process digital twin

Process Digital Twin is a real-time simulation model of a specific manufacturing process step — combining physics-based models with inline measurement data to predict process outcomes, optimize recipes, and enable model-based process control.

Key Capabilities

  • Forward Prediction: Given recipe inputs, predict outputs (film thickness, CD, composition, uniformity).
  • Inverse Optimization: Given desired outputs, find the optimal recipe inputs.
  • Real-Time Calibration: Continuously update model parameters with actual measurement data.
  • Sensitivity Analysis: Identify which recipe parameters most strongly affect each output.

Why It Matters

  • Recipe Development: Accelerates recipe development by reducing the number of physical experiments.
  • Process Transfer: Transfer recipes between tools by adjusting for tool-specific differences via the digital twin.
  • Predictive Quality: Predict wafer quality from recipe parameters before measurement results are available.

Process Digital Twin is the process in silico — a calibrated, real-time simulation of each process step for prediction, optimization, and control.

Go deeper with CFSGPT

Get AI-powered deep-dives, save terms, and run advanced simulations — free account.

Create Free Account