The use of cross-validation for overlay model selection

Sungwoo Jung; Clemens Utzny

doi:10.1117/12.2675560

5 October 2023 The use of cross-validation for overlay model selection

Sungwoo Jung, Clemens Utzny

Proceedings Volume 12802, 38th European Mask and Lithography Conference (EMLC 2023); 128020R (2023) https://doi.org/10.1117/12.2675560
Event: 38th European Mask and Lithography Conference, 2023, Dresden, Germany

Abstract

Overlay requirements are becoming more demanding as the semiconductor device design dimensions continue to reduce in size. Thus, it is increasingly crucial to control overlay under tightened specifications to maximize product yield. To meet these requirements, selecting the best overlay model is important to best manage the lithography process with confidence. A well-characterized overlay model is essential in the wafer production process as it becomes the gauge to optimize product yield, reduce rework process costs and shorten cycle time. In this paper, we will introduce the powerful machine-learning method of Cross-Validation (CV) which helps to improve the prediction capability of an overlay model. This method provides a numerical value that can indicate how well the overlay model predicts the misalignment of a new wafer. Our test result shows that the 5th-order model exhibits an overfitting problem, while the 4th-order model shows good performance. We also discuss how we apply the CV to the correction per exposure (CPE) models that are commonly used.

Citation Download Citation

Sungwoo Jung and Clemens Utzny "The use of cross-validation for overlay model selection", Proc. SPIE 12802, 38th European Mask and Lithography Conference (EMLC 2023), 128020R (5 October 2023); https://doi.org/10.1117/12.2675560

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