Process Improvement in Feedback Adjustment

Lee, Jae-June;Kim, Yong-Hee

  • 투고 : 2012.02.10
  • 심사 : 2012.03.28
  • 발행 : 2012.05.31


Process adjustment, also called engineering process control(EPC), is applied to maintain process output close to a target value by manipulating controllable variables, but special causes may still make the process deviate from the target and result in significant costs. Thus, it is important to detect and mediate deviations as early as possible. We propose a one-step detection method, the moving search block(MSB), with which the time and type of a special cause can be identified in short periods. A modified control rule that can entertain the effects of the special cause is proposed. A numerical example is presented to evaluate the performance of the proposed scheme.


Responsive system;special causes;outliers;moving search block


  1. Atienza, O. O., Tang, L. C. and Ang, B. W. (1998). A SPC procedure for detecting level shifts of auto-correlated processes, Journal of Quality Technology, 30, 340-351.
  2. Box, G. E. P. and Luceno, A. (1997). Statistical Process Monitoring and Feedback Adjustment, John Wiley & Sons, New York.
  3. Chen, C. and Liu, L.-M. (1993). Forecasting time series with outliers, Journal of Forecasting, 13, 13-35.
  4. Hu, S. A. and Roan, C. (1996). Change patterns of time series based control charts, Journal of Quality Technology, 28, 302-312.
  5. Jiang, W. and Tsui, K.-L. (2002). SPC monitoring of MMSE- and PI- Controlled Processes, Journal of Quality Technology, 34, 384-398.
  6. Tsay, R. S. (1986). Time series model specification in the presence of outliers, Journal of American Statistical Association, 81, 131-141.
  7. Tsung, F. and Apley, D. W. (2002). The dynamic T2 chart for monitoring feedback-controlled processes, IIE Transactions, 34, 1043-1053.
  8. Tsung, F., Shi, J. and Wu, C. F. J. (1999). Joint monitoring of PID-controlled processes, Journal of Quality Technology, 31, 275-285.
  9. Tsung, F. and Tsui, K.-L. (2003). A mean-shift pattern study on integration of SPC and APC for process monitoring, IEE Transactions, 35, 231-242.
  10. Vander Wiel, S. A. (1996). Monitoring processes that wander using integrated moving average methods, Technometrics, 38, 139-151.
  11. Vander Wiel, S. A., Tucker, W. T., Faltin, F. W. and Doganaksoy, N. (1992). Algorithmic statistical process control: Concepts and application, Technometrics, 34, 286-297.
  12. Wardell, D. G., Moskowitz, H. and Plante, R. D. (1994). Run-length distributions of special cause control charts for correlated processes, Technometrics, 36, 3-17.
  13. Wright, C. M., Booth, D. E. and Hu, M. Y. (2001). Joint estimation: SPC method for short-run auto-correlated data, Journal of Quality Technology, 33, 365-378.


연구 과제 주관 기관 : Inha University