Digital Twins for Control Optimization: SCADA-Driven Simulation, Prediction & Response

Digital twins are rapidly becoming one of the most powerful tools in industrial automation, enabling real-time simulation, predictive modeling, and autonomous decision support across critical operations. In SCADA-controlled environments, the integration of digital twins and industrial AI offers a new frontier for process optimization—allowing operators to test control strategies virtually, detect anomalies before they escalate, and respond to failures with minimal downtime.

This panel will explore how digital twins can be built from SCADA data streams, historian records, and real-world operational feedback to continuously refine system performance. Experts will discuss use cases such as modeling load changes in energy grids, forecasting equipment health in manufacturing, optimizing pumping sequences in water systems, and reducing risk during operational changes in oil & gas and transportation environments. Attendees will gain actionable insights into architecture requirements, data fidelity challenges, deployment approaches, and how AI-enhanced twins can improve efficiency, resilience, and control accuracy at scale.

Key Discussion Points:

• How SCADA data feeds high-fidelity digital twins for real-time simulation

• AI-powered prediction for failure detection, state forecasting & dynamic response

• Designing twins for continuous learning, adaptation & closed-loop optimization

• Operational benefits, risk reduction & workforce enablement

• Roadmap toward full integration with autonomous control environments