Digital Twin Modeling in Virtual Enterprises and Autonomous Manufacturing Systems: Deep Learning and Neural Network Algorithms, Immersive Visualization Tools, and Cognitive Data Fusion Techniques
Digital Twin Modeling in Virtual Enterprises and Autonomous Manufacturing Systems: Deep Learning and Neural Network Algorithms, Immersive Visualization Tools, and Cognitive Data Fusion Techniques

Summary/Abstract: In this article, I cumulate previous research findings indicating that the digital twin of manufacturing system can monitor and enhance the product development process. I contribute to the literature on digital twin modeling in virtual enterprises and autonomous manufacturing systems by showing that machine learning algorithms can assist in smart process manufacturing by harnessing visualization capabilities and data mining tools. Throughout March 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “digital twin modeling” + “virtual enterprises,” “autonomous manufacturing systems,” “deep learning and neural network algorithms,” “immersive visualization tools,” and “cognitive data fusion techniques.” As I inspected research published in 2022, only 148 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 21, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, ROBIS, and SRDR.

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