Public defence in Mechanical Engineering, M.Sc. Xinyi Tu

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) technologies, which together foster a human-centric, technology-augmented industrial ecosystem. This thesis 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 thesis begins with the development of an XR application tailored for digital twin-based industrial systems, specifically a mixed reality interface for operating an overhead crane and measurement protocols for assessing the application’s control accuracy. This work overcomes the limitations of current industrial XR solutions which lack bidirectional dynamic data interaction with digital twins, thus serving as a practical entry point into the industrial metaverse. 

Expanding on this foundation, the thesis proposes the TwinXR method, a novel approach that fosters robust integration of digital twins with XR across various industrial contexts. Validated through proof-of-concept implementations in two case studies, TwinXR enables the development of a single XR solution that can be efficiently scaled and adapted for multiple setups. By leveraging digital twin descriptions, this method enhances information management and system interoperability, making it suitable for a wide range of industrial applications. 

The thesis concludes with a comprehensive architecture for the industrial metaverse that seamlessly integrates physical factories with the metaverse, facilitated by the interplay of digital twins for data flow and semantic models for knowledge synchronization. This proposed architecture extends beyond prevailing consumer-centric architectures and their narrow focus on XR, and supports a cohesive and interconnected metaverse environment tailored to meet the complex demands of industrial systems. 

Overall, the thesis provides a thorough exploration of the industrial metaverse, traversing from focused applications to broader integration methodology, culminating in an expansive architectural design. The findings highlight the transformative impact of the industrial metaverse in the Industry 5.0 context, where digital twins and XR consolidate to reshape industrial processes and enhance human-machine collaboration. 

Doctoral Student: Xinyi Tu 

Opponent: Prof. Tauno Otto, Tallinn University of Technology, Estonia

Custos: Prof. Kari Tammi, Aalto University School of Engineering, Department of Mechanical Engineering 

The public defense will be organized in Lecture Hall 216, Otakaari 4 and online on Zoom (Meeting ID: 681 1363 7164 Passcode: 26662666). 

The thesis is publicly displayed 10 days prior to the defense in the publication archive Aaltodoc of Aalto University. 

Contact information of doctoral student: 

Doctoral theses in the School of Engineering: https://aaltodoc.aalto.fi/handle/123456789/49