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A big data enabled load-balancing control for smart manufacturing of Industry 4.0

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Abstract

The concept of “Industry 4.0” that covers the topics of Internet of Things, cyber-physical system, and smart manufacturing, is a result of increasing demand of mass customized manufacturing. In this paper, a smart manufacturing framework of Industry 4.0 is presented. In the proposed framework, the shop-floor entities (machines, conveyers, etc.), the smart products and the cloud can communicate and negotiate interactively through networks. The shop-floor entities can be considered as agents based on the theory of multi-agent system. These agents implement dynamic reconfiguration in a collaborative manner to achieve agility and flexibility. However, without global coordination, problems such as load-unbalance and inefficiency may occur due to different abilities and performances of agents. Therefore, the intelligent evaluation and control algorithms are proposed to reduce the load-unbalance with the assistance of big data feedback. The experimental results indicate that the presented algorithms can easily be deployed in smart manufacturing system and can improve both load-balance and efficiency.

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Acknowledgements

This work was supported in part by the National Science Foundation of China (Grant No. 51605168), the National Program on Key Basic Research Project of China (Grant No. 2013CB035403), the Science and Technology Planning Project of Guangdong Province (Grant Nos. 2016A010102008 and 2014B090921003), the Science and Technology Planning Project of Guangzhou City (Grant Nos. 201508030007 and 201604010064), the National Key Technology R&D Program of China (No. 2014BAD08B01), and the program Of Shanghai Subject Chief Scientist (Grant No. 14XD1402000).

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Authors and Affiliations

  1. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China

    Di Li, Hao Tang & Shiyong Wang

  2. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China

    Chengliang Liu

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  1. Di Li
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  2. Hao Tang
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  3. Shiyong Wang
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Correspondence to Shiyong Wang.

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Li, D., Tang, H., Wang, S. et al. A big data enabled load-balancing control for smart manufacturing of Industry 4.0. Cluster Comput 20, 1855–1864 (2017). https://doi.org/10.1007/s10586-017-0852-1

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