Driving Utility Efficiency in Semiconductor Fabs through Real-Time Optimization and Advanced Control

Semiconductor manufacturing is among the most energy-intensive industries, with increasing sustainability demands and volatile utility costs placing greater pressure on operations. This presentation introduces a powerful dual-solution strategy to meet these challenges: AI-enabled Advanced Process Control (APC) combined with a real-time Online Utility Digital Twin. Together, they enable continuous optimization and intelligent control of utility networks, including chilled water, steam, power, and fuel systems.
The high-fidelity Utility Digital Twin minimizes energy costs by dynamically balancing utility supply and demand across the site. It continuously identifies the optimal configuration and loading of chillers, boilers, turbines, and power generation assets based on real-time production needs, tariffs, and emissions constraints. Complementing this, the AI-driven APC system executes the optimizer’s targets—stabilizing temperature fluctuations, header pressures, and minimizing fuel consumption by adapting in real time to process variability.
Additionally, state-based control are incorporated to optimize transitions such as utility system startups, shutdowns, and load changes. This ensures that utility performance remains efficient and safe not only during steady-state operation, but also throughout dynamic events that traditionally introduce energy waste and operational risk.
Together, this integrated approach lays the foundation for autonomous utility optimization—delivering lower energy costs and emissions without compromising process stability or yield.