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2 April 2014 Automatically high accurate and efficient photomask defects management solution for advanced lithography manufacture
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Defect review is a time consuming job. Human error makes result inconsistent. The defects located on don’t care area would not hurt the yield and no need to review them such as defects on dark area. However, critical area defects can impact yield dramatically and need more attention to review them such as defects on clear area. With decrease in integrated circuit dimensions, mask defects are always thousands detected during inspection even more. Traditional manual or simple classification approaches are unable to meet efficient and accuracy requirement. This paper focuses on automatic defect management and classification solution using image output of Lasertec inspection equipment and Anchor pattern centric image process technology. The number of mask defect found during an inspection is always in the range of thousands or even more. This system can handle large number defects with quick and accurate defect classification result. Our experiment includes Die to Die and Single Die modes. The classification accuracy can reach 87.4% and 93.3%. No critical or printable defects are missing in our test cases. The missing classification defects are 0.25% and 0.24% in Die to Die mode and Single Die mode. This kind of missing rate is encouraging and acceptable to apply on production line. The result can be output and reloaded back to inspection machine to have further review. This step helps users to validate some unsure defects with clear and magnification images when captured images can’t provide enough information to make judgment. This system effectively reduces expensive inline defect review time. As a fully inline automated defect management solution, the system could be compatible with current inspection approach and integrated with optical simulation even scoring function and guide wafer level defect inspection.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jun Zhu, Lijun Chen, Lantao Ma, Dejian Li, Wei Jiang, Lihong Pan, Huiting Shen, Hongmin Jia, Chingyun Hsiang, Guojie Cheng, Li Ling, Shijie Chen, Jun Wang, Wenkui Liao, and Gary Zhang "Automatically high accurate and efficient photomask defects management solution for advanced lithography manufacture", Proc. SPIE 9050, Metrology, Inspection, and Process Control for Microlithography XXVIII, 90501V (2 April 2014);

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