16 March 2016 Pattern-based DTCO flow for early estimation of lithographic difficulty using optical image processing
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Abstract
In this paper, we introduce a fast and reasonably accurate methodology to determine patterning difficulty based on the fundamentals of optical image processing techniques to analyze the frequency content of design shapes which determines patterning difficulties via a computational patterning transfer function. In addition, with the help of Monte- Carlo random pattern generator, we use this flow to identify a set of difficult patterns that can be used to evaluate the design ease-of-manufacturability via a scoring methodology as well as to help with the optimization phases of post-tape out flows. This flow offers the combined merits of scoring-based criteria and model-based approach for early designs. The value of this approach is that it provides designers with early prediction of potential problems even before the rigorous model-based DFM kits are developed. Moreover, the flow establishes a bi-directional platform for interaction between the design and the manufacturing communities based on geometrical patterns.
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Moutaz Fakhry, Kareem Madkour, Wael ElManhawy, Jason Cain, Joe Kwan, "Pattern-based DTCO flow for early estimation of lithographic difficulty using optical image processing", Proc. SPIE 9781, Design-Process-Technology Co-optimization for Manufacturability X, 97810I (16 March 2016); doi: 10.1117/12.2219506; https://doi.org/10.1117/12.2219506
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