Exposure process optimization using machine learning overlay prediction

Masahiro Yoshida; W. H. Wang; C. H. Huang; Elvis Yang; T. H. Yang; K. C. Chen; Yosuke Takarada; Yoshiki Sakamoto; Shin-ichi Egashira; Ken Otani; Tsukasa Saito; Shoshi Katayama; Seiya Miura; Douglas Shelton

doi:10.1117/12.2611020

26 May 2022 Exposure process optimization using machine learning overlay prediction

Masahiro Yoshida, W. H. Wang, C. H. Huang, Elvis Yang, T. H. Yang, K. C. Chen, Yosuke Takarada, Yoshiki Sakamoto, Shin-ichi Egashira, Ken Otani, Tsukasa Saito, Shoshi Katayama, Seiya Miura, Douglas Shelton

Author Affiliations +

Proceedings Volume 12053, Metrology, Inspection, and Process Control XXXVI; 120531L (2022) https://doi.org/10.1117/12.2611020
Event: SPIE Advanced Lithography + Patterning, 2022, San Jose, California, United States

Conference Poster

Abstract

As a part of the semiconductor manufacturing process, an overlay measurement instrument is used to inspect overlay accuracy after exposure. The overlay measurement results are not only used to evaluate accuracy, but also to optimize exposure processing by calculating various offsets based on the measurement results and feeding them back to the exposure system. Increasing the number of overlay measurement points can help identify and compensate for local distortions including EPE (edge placement errors). However, it is not practical to perform overlay measurement for all wafers and all regions, therefore the better strategy for is performing correction through combining predicted results with actual measurement results. Canon is working with Macronix to develop the VMOM (Virtual Machine Overlay Metrology) system for predicting overlay measurement results. The VMOM method uses machine learning to study large amounts of data to derive the relationship between overlay error results and exposure system process variables that cause overlay error. A VMOM model was developed using 3D-NAND process data and overlay prediction accuracy and exposure process optimization were evaluated. This paper reports the development status of the VMOM system and the practical effects of the system.

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Masahiro Yoshida, W. H. Wang, C. H. Huang, Elvis Yang, T. H. Yang, K. C. Chen, Yosuke Takarada, Yoshiki Sakamoto, Shin-ichi Egashira, Ken Otani, Tsukasa Saito, Shoshi Katayama, Seiya Miura, and Douglas Shelton "Exposure process optimization using machine learning overlay prediction", Proc. SPIE 12053, Metrology, Inspection, and Process Control XXXVI, 120531L (26 May 2022); https://doi.org/10.1117/12.2611020

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