Precision Matching Optimization of Optical Metrology and Inspection Equipment for Yield Enhancement in Semiconductor Manufacturing

As semiconductor manufacturing continues to scale down, the precision and reliability of high-resolution optical inspection equipment have become critical to maintaining process yield. However, variations in hardware sensitivity and parameter settings among identical tools often lead to inconsistencies in defect detection, undermining the stability of process control. This study proposes an automated hardware matching framework that combines a structured calibration sample fabricated using a Particle Deposition System (PDS) with a residual matrix-based linear interpolation algorithm. The proposed method enables automatic alignment of sensitivity responses across tools by quantifying detection discrepancies and deriving optimal settings for laser power and time delay integration (TDI) gain. Applied to 191 optical inspection tools in a Samsung Electronics high-volume manufacturing (HVM) line, the approach achieved a sensitivity matching accuracy within ±2% and reduced preventive maintenance (PM) time by 45%. Deployed across 191 IS4100 patterned-wafer optical inspectors operating at after-develop (ADI), after-etch (AEI), and post-CMP inspection (PCI) checkpoints, the matched fleet provided consistent in-line gating of excursions, aligning with the observed 0.41-pp improvement in production yield. This framework demonstrates a significant advancement over manual calibration approaches and validates its potential as a core enabling technology for Smart Fab and Unattended Fab environments.