검출력 향상된 자기상관 공정용 관리도의 강건 설계 : 반도체 공정설비 센서데이터 응용
Power Enhanced Design of Robust Control Charts for Autocorrelated Processes : Application on Sensor Data in Semiconductor Manufacturing
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
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.
Abstract
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.
참고문헌 (25)
- 김윤배, "분계점 붓스트랩 방법을 이용한 자기상관을 갖는 공정의 X 관리도", 품질경영학회지, 28(2), pp.39~56 (2000)
- 이재준, "자기상관 공정에 대한 누적합관리도에서 설계모수 값의 결정", 품질경영학회지, 36(4), pp.87~92 (2008), 한국품질경영학회
- 이정형, "자기상관을 갖는 공정의 로버스트 누적합관리도", 품질경영학회지, 27(4), pp.123~142 (1999)
- Alwan,L.C, "Time-Series Modeling for Statistical Process Control", Journal of Business and Economic Statistics, 6(1), pp.87~95 (1988)
- Apley,D.W, "Time Series Control Charts in the Presence of Model Uncertainty", Journal of Manufacturing Science and Engineering, 124(4), pp.891~898 (2002)
- 이현철, "Design of exponentially weighted moving average control charts for autocorrelated processes with model uncertainty", TECHNOMETRICS, 45(3), pp.187~198, AMER STATISTICAL ASSOC
- 이현철, "Robustness comparison of exponentially weighted moving-average charts on autocorrelated data and on residuals", JOURNAL OF QUALITY TECHNOLOGY, 40(4), pp.428~447, AMER SOC QUALITY CONTROL-ASQC
- 이현철, "The Effects of Model Parameter Deviations on the Variance of a Linearly Filtered Time Series", NAVAL RESEARCH LOGISTICS, 57(5), pp.460~471, JOHN WILEY SONS INC
- Box,G, "Time Series Analysis, Forecasting and Control, 4th Edition" (2008), John Wiley and Sons, Inc.
- English,J.R, "Detecting changes in autoregressive processes with X and EWMA charts", IIE Transactions, 32(12), pp.1103~1113 (2000)
- Johnson,R.A, "The Effect of Serial Correlation on the Performance of CUSUM tests", Technometrics, 16(1), pp.103~112 (1974)
- Lee,H.C, "Robust Design of Control Charts for Autocorrelated Processes with Model Uncertainty", 박사, pp.2004
- Lee,H.C, "Improved Design of Robust Exponentially Weighted Moving Average Control Charts for Autocorrelated Processes", QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 27(3), pp.337~352 (2011), WILEY-BLACKWELL
- Lin,W.S, "Combined Control Charts for Forecast-Based Monitoring Schemes", Journal of Quality Technology, 28(3), pp.289~301 (1996)
- Lu,C.W, "EWMA Control Charts for Monitoring the Mean of Autocorrelated Processes", Journal of Quality Technology, 31(2), pp.166~188 (1999)
- Lucas,J.M, "Exponentially Weighted Moving Average Control Schemes:Properties and Enhancements", Technometrics, 32(1), pp.1~12 (1990)
- Montgomery,D.C, "Some Statistical Process Control Methods for Autocorrelated Data", Journal of Quality Technology, 23(3), pp.179~193 (1991)
- Runger G.C, "Average Run Lengths for Cusum Control Charts Applied to Residuals", Communications in Statistics:Theory and Methods, 24(1), pp.273~282 (1995)
- Schmid,W, "On EWMA Charts for Time Series", Frontiers of Statistical Quality Control, 5, pp.115~137 (1997)
- Superville,C.R, "An Evaluation of Forecast-Based Quality Control Schemes", Communications in Statistics:Simulation and Computation, 23(3), pp.645~661 (1994)
- Testik,M.C, "Model Inadequacy and Residuals Control Charts for Autocorrelated Processes", Quality and Reliability Engineering International, 21(2), pp.115~130 (2005)
- Vander Weil,S.A, "Monitoring Processes That Wander Using Integrated Moving Average Models", Technometrics, 38(2), pp.139~151 (1996)
- Vasilopoulos,A.V, "Modification of Control Chart Limits in the Presence of Data Correlation", Journal of Quality Technology, 10(1), pp.20~30 (1978)
- Wardell,D.G, "Run-Length Distributions of Special-Cause Control Charts for Correlated Processes", Technometrics, 36(1), pp.3~17 (1994)
- Zhang,N.F, "A Statistical Control Chart for Stationary Process Data", Technometrics, 40(1), pp.24~38 (1998)