INFLUENCE OF SPECIAL CAUSES ON STOCHASTIC PROCESS ADJUSTMENT

  • Lee, Jae-June (Department of Statistics, Inha University) ;
  • Mihye Ahn (Department of Statistics, Inha University)
  • 발행 : 2004.06.01

초록

Process adjustment is a complimentary tool to process monitoring in process control. Although original intention of process adjustment is not identifying a special cause, detection and elimination of special causes may lead to significant process improvement. In this paper, we examine the impact of special causes on process adjustment. The bias in the adjusted output process is derived for each type of special causes, and average run length (ARL) of the Shewhart chart applied to the adjusted output is computed for each special cause types. Numerical results are illustrated for the ARL of the Shewhart chart, thereupon seriousness of special causes on process adjustment is evaluated for each type of special causes.

키워드

참고문헌

  1. Journal of Business and Economic Statistics v.6 Time-series modeling for statistical process control ALWAN,L.C.;ROBERTS,H.V. https://doi.org/10.2307/1391421
  2. Journal of Quality Technology v.30 A SPC procedure for detecting level shifts of autoorrelated processes ATIENZA,O.O.;TANG,L..;ANG,B.W.
  3. Statistical Control by Monitoring and Feedback Adjustment BOX,G.E.P.;LUCENO,A.
  4. Time Series Analysis : Forecasting and Control(3rd ed.) BOX,G.E.P.;JENKINS,G.M.;REINSEL,G.C.
  5. Technometrics v.34 Statistical process monitoring and feedback adjustment-a discussion BOX,G.E.P.'KRAMER,T. https://doi.org/10.2307/1270028
  6. Technometrics v.41 Integration of statistical and engineering process control in a continuous polymerization process CAPILLA,C.;FERRER,A.;ROMERO,R.;HUALDA,A. https://doi.org/10.2307/1270991
  7. Journal of Forecasting v.12 Forcasting time series with outlier CHAN,C.;LIU,L.M. https://doi.org/10.1002/for.3980120103
  8. Technometrics v.44 Design and performance analysis of the exponentially weighted moving average mean estimate for processes subject to random step changes CHEN,A.;ELSAYED,E.A. https://doi.org/10.1198/004017002188618572
  9. Technometrics v.29 A simple method for studying run-length distributions of exponentially weighted moving average charts CROWDER,S.V. https://doi.org/10.2307/1269450
  10. Journal of Quality Technology v.21 Design of exponentially weighted moving average schemes CROWDER,S.V.
  11. Technometrics v.44 Closed-loop disturbance identification and controller tuning for discrete manufacturing processes DEL CASTILLO,E. https://doi.org/10.1198/004017002317375082
  12. Technometrics v.32 Exponentially weighted moving average control schemes : Properties and enhancements LUCAS,J.M.;SACCUCCI,M.S. https://doi.org/10.2307/1269835
  13. American Institute of Chemical Engineers, Cast Newsletter Interface between process control and on-line statistical process control MACGREGOR,J.F.
  14. Technometrics v.32 Discussion of 'EWMA control schemes : Properties and enhancement' by Lucas and Saccuci MACGREGOR,J.F.;HARRIS,T.J. https://doi.org/10.2307/1269840
  15. Introduction to Statistical Quality Control(4th ed.) MONTGOMERY,D.C.
  16. Journal of Quality Technology v.26 Integrating statistical process control and engineering process control MONTGOMERY,D.C.;KEATS,J.B.;RUNGER,G.C.;MESSINA,W.S.
  17. Forecasting with Dynamic Regression Models PANKRATZ,A.
  18. Journal of the American Statistical Association v.81 Time series model specification in the presence of outliers TSAY,R.S. https://doi.org/10.2307/2287980
  19. Journal of Forecasting v.7 Outliers, level shifts, and variance changes in time series TSAY,R.S. https://doi.org/10.1002/for.3980070102
  20. Technometrics v.38 Monitoring processes that wandor using integrated moving average models VANDER,WIEI,S. https://doi.org/10.2307/1270407
  21. Technometrics v.34 Algorithmic statistical process control : Concepts and an application VANDER WIEI,S.;TUCKER,W.T.;FALTIN,F.W.;DOGANAKSOY,N. https://doi.org/10.2307/1270035
  22. Technometrics v.36 Run-length distributions of special-cause control charts for correlated processes WARDEL,D.G.;MOSKOWITZ,H.;PLANTE,R.D. https://doi.org/10.2307/1269191
  23. Quality Engineering v.5 The statistical of CUSUM charts WOODALL,W.H.;ADAMS,B.M. https://doi.org/10.1080/08982119308918998