Intelligent Manufacturing in the Context of Industry 4.0: A Review

Abstract

Our next generation of industry—Industry 4.0—holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things (IoT)-enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the IoT, cyber-physical systems (CPSs), cloud computing, big data analytics (BDA), and information and communications technology (ICT) that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution.

Keywords

Intelligent manufacturing / Industry 4.0 / Internet of Things / Manufacturing systems / Cloud manufacturing / Cyber-physical system

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Acknowledgements

The authors would like to acknowledge the contributions from the Laboratory for Industry 4.0 Smart Manufacturing Systems (LISMS) at the University of Auckland, and particular those of Pai Zheng, Seyyed Reza Hamzeh, and Shiqiang Yu.

Compliance with ethics guidelines

Ray Y. Zhong, Xun Xu, Eberhard Klotz, and Stephen T. Newman declare that they have no conflict of interest or financial conflicts to disclose.

Funding

RIGHTS & PERMISSIONS

2017 2017 THE AUTHORS. Published by Elsevier LTD on behalf of the Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).