Methodology for Transferring Virtual Models to XR Devices for Human Interaction Within the Concept of Industry 5.0

This study proposes a unified, technically reproducible methodology for transforming real industrial systems into interactive digital twins deployable across extended reality (XR) environments. The approach integrates all stages required to convert physical equipment into a performant virtual representation: selection of acquisition methods; creation of 3D models using CAD modeling, photogrammetry, structuredlight scanning, and laser scanning; geometric cleaning and polygon optimization; preparation of the virtual environment in Unreal Engine; model optimization using tessellation and Nanite; and implementation of realtime data connectivity. The methodology employs the Asset Administration Shell (AAS) standard and OPC UA protocol to synchronize the virtual model with operational data from physical devices, enabling dynamic updates of system states. Interaction logic is implemented through Blueprint scripting, allowing the digital twin to visualize parameters, monitor device behavior, and execute control functions within XR. Experimental evaluation shows that geometric optimization combined with Nanite-based rendering increases runtime performance by up to 167% for scanned models compared to tessellation-based rendering, while maintaining stable real-time visualization. The results demonstrate that heterogeneous 3D models can be successfully optimized for XR constraints and integrated with real industrial signals, forming fully functional digital twins. The methodology provides a scalable foundation for deploying XR-based monitoring, training, and control applications, highlighting its relevance for Industry 5.0 systems that require seamless humanmachine interaction.