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

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41
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46

초록

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.

키워드

Gower distance; Multivariate control charts; Mixture data; Quality control; Statistical process control; STATISTICAL PROCESS-CONTROL; NEAREST NEIGHBOR RULE; EWMA CONTROL CHART; FAULT-DETECTION; MANUFACTURING PROCESSES; ARTIFICIAL CONTRASTS; SIGNALS; MODEL
제목
Gower distance-based multivariate control charts for a mixture of continuous and categorical variables
저자
Tuerhong, Gulanbaier; Kim, Seoung Bum
DOI
10.1016/j.eswa.2013.08.068
발행일
2014-03
유형
Article
저널명
Expert Systems with Applications
권
41
호
4
페이지
1701 ~ 1707