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Digital Twin-based Product Development and Manufacturing Processes in Virtual Space: Data Visualization Tools and Techniques, Cloud Computing Technologies, and Cyber-Physical Production Systems

Digital Twin-based Product Development and Manufacturing Processes in Virtual Space: Data... Despite the relevance of digital twin-based product development and manufacturing processes in virtual space, only limited research has been conducted on this topic. In this article, we cumulate previous research findings indicating that digital twin-based product development and manufacturing processes in virtual space require performance optimization and maintenance scheduling. We contribute to the literature on digital twin-based smart manufacturing technologies and tools by showing that sensor-based data acquisition and analysis are pivotal in diagnosis and simulation of digital twin-based product development. Throughout February 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “digital twin” + “product development,” “manufacturing processes,” “data visualization tools and techniques,” “cloud computing technologies,” and “cyber-physical production systems.” As we inspected research published in 2022, only 154 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 23, 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, Distiller SR, and MMAT. JEL codes: D53; E22; E32; E44; G01; G41 Keywords: digital twin; cloud computing; cyber-physical production system http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Economics, Management, and Financial Markets Addleton Academic Publishers

Digital Twin-based Product Development and Manufacturing Processes in Virtual Space: Data Visualization Tools and Techniques, Cloud Computing Technologies, and Cyber-Physical Production Systems

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Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
1842-3191
eISSN
1938-212X
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Abstract

Despite the relevance of digital twin-based product development and manufacturing processes in virtual space, only limited research has been conducted on this topic. In this article, we cumulate previous research findings indicating that digital twin-based product development and manufacturing processes in virtual space require performance optimization and maintenance scheduling. We contribute to the literature on digital twin-based smart manufacturing technologies and tools by showing that sensor-based data acquisition and analysis are pivotal in diagnosis and simulation of digital twin-based product development. Throughout February 2022, we performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “digital twin” + “product development,” “manufacturing processes,” “data visualization tools and techniques,” “cloud computing technologies,” and “cyber-physical production systems.” As we inspected research published in 2022, only 154 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, we decided upon 23, 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, Distiller SR, and MMAT. JEL codes: D53; E22; E32; E44; G01; G41 Keywords: digital twin; cloud computing; cyber-physical production system

Journal

Economics, Management, and Financial Markets – Addleton Academic Publishers

Published: Jan 1, 2022

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