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Cluster Computing
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17-04-2017

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

Authors: Di Li, Hao Tang, Shiyong Wang, Chengliang Liu

Published in: Cluster Computing | Issue 2/2017

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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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Metadata
Title
A big data enabled load-balancing control for smart manufacturing of Industry 4.0
Authors
Di Li
Hao Tang
Shiyong Wang
Chengliang Liu
Publication date
17-04-2017
Publisher
Springer US
Published in
Cluster Computing / Issue 2/2017
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-0852-1

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