An application of multivariate T2 control chart for skewed distributed data

Author(s):  
Mahsa Sasaei
2012 ◽  
Vol 30 (1) ◽  
pp. 25-35 ◽  
Author(s):  
Moustafa Omar Ahmed Abu-Shawiesh ◽  
B. M. Golam Kibria ◽  
Florence George

2013 ◽  
Vol 64 (1) ◽  
pp. 179-189 ◽  
Author(s):  
Michael B.C. Khoo ◽  
Zhang Wu ◽  
Philippe Castagliola ◽  
H.C. Lee

2006 ◽  
Vol 47 (4) ◽  
pp. 569-593 ◽  
Author(s):  
Alireza Faraz ◽  
Ahmad Parsian

2019 ◽  
Vol 16 (Special Issue) ◽  
Author(s):  
Mahmood Shahrabi ◽  
Amirhossein Amiri ◽  
Hamidreza Saligheh Rad ◽  
Sedigheh Ghofrani

2021 ◽  
Vol 336 ◽  
pp. 09021
Author(s):  
Kunyun Wang ◽  
Qianqian Li ◽  
Guangdong Li

Hotelling T2 control chart not only reflects the correla-tions between different quality characteristics but also has good efficiency on monitoring multivariate quality characteristics in production process. A new alternative control chart was constructed after the original products data are processed by using multivariate exponentially weighted moving average for cumulating failure effects because T2 control chart is ineffective on detecting minimal mean deviations. Exemplified by bivariate quality characteristics, we compared the monitoring effects of Hotelling T2 control chart and new control chart which is called as T2MEWMA control chart. Paper showed the improved T2MEWMA control chart has smaller average run length than Hotelling T2 control chart on monitoring minimal mean deviation and that also studied the relationships between T2MEWMA control chart’s forgetting factor, sample sizes N and type II error. It indicated the smaller forgetting factor is more sensitive to minimal mean value deviation and that average run length tended to become bigger gradually along with increase of sample sizes N when production process is out of control.


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