Cross Domain Anomaly Detection in Semiconductor Manufacturing via Projection Comparison and Reconstruction in Latent Space
Abstract
Photovoltaic wafer manufacturing demands near-zero defects, yet anomaly detection models often fail to generalize across manufacturing lines due to domain shift caused by varying imaging devices and process conditions. This letter presents Projection Comparison and Reconstruction (PCR), a framework for cross-domain anomaly detection. Patch-based Domain Fusion mixes source and target images via grid-wise stochastic patch replacement, explicitly increasing cross-domain distribution overlap. Dual-Teacher Knowledge Distillation combines a frozen domain-agnostic teacher with a trainable adaptive teacher to obtain domain-invariant features for robust reconstruction. PCR achieves state-of-the-art performance, including an 8.07-point image-level AUROC gain on ELAD.
Fields of Study & Subjects
Industrial Vision Systems and Defect Detection
Anomaly Detection Techniques and Applications
Fault Detection and Control Systems
Publication details
- Journal / source
- IEEE Transactions on Semiconductor Manufacturing
- Volume
- 39
- Issue
- 2
- Pages
- 372–374
- Publication date
- 17 February 2026
- Language
- EN