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Applied Computer Science
Article . 2021 . Peer-reviewed
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Applied Computer Science
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Applied Computer Science
Article . 2021
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CYBER-PHYSICAL SYSTEMS TECHNOLOGIES AS A KEY FACTOR IN THE PROCESS OF INDUSTRY 4.0 AND SMART MANUFACTURING DEVELOPMENT

Authors: ZUBRZYCKI, Jarosław; ŚWIĆ, Antoni; SOBASZEK, Łukasz; KOVAC, Juraj; KRALIKOVA, Ruzena; JENCIK, Robert; SMIDOVA, Natalia; +3 Authors

CYBER-PHYSICAL SYSTEMS TECHNOLOGIES AS A KEY FACTOR IN THE PROCESS OF INDUSTRY 4.0 AND SMART MANUFACTURING DEVELOPMENT

Abstract

The continuous development of production processes is currently observed in the fourth industrial revolution, where the key place is the digital transformation of production is known as Industry 4.0. The main technologies in the context of Industry 4.0 consist Cyber-Physical Systems (CPS) and Internet of Things (IoT), which create the capabilities needed for smart factories. Implementation of CPS solutions result in new possibilities creation – mainly in areas such as remote diagnosis, remote services, remote control, condition monitoring, etc. In this paper, authors indicated the importance of Cyber-Physical Systems in the process of the Industry 4.0 and the Smart Manufacturing development. Firstly, the basic information about Cyber-Physical Production Systems were outlined. Then, the alternative definitions and different authors view of the problem were discussed. Secondly, the conceptual model of Cybernetic Physical Production System was presented. Moreover, the case study of proposed solution implementation in the real manufacturing process was presented. The key stage of the verification concerned the obtained data analysis and results discussion.

Keywords

iot, Electronic computers. Computer science, cps, Information technology, QA75.5-76.95, industry 4.0, machine monitoring, T58.5-58.64

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    7
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Average
gold