Defect Inspection and Reduction
Session Chairs: Alexa Greer, George Kong
In-line inspection is critical for semiconductor processing. The session talks about defect inspection, review and classification. This discussion includes application of machine learning to optimize use of inspection and review tools for defect learnings.
Tuesday, May 14, 2024
1:50 PM ET
5.1 Process Control Solutions for GaN-on-Si Devices in a Production Line
F. Carboni, L. Perego, D. Capelli, L. Czeppel, M. Bollin, C. Adamo, B. Moio, STMicroelectronics; L. Barbisan, F. Bellando, M. Salamone, P. Sharma, P. Parisi, S. Deepak, M. Dayyala, KLA
5.2 Critical Defect Detection at 3nm Technology Node: Enhanced Detection Using DUV Optical Inspection Technology with AI-Based Algorithm
S. Chiu, M. Peng, Y. Wei, K. Cheng, T. Chen, Taiwan Semiconductor Manufacturing; H. Chou, M. Wu, K. H. Su, N. Shushan, A. Mizrahi, S. Maurya, G. Danieli, G. Reut, Applied Materials
5.3 Effective Downsampling Techniques for SEM Defect Inspection Using Design Insights in Machine Learning
Q. Xie, S. Jayaram, K. Viswanatha, S. Krishnankutty, F. Huguennet, R. Soni, A. Basu, Siemens EDA
5.4 Difference Image-Based Training Sets for Automatic Defect Classification at Outgoing Inspection
M. Sidorchuk, N. Caprotti, M. Kilicoglu, P.S. Venkatachalam, S. Marble, B. Trapp, P. P. Lau, GlobalFoundries