TY - JOUR
T1 - Gower distance-based multivariate control charts for a mixture of continuous and categorical variables
AU - Tuerhong, Gulanbaier
AU - Kim, Seoung Bum
N1 - Funding Information:
The authors thank the editor and the referees, whose comments helped improving the presentation of this paper. This research was supported by Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT and Future Planning (2013007724) and the Ministry of Knowledge Economy in Korea under the IT R&D Infrastructure Program supervised by the NIPA (National IT Industry Promotion Agency) (NIPA-2011-(B1110-1101-0002)).
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - Gower distance
KW - Mixture data
KW - Multivariate control charts
KW - Quality control
KW - Statistical process control
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U2 - 10.1016/j.eswa.2013.08.068
DO - 10.1016/j.eswa.2013.08.068
M3 - Article
AN - SCOPUS:84888379498
SN - 0957-4174
VL - 41
SP - 1701
EP - 1707
JO - Expert Systems with Applications
JF - Expert Systems with Applications
IS - 4 PART 2
ER -