Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

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... 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. JEL codes: D53; E22; E32; E44; G01; G41 Keywords: digital twin; virtual enterprise; autonomous manufacturing system http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Economics, Management, and Financial Markets Addleton Academic Publishers

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

Download PDF
15 pages

Loading next page...
 
/lp/addleton-academic-publishers/digital-twin-modeling-in-virtual-enterprises-and-autonomous-3NMKw8C78K
Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1842-3191
eISSN
1938-212X
Publisher site
See Article on Publisher Site

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. JEL codes: D53; E22; E32; E44; G01; G41 Keywords: digital twin; virtual enterprise; autonomous manufacturing system

Journal

Economics, Management, and Financial Markets – Addleton Academic Publishers

Published: Jan 1, 2022

There are no references for this article.