Industry 4.0 technologies basic network identification

• Published in: Scientometrics 2019-11, Vol.121 (2), p.977-994
• Main Authors: Da Costa, Matheus Becker, Dos Santos, Leonardo Moraes Aguiar Lima, Schaefer, Jones Luís, Baierle, Ismael Cristofer, Nara, Elpidio Oscar Benitez
• Format: Article
• Language: English
• Subjects: Algorithms; Automation; Bibliometrics; Computer Science; Cyber-physical systems; Data mining; Industrial applications; Industrial Revolution; Information Storage and Retrieval; Library Science; New technology; Robotics; State-of-the-art reviews
• ISSN: 0138-9130; 1588-2861
• DOI: 10.1007/s11192-019-03216-7

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.