Control Charts for Controlling Variability of Non-Normal Processes

Das Nandini ()
Additional contact information
Das Nandini: SQC & OR Unit, Indian Statistical Institute, 203 B T Road, Kolkata 700108, India.

Stochastics and Quality Control, 2011, vol. 26, issue 2, 121-131

Abstract: Control charts represent a very effective tool used for reducing process variability by early detection of the occurrence of assignable causes of variation. -charts are applied to detect changes in process mean whereas S-charts are used to detect the same in process variability. Both charts are generally based on the normality assumption. The S-chart utilizes an unbiased estimator of the population standard deviation . However, it is highly affected by any violation of the normality assumption. In this paper, we propose some alternatives of S-charts based on some robust estimate of scale parameters. We will also illustrate the performance of the proposed control chart.

Keywords: Robust Estimator; Scale Parameter; Sn Statistics; Qn Statistics; ARL (search for similar items in EconPapers)
Date: 2011
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/EQC.2011.012 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:ecqcon:v:26:y:2011:i:2:p:121-131:n:4

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/eqc/html

DOI: 10.1515/EQC.2011.012

Access Statistics for this article

Stochastics and Quality Control is currently edited by George P. Yanev

More articles in Stochastics and Quality Control from De Gruyter
Bibliographic data for series maintained by Peter Golla ().