4 April 2018 Litho friendly via insertion with in-design auto-fix flow using machine learning
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Abstract
Via failure has always been a significant yield detractor caused by random and systematic defects. Introducing redundant vias or via bars into the design can alleviate the problem significantly [1] and has, therefore, become a standard DFM procedure [2]. Applying rule-based via bar insertion to convert millions of via squares to via bar rectangles, in all possible places where enough room could be predicted, is an efficient methodology to maximize the redundancy rate. However, inserting via bars can result in lithography hotspots. A Pattern Manufacturability (PATMAN) model is proposed, to maximize the Redundant Via Insertion (RVI) rate in a reasonable runtime, while insuring lithography friendly insertion based on the accumulated DFM learnings during the yield ramp.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ahmed Mounir Elsemary, Ahmed Mounir Elsemary, Moutaz Fakhry, Moutaz Fakhry, Janam Bakshi, Janam Bakshi, Nishant Shah, Nishant Shah, Mohamed Ismail, Mohamed Ismail, Fadi Batarseh, Fadi Batarseh, Uwe Paul Schroeder, Uwe Paul Schroeder, Ahmed Mohyeldin, Ahmed Mohyeldin, Jason Cain, Jason Cain, } "Litho friendly via insertion with in-design auto-fix flow using machine learning", Proc. SPIE 10588, Design-Process-Technology Co-optimization for Manufacturability XII, 105880F (4 April 2018); doi: 10.1117/12.2297499; https://doi.org/10.1117/12.2297499
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