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Want to understand how to connect real-world process data with virtual models? Curious about how Digital Twins can enhance monitoring, optimization, and predictive maintenance in industrial environments?
Join our hands-on session and explore how combining physics, data, and AI enables the creation of digital replicas that bring insight and efficiency to complex systems.
Designing a useful Digital Twin requires more than collecting data — it means building a consistent bridge between physical models, real-time measurements, and computational intelligence.
This workshop offers a practical introduction to the Digital Twin approach, guiding participants through the end-to-end workflow: from experimental data acquisition and model integration to visualization, validation, and scenario testing, using the Plasma Group’s fluidized-bed reactor demonstrator as a real-world example.
What you'll get
Over the course of this interactive session, you will:
- During this interactive session, you will:
- Discover the foundations of Digital Twin architecture — physical layer, data layer, and model layer.
- Learn how to connect sensor data streams with physics-based and statistical models.
- Explore data synchronization, model calibration, and visualization in practice.
- Interact with live process data from the plasma demonstrator.
- Understand how Digital Twins can support process monitoring, optimization, and scale-up.
- Gain insights into data management, reproducibility, and cross-domain transferability.
