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Industrial Cyberphysical Systems: A Backbone of the Fourth Industrial Revolution

Colombo, Armando W., Karnouskos, Stamatis, Kaynak, Okyay, Shi, Yang, Yin, Shen·2017·IEEE Industrial Electronics Magazine

Abstract

Cyberphysical systems (CPSs) are perceived as the pivotal enabler for a new era of real-time Internet-based communication and collaboration among value-chain participants, e.g., devices, systems, organizations, and humans. The CPS utilization in industrial settings is expected to revolutionize the way enterprises conduct their business from a holistic viewpoint, i.e., from shop-floor to business interactions, from suppliers to customers, and from design to support across the whole product and service lifecycle. Industrial CPS (ICPSs) blur the fabric of cyber (including business) and physical worlds and kickstart an era of systemwide collaboration and information-driven interactions among all stakeholders of the value chain. Therefore, ICPSs are expected to empower the transformation of industry and business at large to a digital, adaptive, networked, and knowledge-based industry with significant long-term impact on the economy, society, environment, and citizens.

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Metadata

Authors
Colombo, A. W., Karnouskos, S., Kaynak, O., Shi, Y., & Yin, S.
Venue
IEEE Industrial Electronics Magazine
Published
2017-03
Volume
11
Issue
1
Pages
6-16
ISSN
1932-4529 (ISSN-L)
OpenAlex
W2598976192
Cited by
399
References
0
FWCI
43.78
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Industrial Cyberphysical Systems: A Backbone of the Fourth Industrial Revolution. https://app.cochat.ai/papers/10.1109/mie.2017.2648857
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Colombo, A. W., Karnouskos, S., Kaynak, O., Shi, Y., & Yin, S. (2017). Industrial Cyberphysical Systems: A Backbone of the Fourth Industrial Revolution. IEEE Industrial Electronics Magazine. https://doi.org/10.1109/mie.2017.2648857

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.