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Real-Time Digital Twin Architecture for Immersive Industrial Automation Training.

Jessica S Ortiz1, Víctor H Andaluz1, Christian P Carvajal2

  • 1Departamento de Eléctrica, Electrónica y Telecomunicaciones, Universidad de las Fuerzas Armadas ESPE, Sangolquí 171103, Ecuador.

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Summary

This study introduces a real-time Digital Twin architecture for industrial automation training, overcoming equipment access and safety limits. The scalable platform enhances learning with reliable synchronization and high usability.

Keywords:
Digital TwinIndustry 4.0immersive environmentsindustrial IoTnetworked architecturereal-time systems

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Area of Science:

  • Engineering
  • Computer Science
  • Industrial Automation

Background:

  • Industrial automation labs face challenges with equipment access, safety, and scalability.
  • Hands-on experimentation is crucial for Industry 4.0 training but often restricted.
  • Existing solutions lack integrated, real-time, and scalable platforms.

Purpose of the Study:

  • To propose a novel real-time multi-layer Digital Twin architecture.
  • To integrate physical industrial equipment with a virtual environment for enhanced training.
  • To evaluate the system's performance, scalability, and impact on student learning.

Main Methods:

  • Developed a Digital Twin architecture with physical (Siemens S7-1500 PLC), virtual (Unity), HMI, and IoT layers.
  • Implemented a unified communication framework using Ethernet TCP/IP for bidirectional synchronization.
  • Evaluated system performance via synchronization metrics (latency, jitter) and user studies (usability, cognitive workload).

Main Results:

  • Achieved stable PLC-Digital Twin communication with average latency < 15 ms and jitter < 0.5 ms.
  • Demonstrated modular scalability and reliable real-time interaction.
  • Engineering students reported high usability (SUS = 86/100) and reduced cognitive workload (NASA-TLX = 34/100).

Conclusions:

  • The proposed Digital Twin architecture effectively addresses limitations in industrial automation training.
  • The platform offers a scalable and reliable solution for Industry 4.0 education.
  • The system significantly improves learning conditions and user experience.