지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
이용수
초록· 키워드
오류제보하기
The purpose of virtual metrology (VM) in semiconductor manufacturing is to predict every wafer’s metrological values based on its process equipment data without an actual metrology. In this paper, we propose novelty detection-based reliability estimation models for VM in order to support flexible utilization of VM results.
Because the proposed model can not only estimate the reliability of VM, but also identify suspicious process variables lowering the reliability, quality control actions can be taken selectively based on the reliance level and its causes. Based on the preliminary experimental results with actual semiconductor manufacturing process data, our models can successfully give a high reliance level to the wafers with small prediction errors and a low reliance level to the wafers with large prediction errors. In addition, our proposed model can give more detailed information by identifying the critical process variables and their relative impacts on the low reliability.
Because the proposed model can not only estimate the reliability of VM, but also identify suspicious process variables lowering the reliability, quality control actions can be taken selectively based on the reliance level and its causes. Based on the preliminary experimental results with actual semiconductor manufacturing process data, our models can successfully give a high reliance level to the wafers with small prediction errors and a low reliance level to the wafers with large prediction errors. In addition, our proposed model can give more detailed information by identifying the critical process variables and their relative impacts on the low reliability.
목차
1. 서론
2. 이상치 탐지 기반 가상 계측 결과 신뢰도 및 설비변수 영향력 추정
3. 실험 설계
4. 실험 결과
5. 결론 및 향후 연구 방향
참고문헌
참고문헌 (21)
참고문헌 신청
Akaike, H. / 1974 / A New Look at the Statistical Model Identification / IEEE Transactions on Automatic Control 19(6):716~723
Barnett, V. / 1994 / Outliers in Statistical Data / Wiley and Sons
Bergeret, F. / 2003 / Yield Improvement Using Statistical Analysis of Process Data / IEEE Transactions on Semiconductor Manufacturing 16(3):535~542
Besnard, J. / 2006 / Wafer-to-Wafer Virtual Metrology Applied to Run-to-Run Control / Proc. of the Third ISMI Symposium on Manufacturing Effectiveness
Chang, Y. -J. / 2006 / Virtual Metrology Technique for Semiconductor Manufacturing / Proc. Int. Joint Conf. on Neural Network(IJCNN 2006) :5289~5293
Barnett, V. / 1994 / Outliers in Statistical Data / Wiley and Sons
Bergeret, F. / 2003 / Yield Improvement Using Statistical Analysis of Process Data / IEEE Transactions on Semiconductor Manufacturing 16(3):535~542
Besnard, J. / 2006 / Wafer-to-Wafer Virtual Metrology Applied to Run-to-Run Control / Proc. of the Third ISMI Symposium on Manufacturing Effectiveness
Chang, Y. -J. / 2006 / Virtual Metrology Technique for Semiconductor Manufacturing / Proc. Int. Joint Conf. on Neural Network(IJCNN 2006) :5289~5293
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UCI(KEPA) : I410-ECN-0101-2013-530-003629325