신경망을 이용한 반도체 공정 시뮬레이터

• 영문명: Neural network simulator for semiconductor manufacturing ; Case study - photolithography process overlay parameters
• 발행기관: 한국시뮬레이션학회
• 저자명: 박상훈(Sanghoon Park) 서상혁(Sanghyok Seo) 김지현(Jihyun Kim) 김성식(Sung-Shick Kim)
• 간행물 정보: 『한국시뮬레이션학회 논문지』제14권 제4호, 55~68쪽, 전체 14쪽
• 주제분류: 공학 > 기타공학
• 파일형태: PDF
• 발행일자: 2005.12.30

영문 초록

The advancement in semiconductor technology is leading toward smaller critical dimension designs and larger wafer manufactures. Due to such phenomena, semiconductor industry is in need of an accurate control of the process. Photolithography is one of the key processes where the pattern of each layer is formed. In this process, precise superposition of the current layer to the previous layer is critical. Therefore overlay parameters of the semiconductor photolithography process is targeted for this research. The complex relationship among the input parameters and the output metrologies is difficult to understand and harder yet to model. Because of the superiority in modeling multi-nonlinear relationships, neural networks is used for the simulator modeling. For training the neural networks, conjugate gradient method is employed. An experiment is performed to evaluate the performance among the proposed neural network simulator, stepwise regression model, and the currently practiced prediction model from the test site.

목차

1. 서론

2. 신경망 모델의 필요성 및 기존연구

3. 오버레이 공정

4. 신경망 모델링

5. 실험 및 심험결과

6. 결론

참고문헌

키워드

Neural networks modeling photolithography overlay