검출력 향상된 자기상관 공정용 관리도의 강건 설계

• 영문명: Power Enhanced Design of Robust Control Charts for Autocorrelated Processes : Application on Sensor Data in Semiconductor Manufacturing
• 발행기관: 한국산업경영시스템학회
• 저자명: 이현철(Hyun Cheol Lee)
• 간행물 정보: 『산업경영시스템학회지』제34권 제4호, 57~65쪽, 전체 9쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2011.12.31

영문 초록

Monitoring autocorrelated processes is prevalent in recent manufacturing environments. As a proactive control for manufacturing processes is emphasized especially in the semiconductor industry, it is natural to monitor real-time status of equipment through sensor rather than resultant output status of the processes. Equipment’s sensor data show various forms of correlation features. Among them, considerable amount of sensor data, statistically autocorrelated, is well represented by Box-Jenkins autoregressive moving average (ARMA) model. In this paper, we present a design method of statistical process control (SPC) used for monitoring processes represented by the ARMA model. The proposed method shows benefits in the power of detecting process changes, and considers robustness to ARMA modeling errors simultaneously. We prove benefits through Monte carlo simulation-based investigations.

목차

1. 서론

2. 선행 연구

3. 제안된 관리도 구조

4. 저차수 ARMA 모델 적용결과

5. 적용예제 및 성능비교

6. 결론

참고문헌

키워드

Statistical Process Control Power Semiconductor Manufacture Autoregressive Moving Average