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This paper focuses on optimizing the complexity of scanned digital twin models for use in cross reality (XR) devices that support the Industry 5.0 concept. The proposed optimization method uses Unreal Engine’s Nanite technology to optimize model complexity, providing a more efficient alternative to the common use of different mosaic levels of detail (LOD). In addition, the methodology includes automatic detection of virtual device performance and dynamic optimization of model complexity in real time from frame rate measurements. The experiment consists of two parts where the first part describes the methods for creating a digital model using scanning. The second part involves transferring the finished model to the virtual environment, direct optimization for use in XR, and an example of a blueprint program for directly displaying the FPS of an XR device in real time. The result of the given experiment should show whether this methodology significantly improves rendering performance and whether it maintains high frame rates while maintaining visual quality. This adaptive optimization framework demonstrates the potential for scalable and efficient deployment of complex digital twin models in XR, contributing to more sustainable and affordable Industry 5.0 solutions.

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Optimalization of Scanned Digital Twin Models for XR Devices in Concept of Industry 5.0

  • 会议论文

  • 发表日期：

    2026年

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  • Anastasiia Nazim,
  • Kamil Židek,
  • Michal Duhančík,
  • Peter Lazorík,
  • Amberlynn Bonello

摘要

This paper focuses on optimizing the complexity of scanned digital twin models for use in cross reality (XR) devices that support the Industry 5.0 concept. The proposed optimization method uses Unreal Engine’s Nanite technology to optimize model complexity, providing a more efficient alternative to the common use of different mosaic levels of detail (LOD). In addition, the methodology includes automatic detection of virtual device performance and dynamic optimization of model complexity in real time from frame rate measurements. The experiment consists of two parts where the first part describes the methods for creating a digital model using scanning. The second part involves transferring the finished model to the virtual environment, direct optimization for use in XR, and an example of a blueprint program for directly displaying the FPS of an XR device in real time. The result of the given experiment should show whether this methodology significantly improves rendering performance and whether it maintains high frame rates while maintaining visual quality. This adaptive optimization framework demonstrates the potential for scalable and efficient deployment of complex digital twin models in XR, contributing to more sustainable and affordable Industry 5.0 solutions.