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.