Automated Defect Classification (ADC) and Progression Monitoring (DPM) in wafer fab reticle requalification

T. H. Yen; Rick Lai; Laurent C. Tuo; Vikram Tolani; Dongxue Chen; Peter Hu; Jiao Yu; George Hwa; Yan Zheng; Suresh Lakkapragada; Kechang Wang; Danping Peng; Bill Wang; Kaiming Chiang

doi:10.1117/12.2031786

20 September 2013 Automated Defect Classification (ADC) and Progression Monitoring (DPM) in wafer fab reticle requalification

T. H. Yen, Rick Lai, Laurent C. Tuo, Vikram Tolani, Dongxue Chen, Peter Hu, Jiao Yu, George Hwa, Yan Zheng, Suresh Lakkapragada, Kechang Wang, Danping Peng, Bill Wang, Kaiming Chiang

Author Affiliations +

Proceedings Volume 8880, Photomask Technology 2013; 88800A (2013) https://doi.org/10.1117/12.2031786
Event: SPIE Photomask Technology, 2013, Monterey, California, United States

Abstract

As optical lithography continues to extend into low-k1 regime, resolution of mask patterns continue to diminish, and so do mask defect requirements due to increasing MEEF. Post-inspection, mask defects have traditionally been classified by operators manually based on visual review. This approach may have worked down to 65/55nm node layers. However, starting 45nm and smaller nodes, visually reviewing 50 to sometimes 100s of defects on masks with complex modelbased OPC, SRAF, and ILT geometries, is error-prone and takes up valuable inspection tool capacity. Both these shortcomings in manual defect review are overcome by adoption of the computational solution called Automated Defect Classification (ADC) wherein mask defects are accurately classified within seconds and consistent to guidelines used by production technicians and engineers.

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T. H. Yen, Rick Lai, Laurent C. Tuo, Vikram Tolani, Dongxue Chen, Peter Hu, Jiao Yu, George Hwa, Yan Zheng, Suresh Lakkapragada, Kechang Wang, Danping Peng, Bill Wang, and Kaiming Chiang "Automated Defect Classification (ADC) and Progression Monitoring (DPM) in wafer fab reticle requalification", Proc. SPIE 8880, Photomask Technology 2013, 88800A (20 September 2013); https://doi.org/10.1117/12.2031786

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