Deep Integration of Virtual Reality and Digital Twin: An Empirical Study on the Innovation of Manufacturing Industry and Cross-Domain Expansion

With the rapid progress in computer science and network information technology, the integration of Virtual Reality (VR) and Digital Twin technologies has emerged as a focal point in research. This study explores the innovative applications of these two technologies in the realms of interactive simulation, predictive analysis, and remote operation. Our team has constructed a Digital Twin experimental platform based on VR, targeting the simulation of manufacturing assembly lines to enhance their performance across diverse working environments. The findings reveal that the Digital Twin platform, when combined with VR, can boost production efficiency and decrease operational errors. Additionally, the research uncovers that three-dimensional modeling and sensor data can replicate the dynamics of the physical world within virtual space, thereby enhancing the immersive experience of VR and the intuitiveness of human-computer interaction. According to our team's simulation results, under certain conditions, adjusting the VR interface parameters can lead to a 15% increase in production efficiency and achieve a fault prediction accuracy of 92%. Furthermore, the Digital Twin model has demonstrated its value in remote education and medical consultation, transcending the constraints of physical distance. Overall, this research is of significant importance for advancing the convergence of VR and Digital Twin technologies, elevating the level of industrial intelligence, and broadening the scope of interdisciplinary applications.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1109/icftic64248.2024.10912854
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
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article

Deep Integration of Virtual Reality and Digital Twin: An Empirical Study on the Innovation of Manufacturing Industry and Cross-Domain Expansion

B. Liu
Impact of AI and Big Data on Business and Society
article

Deep Integration of Virtual Reality and Digital Twin: An Empirical Study on the Innovation of Manufacturing Industry and Cross-Domain Expansion

B. Liu
article en

Abstract

With the rapid progress in computer science and network information technology, the integration of Virtual Reality (VR) and Digital Twin technologies has emerged as a focal point in research. This study explores the innovative applications of these two technologies in the realms of interactive simulation, predictive analysis, and remote operation. Our team has constructed a Digital Twin experimental platform based on VR, targeting the simulation of manufacturing assembly lines to enhance their performance across diverse working environments. The findings reveal that the Digital Twin platform, when combined with VR, can boost production efficiency and decrease operational errors. Additionally, the research uncovers that three-dimensional modeling and sensor data can replicate the dynamics of the physical world within virtual space, thereby enhancing the immersive experience of VR and the intuitiveness of human-computer interaction. According to our team's simulation results, under certain conditions, adjusting the VR interface parameters can lead to a 15% increase in production efficiency and achieve a fault prediction accuracy of 92%. Furthermore, the Digital Twin model has demonstrated its value in remote education and medical consultation, transcending the constraints of physical distance. Overall, this research is of significant importance for advancing the convergence of VR and Digital Twin technologies, elevating the level of industrial intelligence, and broadening the scope of interdisciplinary applications.

Siam University (TH)
Industry, innovation and infrastructure
Openalex Percentile: Top 66%
Impact of AI and Big Data on Business and Society
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Deep Integration of Virtual Reality and Digital Twin: An Empirical Study on the Innovation of Manufacturing Industry and Cross-Domain Expansion — B. Liu · (2024) | TGRS Research Map | TGRS