4.6 Article

Digital Twin and Smart Manufacturing in Industries: A Bibliometric Analysis with a Focus on Industry 4.0

Journal

SENSORS
Volume 22, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/s22041388

Keywords

digital twin; smart manufacturing; Industry 4; 0; bibliometric analysis

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This research used bibliometric analysis to examine the production of scientific literature on digital twin and smart manufacturing in the context of Industry 4.0. The research found that China had the highest knowledge output, Tao F. and Soderberg R. were the main authors, and Elsevier was the main publisher. Digital twin is expected to be an important part of future technologies due to its rapid ascension.
Technology is being used in our society in all areas, mostly in industry, and generates the most interest in current research since it is a part of day-to-day activities. The main objective of this research was to use bibliometric analysis to analyze the production of scientific literature on digital twin and smart manufacturing with a focus on Industry 4.0, using information from the Web of Science database. To conduct the study, the keywords necessary for data selection were chosen, and then analyzed based on different variables such as author productivity, citations, most productive institutions, publishers with the highest number of publications, scientific document classification, countries with the highest number of publications, and a network analysis using VOSviewer. The results showed Tao F. and Soderberg R. were the main authors, that China was the country with the highest knowledge, and Elsevier was the main publisher. Although the subject has only been in publication for five years, digital twin will constitute an important part of future technologies due to its rapid ascension, proof of this being its yearly productivity (2020 producing the highest number of materials). Papers published in 2021 were excluded, but the difference between the numbers of materials found and those analyzed shows that 2021 will be even more productive than 2020.

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