Comparison of monitoring the output variable and the input variable in the integrated process control

통합공정관리에서 출력변수와 입력변수를 탐지하는 절차의 비교

  • Lee, Jae-Heon (Department of Applied Statistics, Chung-Ang University)
  • 이재헌 (중앙대학교 응용통계학과)
  • Received : 2011.05.23
  • Accepted : 2011.06.23
  • Published : 2011.08.01

Abstract

Two widely used approaches for improving the quality of the output of a process are statistical process control (SPC) and automatic process control (APC). In recent hybrid processes that combine aspects of the process and parts industries, process variations due to both the inherent wandering and special causes occur commonly, and thus simultaneous application of APC and SPC schemes is needed to effectively keep such processes close to target. The simultaneous implementation of APC and SPC schemes is called integrated process control (IPC). In the IPC procedure, the output variables are monitored during the process where adjustments are repeatedly done by its controller. For monitoring the APC-controlled process, control charts can be generally applied to the output variable. However, as an alternative, some authors suggested that monitoring the input variable may improve the chance of detection. In this paper, we evaluate the performance of several monitoring statistics, such as the output variable, the input variable, and the difference variable, for efficiently monitoring the APC-controlled process when we assume IMA(1,1) noise model with a minimum mean squared error adjustment policy.

Acknowledgement

Supported by : 한국연구재단

References

  1. Box, G. E. P., Jenkins, G. M. and Reinsel, G. C. (1994). Time series analysis, forecasting and control, 3rd Ed., Prentice Hall, Englewood Cliffs, New Jersey.
  2. Box, G. E. P. and Kramer, T. (1992). Statistical process control and feedback adjustment - A discussion. Technometrics, 34, 251-285. https://doi.org/10.2307/1270028
  3. Hu, S. J. and Roan, C. (1996). Change patterns of time series-based control charts. Journal of Quality Technology, 28, 302-312.
  4. Jiang, W. (2004). A joint monitoring scheme for automatically controlled processes. IIE Transactions, 36, 1201-1210. https://doi.org/10.1080/07408170490507828
  5. Jiang, W. and Tsui, K.-L. (2002). SPC monitoring of MMSE- and PI-controlled processes. Journal of Quality Technology, 34, 384-398.
  6. Lee, J. and Kim, M. (2010). Procedure for monitoring special causes and readjustment in ARMA(1,1) noise model. Journal of the Korean Data & Information Science Society, 21, 841-852.
  7. Nembhard, H. B. and Chen, S. (2007). Cuscore control charts for generalized feedback-control systems. Quality and Reliability Engineering International, 23, 483-502. https://doi.org/10.1002/qre.831
  8. Pan, R. and Del Castillo, E. (2003). Integration of sequential process adjustment and process monitoring techniques. Quality and Reliability Engineering International, 19, 371-386. https://doi.org/10.1002/qre.590
  9. Park, C. (2007). An algorithm for the properties of the integrated process control with bounded adjustments and EWMA monitoring. International Journal of Production Research, 45, 5571-5587. https://doi.org/10.1080/00207540701325397
  10. Park, C. and Lee, J. (2008). An integrated process control scheme based on the future loss. The Korean Journal of Applied Statistics, 21, 247-264. https://doi.org/10.5351/KJAS.2008.21.2.247
  11. Park, C. and Lee, J. (2009). A readjustment procedure after signalling in the integrated process control. Communications of the Korean Statistics Society, 16, 429-436. https://doi.org/10.5351/CKSS.2009.16.3.429
  12. Park, C. and Reynolds, M., Jr. (2008). Economic design of an integrated process control procedure with repeated adjustments and EWMA monitoring. Journal of the Korean Statistical Society, 37, 155-174. https://doi.org/10.1016/j.jkss.2007.10.005
  13. Reynolds, M., Jr. and Park, C. (2010). CUSUM charts for detecting special causes in integrated process control. Quality and Reliability Engineering International, 26, 199-221. https://doi.org/10.1002/qre.1045
  14. Runger, G., Testik, M. C. and Tsung, F. (2006). Relationships among ontrol charts used with feedback control. Quality and Reliability Engineering International, 22, 877-887. https://doi.org/10.1002/qre.774
  15. Tsung, F. and Tsui, K.-L. (2003). A mean-shift pattern study on integration of SPC and APC for process monitoring. IIE Transactions, 35, 231-242. https://doi.org/10.1080/07408170304365
  16. Vander Wiel, S. A. (1996). Monitoring processes that wander using integrated moving average models. Technometrics, 38, 139-151.