Defective Wafer Detection Using Sensed Numerical Features

Kotcharat Kitchat, Ching Yu Lin, Min Te Sun

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

One of the fundamental processes in semiconductor manufacturing is slicing, which means cutting an ingot into many wafers. During the slicing process, it is possible to produce defective wafers. Unfortunately, the inspection to identify defective wafers is time-consuming and difficult. To solve this problem, we build a system, which uses sensors to collect features (e.g., temperature, thickness, pattern on wafer surface, etc.) during the slicing process to detect if the wafers are defective in the manufacturing process. Two different models, the GRU neural network and XGBoost, are implemented in the proposed system. After fine-Tuning both models, experimental results based on real dataset indicate that the GRU neural network outperforms XGBoost for wafer defective detection in both the prediction accuracy and model training time.

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主出版物標題2021 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2021
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781665431569
DOIs
出版狀態已出版 - 23 8月 2021
事件2021 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2021 - Virtual, Barcelona, Spain
持續時間: 23 8月 202126 8月 2021

出版系列

名字2021 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2021

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???event.eventtypes.event.conference???2021 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2021
國家/地區Spain
城市Virtual, Barcelona
期間23/08/2126/08/21

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