High dimensional quality control chart: A case study of “Baju Kurung” manufacturing industry

There is a need for quality control chart that can cater for high dimension data set (n < p) in a real world application due to either limited number of productions (n) but high number of measurements of a product (p) or to minimize the cost for products quality testing. Therefore, monitoring th...

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Bibliographic Details
Main Authors: Sharif, Shamshuritawati, Ismail, Suzilah, Omar, Zurni
Format: Article
Language:English
Published: Research India Publications 2017
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Online Access:http://repo.uum.edu.my/27956/1/IJAER%2012%2016%202017%205491%205494.pdf
http://repo.uum.edu.my/27956/
https://www.ripublication.com/Volume/ijaerv12n16.htm
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Summary:There is a need for quality control chart that can cater for high dimension data set (n < p) in a real world application due to either limited number of productions (n) but high number of measurements of a product (p) or to minimize the cost for products quality testing. Therefore, monitoring the quality process control in the case of dimension (p) is large relative to the number of sample (n) is a crucial part in statistical process control study. In this paper we propose S* control chart to do such analysis in multivariate process variability monitoring for “baju kurung” manufacturing industry in Malaysia. A case study where p=7 and n=5 is presented via control chart to illustrate the advantage of the proposed method. The findings reveal that the high dimensional quality control chart can assist in differentiating between in-control and out-of-control signals easily via multivariate statistical process control chart.