Optimal design of the variable sampling size and sampling interval variable dimension T2 control chart for monitoring the mean vector of a multivariate normal process

2017 ◽  
Vol 47 (2) ◽  
pp. 329-337 ◽  
Author(s):  
Reza Shokrizadeh ◽  
Abbas Saghaei ◽  
Vahid Amirzadeh
Author(s):  
SIEBRAND J. WIERDA ◽  
TON STEERNEMAN

The T2 control chart is a multivariate SPC tool that monitors the mean vector of a process and that examines whether it remains stable over time. This paper examines the probability that the T2 control chart signals for an out-of-control situation. This probability is called the power of the chart. We study the effect on the power consequent on a change in the sample sizes, the dimension, or the level. For the bivariate case, we consider the impact on the power consequent on a change in the correlation coefficient. Finally, we examine what happens if the assumption that the covariance matrix is stable over time is violated.


Author(s):  
Masoud Tavakoli ◽  
Reza Pourtaheri

Due to the proper performance of Bayesian control chart in detecting process shifts, it recently has become the subject of interest. It has been proved that on Bayesian and traditional control charts, the economic and statistical performances of the variable sampling interval (VSI) scheme are superior to those of the fixed ratio sampling (FRS) strategy in detecting small to moderate shifts. This paper studies the VSI multivariate Bayesian control chart based on economic and economic-statistical designs. Since finding the distribution of Bayesian statistic is t complicated, we apply Monte Carlo method and we employ artificial bee colony (ABC) algorithm to obtain the optimal design parameters (sample size, sampling intervals, warning limit and control limit). In the end, this case study is compared with VSI Hotelling’s T2 control chart and it is shown that this approach is more desirable statistically and economically.


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