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Industrial Metaverse: Revolutionizing Industry 5.0 with Digital Twins and Extended Reality

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Abstract:

The industrial landscape is transitioning towards Industry 5.0, characterized by the integration of human ingenuity with advanced technological systems. This shift features the adoption of digital twins and extended reality (XR), which together foster a human-centric, technology-augmented industrial ecosystem. This seminar delves into these transformative technologies within the context of the industrial metaverse, addressing the challenges and opportunities they present in merging the digital and physical spaces in industrial settings.

The discussion begins with the development and application of XR interfaces tailored for digital twin-based systems, specifically highlighting a mixed reality interface for an overhead crane. This application serves as a practical entry point into the industrial metaverse, illustrating how digital and physical elements can be effectively synchronized for enhanced operational control and efficiency.

Expanding on this foundation, the talk introduces the TwinXR method, a novel approach that fosters robust integration of digital twins with XR across various industrial contexts. This method enhances operational insights and improves information management, offering scalable and efficient solutions suitable for diverse industrial applications.

Concluding the seminar, the speaker will present a comprehensive architecture for the industrial metaverse that combines digital twins for data flow and semantic models for knowledge synchronization. This architecture supports a cohesive and interconnected metaverse environment tailored to meet the complex demands of industrial systems.

Speaker’s bio:

Xinyi (Joyce) Tu is a Visiting Researcher at the Cyber-Human Lab, Institute for Manufacturing, Department of Engineering, University of Cambridge, where her work focuses on engineering the future of human-technology systems. As she completes her doctoral studies at DigiTwin Lab, Aalto University, Finland, her thesis, “Industrial Metaverse: Revolutionizing Industry 5.0 with Digital Twins and Extended Reality”, explores the integration of digital twins and extended reality to develop cutting-edge industrial applications and interoperable workflows, and outlines a visionary blueprint to the industrial metaverse. Her research is funded by Business Finland and has contributed to significant international academic-industrial co-innovation projects. Joyce actively publishes in peer-reviewed journals and presents at both academic and industry conferences. She is a key contributor to several Industry 5.0 and metaverse initiatives, including the FORGING Expert Forum, Metavethics Institute, Metaverse Standards Forum – Industrial Metaverse Working Group, IEEE Standards Association | IEEE SA - Metaverse Working Group, and IEC (International Electrotechnical Commission) – SEG 15 Metaverse.

Joyce holds a Master of Science in “Robotics, Cognition, Intelligence” from the Technical University of Munich, Germany, and a Bachelor of Engineering in Mechatronics from Tongji University, China, both accoladed with multiple scholarships and awards. Her academic journey is complemented by internships at Siemens PLM in China and Siemens Digital Factory in Germany. Currently, Joyce is also a Senior Data Scientist and Operations Consultant at PwC Finland Advisory, where she works on robust AI strategies, digital transformation, and competitive manufacturing practices. Outside her professional role, Joyce is committed to fostering innovation and inclusivity in the tech community, leading significant hackathons and entrepreneurship events, as well as advocating for the Women in AI community.

Research Interests: Industry X.0, industrial metaverse, digital twins, extended reality, cyber-manufacturing, Industrial Internet of Things, Artificial Intelligence.

LinkedIn: https://www.linkedin.com/in/xinyi-tu-joyce/ Google Scholar: https://scholar.google.com/citations?hl=en&user=leA0PFAAAAAJ

This talk is part of the Cyber-Human Lab Seminar Series series.

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