Hybrid Metrology is a strategy that combines measurements from multiple metrology tools to achieve better accuracy than any single technique — using statistical methods (Bayesian inference, regression) to fuse data from OCD, CD-SEM, AFM, and TEM into a single, improved measurement result.

How Does Hybrid Metrology Work?

• Multiple Tools: Measure the same parameter (e.g., CD) with several techniques (OCD, CD-SEM, AFM).
• Cross-Calibration: Establish relationships between tool outputs (bias corrections, scaling factors).
• Fusion: Combine measurements using weighted averaging, Bayesian estimation, or regression models.
• Result: A single "hybrid" measurement with lower uncertainty than any individual tool.

Why It Matters

• Accuracy: Each tool has different systematic errors — combination reduces total measurement uncertainty.
• Reference Metrology: Hybrid values serve as more accurate reference values for tool matching.
• Industry Push: SEMI and NIST actively promote hybrid metrology for sub-nm node requirements.

Hybrid Metrology is the wisdom of many tools — combining multiple measurement techniques for dimensional accuracy beyond any single instrument's capability.