Multivariate control charts that combine the Hotelling T-2 and classification algorithms
- Authors
- Park, Sung Ho; Kim, Seoung Bum
- Issue Date
- 3-6월-2019
- Publisher
- TAYLOR & FRANCIS LTD
- Keywords
- Quality; control; statistical process control; multivariate control chart; classification algorithm
- Citation
- JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, v.70, no.6, pp.889 - 897
- Indexed
- SCIE
SSCI
SCOPUS
- Journal Title
- JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
- Volume
- 70
- Number
- 6
- Start Page
- 889
- End Page
- 897
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/64805
- DOI
- 10.1080/01605682.2018.1468859
- ISSN
- 0160-5682
- Abstract
- Multivariate control charts, including Hotelling's T-2 chart, have been widely adopted for the multivariate processes found in many modern systems. However, traditional multivariate control charts assume that the in-control group is the only population that can be used to determine a decision boundary. However, this assumption has restricted the development of more efficient control chart techniques that can capitalise on available out-of-control information. In the present study, we propose a control chart that improves the sensitivity (i.e., detection accuracy) of a Hotelling's T-2 control chart by combining it with classification algorithms, while maintaining low false alarm rates. To the best of our knowledge, this is the first attempt to combine classification algorithms and control charts. Simulations and real case studies demonstrate the effectiveness and applicability of the proposed control chart.
- 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](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholar.korea.ac.kr/handle/2021.sw.korea/64805)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.