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| Natura: | Preprint |
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2025
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| Accesso online: | https://arxiv.org/abs/2510.16280 |
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| _version_ | 1866917182193008640 |
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| author | Yang, Hui Aqlan, Faisal Zhao, Richard |
| author_facet | Yang, Hui Aqlan, Faisal Zhao, Richard |
| contents | The rapid evolution of modern manufacturing systems is driven by the integration of emerging metaverse technologies such as artificial intelligence (AI), digital twin (DT) with different forms of extended reality (XR) like virtual reality (VR), augmented reality (AR), and mixed reality (MR). These advances confront manufacturing workers with complex and evolving environments that demand digital literacy for problem solving in the future workplace. However, manufacturing industry faces a critical shortage of skilled workforce with digital literacy in the world. Further, global pandemic has significantly changed how people work and collaborate digitally and remotely. There is an urgent need to rethink digital platformization and leverage emerging technologies to propel industrial evolution toward human-centered manufacturing metaverse (MfgVerse). This paper presents a forward-looking perspective on the development of smart MfgVerse, highlighting current efforts in learning factory, cognitive digital twinning, and the new sharing economy of manufacturing-as-a-service (MaaS). MfgVerse is converging into multiplex networks, including a social network of human stakeholders, an interconnected network of manufacturing things or agents (e.g., machines, robots, facilities, material handling systems), a network of digital twins of physical things, as well as auxiliary networks of sales, supply chain, logistics, and remanufacturing systems. We also showcase the design and development of a learning factory for workforce training in extended reality. Finally, future directions, challenges, and opportunities are discussed for human-centered manufacturing metaverse. We hope this work helps stimulate more comprehensive studies and in-depth research efforts to advance MfgVerse technologies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_16280 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Smart Manufacturing Metaverse via Digital Twinning in Extended Reality Yang, Hui Aqlan, Faisal Zhao, Richard Systems and Control Image and Video Processing The rapid evolution of modern manufacturing systems is driven by the integration of emerging metaverse technologies such as artificial intelligence (AI), digital twin (DT) with different forms of extended reality (XR) like virtual reality (VR), augmented reality (AR), and mixed reality (MR). These advances confront manufacturing workers with complex and evolving environments that demand digital literacy for problem solving in the future workplace. However, manufacturing industry faces a critical shortage of skilled workforce with digital literacy in the world. Further, global pandemic has significantly changed how people work and collaborate digitally and remotely. There is an urgent need to rethink digital platformization and leverage emerging technologies to propel industrial evolution toward human-centered manufacturing metaverse (MfgVerse). This paper presents a forward-looking perspective on the development of smart MfgVerse, highlighting current efforts in learning factory, cognitive digital twinning, and the new sharing economy of manufacturing-as-a-service (MaaS). MfgVerse is converging into multiplex networks, including a social network of human stakeholders, an interconnected network of manufacturing things or agents (e.g., machines, robots, facilities, material handling systems), a network of digital twins of physical things, as well as auxiliary networks of sales, supply chain, logistics, and remanufacturing systems. We also showcase the design and development of a learning factory for workforce training in extended reality. Finally, future directions, challenges, and opportunities are discussed for human-centered manufacturing metaverse. We hope this work helps stimulate more comprehensive studies and in-depth research efforts to advance MfgVerse technologies. |
| title | Towards Smart Manufacturing Metaverse via Digital Twinning in Extended Reality |
| topic | Systems and Control Image and Video Processing |
| url | https://arxiv.org/abs/2510.16280 |