Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Gower distance-based multivariate control charts for a mixture of continuous and categorical variables

Authors
Tuerhong, GulanbaierKim, Seoung Bum
Issue Date
Mar-2014
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Keywords
Gower distance; Multivariate control charts; Mixture data; Quality control; Statistical process control
Citation
EXPERT SYSTEMS WITH APPLICATIONS, v.41, no.4, pp.1701 - 1707
Indexed
SCIE
SCOPUS
Journal Title
EXPERT SYSTEMS WITH APPLICATIONS
Volume
41
Number
4
Start Page
1701
End Page
1707
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/99108
DOI
10.1016/j.eswa.2013.08.068
ISSN
0957-4174
Abstract
Processes characterized by high dimensional and mixture data challenge traditional statistical process control charts. In this study, we propose a multivariate control chart based on the Gower distance that can handle a mixture of continuous and categorical data. An extensive simulation study was conducted to examine the properties of the proposed control chart under various scenarios and compared it with some existing multivariate control charts. The simulation results revealed that the proposed control chart outperformed the existing charts when the number of categorical variables increases. Furthermore, we demonstrated the applicability and effectiveness of the proposed control charts through a real case study. (C) 2013 Elsevier Ltd. All rights reserved.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher KIM, Seoung Bum photo

KIM, Seoung Bum
College of Engineering (School of Industrial and Management Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE