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Multivariate control charts that combine the Hotelling T-2 and classification algorithms

Authors
Park, Sung HoKim, 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.
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