EconPapers    
Economics at your fingertips  
 

Improving the Performance of the Chi-square Control Chart via Runs Rules

Markos V. Koutras (), Sotirios Bersimis () and Demetrios L. Antzoulakos ()
Additional contact information
Markos V. Koutras: University of Piraeus
Sotirios Bersimis: University of Piraeus
Demetrios L. Antzoulakos: University of Piraeus

Methodology and Computing in Applied Probability, 2006, vol. 8, issue 3, 409-426

Abstract: Abstract The most popular multivariate process monitoring and control procedure used in the industry is the chi-square control chart. As with most Shewhart-type control charts, the major disadvantage of the chi-square control chart, is that it only uses the information contained in the most recently inspected sample; as a consequence, it is not very efficient in detecting gradual or small shifts in the process mean vector. During the last decades, the performance improvement of the chi-square control chart has attracted continuous research interest. In this paper we introduce a simple modification of the chi-square control chart which makes use of the notion of runs to improve the sensitivity of the chart in the case of small and moderate process mean vector shifts.

Keywords: Multivariate statistical quality control; Chi-square control chart; Average run length; Runs rules; 62N10 (search for similar items in EconPapers)
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://link.springer.com/10.1007/s11009-006-9754-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:metcap:v:8:y:2006:i:3:d:10.1007_s11009-006-9754-z

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1007/s11009-006-9754-z

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:metcap:v:8:y:2006:i:3:d:10.1007_s11009-006-9754-z