Model Predictive Control in Semiconductor

MPC (Model Predictive Control) in semiconductor manufacturing is a multi-variable control strategy that uses a process model to predict future outputs and optimize control actions over a prediction horizon — considering constraints, interactions between variables, and future setpoint changes.

How Does MPC Work in Fab?

  • Process Model: A dynamic model predicts how process outputs respond to input changes over time.
  • Prediction Horizon: Predict output trajectories several time steps ahead.
  • Optimization: At each step, solve an optimization problem to find the control inputs that minimize future error.
  • Constraints: Explicitly handles input constraints (power limits, flow ranges) and output constraints (spec limits).

Why It Matters

  • Multi-Variable: Handles coupled, interacting process variables better than independent SISO controllers.
  • Constraint Handling: Respects physical process limits while optimizing performance.
  • Thermal Processes: Particularly effective for furnace and thermal CVD processes with slow dynamics and interactions.

MPC is chess-playing process control — looking multiple moves ahead to find the optimal control strategy while respecting all constraints.

Take model predictive control in semiconductor further

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