CD process control through machine learning

Clemens Utzny

doi:10.1117/12.2248903

20 October 2016 CD process control through machine learning

Clemens Utzny

Proceedings Volume 10032, 32nd European Mask and Lithography Conference; 100320R (2016) https://doi.org/10.1117/12.2248903
Event: 32nd European Mask and Lithography Conference, 2016, Dresden, Germany

Abstract

For the specific requirements of the 14nm and 20nm site applications a new CD map approach was developed at the AMTC. This approach relies on a well established machine learning technique called recursive partitioning. Recursive partitioning is a powerful technique which creates a decision tree by successively testing whether the quantity of interest can be explained by one of the supplied covariates. The test performed is generally a statistical test with a pre-supplied significance level. Once the test indicates significant association between the variable of interest and a covariate a split performed at a threshold value which minimizes the variation within the newly attained groups. This partitioning is recurred until either no significant association can be detected or the resulting sub group size falls below a pre-supplied level.

Citation Download Citation

Clemens Utzny "CD process control through machine learning ", Proc. SPIE 10032, 32nd European Mask and Lithography Conference, 100320R (20 October 2016); https://doi.org/10.1117/12.2248903

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