Artificial Intelligence-Enhanced Digital Twin Systems Engineering Towards the Industrial Metaverse in the Era of Industry 5.0
He Zhang, Yilin Li, Shuai Zhang, Lu-Kai Song, Fei Tao
- Year
- 2025
- Citations
- 16
- Access
- Open access
Abstract
Abstract With the continuous advancement and maturation of technologies such as big data, artificial intelligence, virtual reality, robotics, human-machine collaboration, and augmented reality, many enterprises are finding new avenues for digital transformation and intelligent upgrading. Industry 5.0, a further extension and development of Industry 4.0, has become an important development trend in industry with more emphasis on human-centered sustainability and flexibility. Accordingly, both the industrial metaverse and digital twins have attracted much attention in this new era. However, the relationship between them is not clear enough. In this paper, a comparison between digital twins and the metaverse in industry is made firstly. Then, we propose the concept and framework of Digital Twin Systems Engineering (DTSE) to demonstrate how digital twins support the industrial metaverse in the era of Industry 5.0 by integrating systems engineering principles. Furthermore, we discuss the key technologies and challenges of DTSE, in particular how artificial intelligence enhances the application of DTSE. Finally, a specific application scenario in the aviation field is presented to illustrate the application prospects of DTSE.
Keywords
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