Effect of warning limits on the performance of the X chart under autocorrelation
by Sukhraj Singh; D.R. Prajapati
International Journal of Productivity and Quality Management (IJPQM), Vol. 13, No. 2, 2014

Abstract: X charts for variables are one of the outstanding charts of statistical quality control (SQC), used to detect larger shifts in the process mean. In actual practice, many processes are autocorrelated and if these charts are used, their performance is deteriorated. The performance of the chart is measured in terms of the average run length (ARL), which is the average number of samples before getting an out-of-control signal. The ARLs at various sets of parameters of the X chart are computed by simulation, using MATLAB. An attempt has been made to counter autocorrelation by designing the X chart using warning limits. Various optimal schemes are proposed for different levels of correlation (Φ). Moreover these optimal schemes of modified X chart are compared with Derman-Ross's (Derman and Ross, 1997) and Klein's (2000) schemes at various levels of correlation (Φ). It is concluded that the modified X scheme outperforms the Derman-Ross's (2 of 2) scheme.

Online publication date: Sat, 17-May-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Productivity and Quality Management (IJPQM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com