Systems and methods for predicting defects and critical dimension using deep learning in the semiconductor manufacturing process
US11275361B2 · kind B2 · utility
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Key dates
| Filing date | Nov 16, 2017 |
| Grant date | Mar 15, 2022 |
| Priority date | — |
| Expiry date | Nov 20, 2040 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02P90/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An initial inspection or critical dimension measurement can be made at various sites on a wafer. The location, design clips, process tool parameters, or other parameters can be used to train a deep learning model. The deep learning model can be validated and these results can be used to retrain the deep learning model. This process can be repeated until the predictions meet a detection accuracy threshold. The deep learning model can be used to predict new probable defect location or critical dimension failure sites.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.