Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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Deep Learning Based TSV Hole TCD Measurement

딥러닝 기반의 TSV Hole TCD 계측 방법

  • 정준희 (인천대학교 임베디드시스템공학과) ;
  • 구창모 ((주)넥스틴) ;
  • 조중휘 (인천대학교 임베디드시스템공학과)
  • Received : 2021.06.10
  • Accepted : 2021.06.22
  • Published : 2021.06.30
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Abstract

The TCD is used as one of the indicators for determining whether TSV Hole is defective. If the TCD is not normal size, it can lead to contamination of the CMP equipment or failure to connect the upper and lower chips. We propose a deep learning model for measuring the TCD. To verify the performance of the proposed model, we compared the prediction results of the proposed model for 2461 via holes with the CD-SEM measurement data and the prediction results of the existing model. Although the number of trainable parameters in the proposed model was about one two-thousandth of the existing model, the results were comparable. The experiment showed that the correlation between CD-SEM and the prediction results of the proposed model measured 98%, the mean absolute difference was 0.051um, the standard deviation of the absolute difference was 0.045um, and the maximum absolute difference was 0.299um on average.

Keywords

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