JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A Readjustment Procedure after Signalling in the Integrated Process Control
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Readjustment Procedure after Signalling in the Integrated Process Control
Park, Chang-Soon; Lee, Jae-Heon;
  PDF(new window)
 Abstract
This paper considers the integrated process control procedure for detecting special causes in an IMA(1,1) process that is being adjusted automatically after each observation using a minimum mean squared error adjustment policy. When the control chart signals after the occurrence of a special cause, the special cause will be detected and eliminated from the process by the rectifying action. However, when the elimination of the special cause costs high or is not practically possible, an alternative action is to readjust the process with appropriately modified adjustment scheme. In this paper, we propose the readjustment procedure after having a true signal, and show that the use of the readjustment can reduce the deviation of a process from the target.
 Keywords
Integrated process control;process adjustment;readjustment;rectifying action;
 Language
Korean
 Cited by
1.
통합공정관리에서 일반화가능도비 관리도의 설계,천가영;이재헌;

Communications for Statistical Applications and Methods, 2010. vol.17. 3, pp.357-365 crossref(new window)
2.
통합공정관리에서 출력변수와 입력변수를 탐지하는 절차의 비교,이재헌;

Journal of the Korean Data and Information Science Society, 2011. vol.22. 4, pp.679-690
3.
다변량 통합공정관리에서 재수정 절차,조교영;박종숙;

Journal of the Korean Data and Information Science Society, 2011. vol.22. 6, pp.1123-1135
1.
Parameter estimation in a readjustment procedure in the multivariate integrated process control, Journal of the Korean Data and Information Science Society, 2013, 24, 6, 1275  crossref(new windwow)
 References
1.
Box, G. E. P. and Kramer, T. (1992). Statistical process control and feedback adjustment - A discussion, Technometrics, 34, 251-285 crossref(new window)

2.
Del Castillo, E. (2002). Statistical Process Adjustment for Quality Control, John Wiley & Sons, New York

3.
Jiang, W. (2004). A joint monitoring scheme for automatically controlled processes, lIE Transactions, 36, 1201-1210 crossref(new window)

4.
Montgomery, D. C. (1999). A perspective on models and the quality sciences: Some challenges and future directions, ASQ Statistics Division Newsletter, 18, 8-13

5.
Nembhard, H. B. and Chen, S. (2007). Cuscore control charts for generalized feedback-control systems, Quality and Reliability Engineering International, 23, 483-502 crossref(new window)

6.
Pan, R. and Del Castillo, E. (2003). Integration of sequential process adjustment and process monitoring techniques, Quality and Reliability Engineering International, 19, 371-386 crossref(new window)

7.
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 crossref(new window)

8.
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 crossref(new window)

9.
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 crossref(new window)

10.
Runger, G., Testik, M. C. and Tsung, F. (2006), Relationships among control charts used with feedback control, Quality and Reliability Engineering International, 22, 877-887 crossref(new window)

11.
Vander Wiel, S. A. (1996). Monitoring processes that wander using integrated moving average models, Technometrics, 38, 139-151 crossref(new window)