Presentation Information
[8p-P11-8]Optimization of Semiconductor Drying Process Using AI-Driven Process Evaluation Metrics
〇Yusuke Kubo1, Yuui Nakano1, Hiromori Murashima1, Shogo Kunieda1, Yuta Sasaki1, Yosuke Hanawa1 (1.SCREEN Holdings Co., Ltd.)
Keywords:
semiconductor,process informatics,machine learning
Conventional semiconductor drying process development has evaluated the quality of the process by measuring the collapse rate using scanning electron microscope (SEM) images. However, collapse evaluation using SEM images is time-consuming and costly. Therefore, we developed an AI that estimates the collapse rate from moiré patterns in optical microscope images, which can be acquired in a short time. process optimization using the collapse rate estimated by the AI has succeeded in optimizing the drying process conditions in about 68% less time than before.