Intelligent Manufacturing in the Context of Industry 4.0: A Review
Интеллектуальное производство в контексте Индустрии 4.0: обзор
2017-10-01
SCID: 54.1/hd3awz8n
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Cloud manufacturingCyber-physical systems (CPSs)Industry 4.0Intelligent manufacturingInternet of Things (IoT)
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Abstract (AI)
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.
Key Findings
1
Industry 4.0 promises greater manufacturing flexibility, mass customization, improved quality, and higher productivity while supporting shorter time-to-market for individualized products.
2
Intelligent manufacturing transforms conventional resources into intelligent objects capable of sensing, acting, and behaving within smart environments.
3
IoT, cyber-physical systems, cloud computing, big data analytics, and ICT are identified as key enabling technologies for intelligent manufacturing.
4
The paper surveys international governmental and corporate strategies, then identifies current challenges and future research directions for realizing Industry 4.0.
5
The review clarifies similarities and differences among intelligent manufacturing, IoT-enabled manufacturing, and cloud manufacturing.
Research Object
intelligent manufacturing in the context of Industry 4.0
Research Subject
the concepts, enabling technologies, similarities and differences, global developments, challenges, and future research directions of intelligent manufacturing
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2017-10-01
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References available in scid.ai8
How Virtualization, Decentralization And Network Building Change The Manufacturing Landscape: An Industry 4.0 Perspective2014
Progress on information and communication technologies in hospitality and tourism2014
Modeling Cyber–Physical Systems2011
A case of implementing RFID-based real-time shop-floor material management for household electrical appliance manufacturers2010
Cloud Migration: A Case Study of Migrating an Enterprise IT System to IaaS2010
Cloud computing: state-of-the-art and research challenges2010
A view of cloud computing2010
Cyber Physical Systems: Design Challenges2008
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