Industry 4.0 technologies basic network identification

Matheus Becker Costa (), Leonardo Moraes Aguiar Lima Santos (), Jones Luís Schaefer (), Ismael Cristofer Baierle () and Elpidio Oscar Benitez Nara ()
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Matheus Becker Costa: University of Santa Cruz do Sul (UNISC)
Leonardo Moraes Aguiar Lima Santos: University of Santa Cruz do Sul (UNISC)
Jones Luís Schaefer: University of Santa Cruz do Sul (UNISC)
Ismael Cristofer Baierle: University of Vale do Rio dos Sinos (UNISINOS)
Elpidio Oscar Benitez Nara: University of Santa Cruz do Sul (UNISC)

Scientometrics, 2019, vol. 121, issue 2, No 17, 977-994

Abstract: Abstract Nowadays, one of the most discussed topics in the technology industry is related to the new industrial revolution, called Industry 4.0. Industry 4.0 will transform entire production systems and products. However, the subject still lacks systematic study in its state of the art. This study seeks to identify relations or associations among emerging technologies in Industry 4.0. Through publications on its theme and keywords, a data mining technique was applied to help identify the network of associations with a new bibliometric approach. In order to reach the objective of the study, we utilized the Apriori algorithm in the Waikato Environment for Knowledge Analysis software. In this process, 15 association rules were found that met the input metrics: support, confidence, and lift. The rules point to two main technologies, internet of things and cyber-physical systems. This research points out that these technologies are key elements of Industry 4.0, and are related to others, such as cloud, big data, automation, virtualization, and robotics. Through data mining, the best associations and relations of the technologies in Industry 4.0 were identified. Moreover, this study pointed out the most important technologies for the new industrial revolution and the complementary technologies of each identified group. Thus, this network of technologies provides a basic guide for future works, which seek to deepen the characteristics of these relations.

Keywords: Industry 4.0; Big data; CPS; IoT; Data mining; Apriori algorithm; 05E30 (search for similar items in EconPapers)
JEL-codes: L60 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s11192-019-03216-7

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