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Industry 4.0 technologies basic network identification

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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.

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Acknowledgements

This paper was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

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Authors and Affiliations

  1. Department of Engineering, University of Santa Cruz do Sul (UNISC), Santa Cruz do Sul, Rio Grande do Sul, Brazil

    Matheus Becker Da Costa, Leonardo Moraes Aguiar Lima Dos Santos, Jones Luís Schaefer & Elpidio Oscar Benitez Nara

  2. Department of Production and Systems Engineering, University of Vale do Rio dos Sinos (UNISINOS), Santa Cruz do Sul, Rio Grande do Sul, Brazil

    Ismael Cristofer Baierle

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  1. Matheus Becker Da Costa
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Correspondence to Elpidio Oscar Benitez Nara.

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Da Costa, M.B., Dos Santos, L.M.A.L., Schaefer, J.L. et al. Industry 4.0 technologies basic network identification. Scientometrics 121, 977–994 (2019). https://doi.org/10.1007/s11192-019-03216-7

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