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

Abstract

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.

Digital Twin for a Multifunctional Technology of Flexible Assembly on a Mechatronics Line with Integrated Robotic Systems and Mobile Visual Sensor—Challenges towards Industry 5.0

“…The virtual world consists of digital tools for modeling and simulating technology, specific actions, and operations. The real world is a transposition on the available hardware of all models and representations in the virtual world with remote monitoring [ 4 , 5 ].…”

“…A digital twin is a virtual representation of a real-world product or asset, with the benefit of continuous, real-time data from a product or a manufacturing technology. Digital twins provide insights to increase productivity, to improve product quality, components and subassemblies recovery, reduce downtime, optimization, and control of manufacturing processes [ 4 , 5 , 18 ].…”

Bibliometric Analysis of Fourth Industrial Revolution Applied to Material Sciences Based on Web of Science and Scopus Databases from 2017 to 2021

“…Few articles deal with the bibliometric analysis of industry 4.0 applied to material science. Advanced and smart manufacturing have been studied separately based on Scopus or Web of Science (WoS) databases, proving that industry 4.0 is exponentially increasing and just emerging, correspondingly [21,22]. Artificial neural network applications have been explored through Scopus, highlighting their importance in engineering fields [23].…”

Digital Twin for Human–Robot Interactions by Means of Industry 4.0 Enabling Technologies

“…With the onset of Industry 4.0, manufacturing industries have increasing access to various technology drivers, such as big data and analytics, the Industrial Internet of Things (IIOT), cyber-physical systems (CPSs), cloud computing, additive manufacturing and augmented, virtual and mixed realities (AR/VR/MR), among others [5]. More recently, the concept of digital twins (DTs) has been introduced alongside these rapidly expanding technologies [6,7]. Digital twins offer a physical model in real space that can be connected with a corresponding virtual model in virtual space using data and information [8].…”