to be integrated with other systems, such as banks and logistical network, to cope with personalized consumption demands. Then, we present a scheme for inter-layered interaction. As for the physical devices, we also design an intra-layered negotiation mechanism to implement dynamic reconfiguration, so that the system can support hybrid production of multi-typed products. Finally, we give experimental results to verify efficiency, self-organized process, and hybrid production paradigm of the proposed system.

Keywords

Smart factory Smart manufacturing Industry 4.0 Self-organization Industrial big data 

Notes

Acknowledgments

This work was supported in part by the National Key Technology R&D Program of China (No. 2015BAF20B01), the Science and Technology Planning Project of Guangdong Province (Nos. 2016A010102008 and 2014B090921003), the Science and Technology Planning Project of Guangzhou City (Nos. 201508030007 and 201604010064), the Natural Science Foundation of Guangdong Province (nos. 2016A030313734 and 2016A030313735), and the Fundamental Research Funds for the Central Universities (No. 2015ZZ079). Imran’s work is supported by the Deanship of Scientific Research at King Saud University through Research group No. (RG # 1435-051).

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Shiyong Wang
    • 1
  • Jiafu Wan
    • 1
    Email author
  • Muhammad Imran
    • 2
  • Di Li
    • 1
  • Chunhua Zhang
    • 1
  1. 1.School of Mechanical and Automotive EngineeringSouth China University of TechnologyGuangzhouChina
  2. 2.College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia

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