23 March 2009 Systematic defect filtering and data analysis methodology for design based metrology
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Abstract
Recently several Design Based Metrologies (DBMs) are introduced and being in use for wafer verification. The major applications of DBM are OPC accuracy improvement, DFM feed-back through Process Window Qualification (PWQ) and advanced process control. In general, however, the amount of output data from DBM is normally so large that it is very hard to handle the data for valuable feed-back. In case of PWQ, more than thousands of hot spots are detected on a single chip at the edge of process window. So, it takes much time and labor to review and analyze all the hot spots detected at PWQ. Design-related systematic defects, however, will be found repeatedly and if they can be classified into groups, it would be possible to save a lot of time for the analysis. We have demonstrated an EDA tool which can handle the large amount of output data from DBM by reducing pattern defects to groups. It can classify millions of patterns into less than thousands of pattern groups. It has been evaluated on the analysis of PWQ of metal layer in NAND Flash memory device and random contact hole patterns in a DRAM device. The result shows that this EDA tool can handle the CD measurement data easily and can save us a lot of time and labor for the analysis. The procedures of systematic defect filtering and data handling using an EDA tool are presented in detail
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Hyunjo Yang, Hyunjo Yang, Jungchan Kim, Jungchan Kim, Taehyeong Lee, Taehyeong Lee, Areum Jung, Areum Jung, Gyun Yoo, Gyun Yoo, Donggyu Yim, Donggyu Yim, Sungki Park, Sungki Park, Toshiaki Hasebe, Toshiaki Hasebe, Masahiro Yamamoto, Masahiro Yamamoto, Jun Cai, Jun Cai, } "Systematic defect filtering and data analysis methodology for design based metrology", Proc. SPIE 7272, Metrology, Inspection, and Process Control for Microlithography XXIII, 72721C (23 March 2009); doi: 10.1117/12.814373; https://doi.org/10.1117/12.814373
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