Abstract
ABSTRACTMemory type control charts have built using logarithmic transformations for the normalization of unbiased sample variance for monitoring of changes in the dispersion of process. The intention of this study is to give a new hybrid exponentially weighted moving average (HEWMA) control chart for monitoring theprocess dispersion. The logarithmic transformation is used to normalize the distribution of sample variance. The execution of the proposed HEWMA control chart is evaluated in accordance with the average run length and standard deviation run length estimated with the help of Monte Carlo method. The proposed HEWMTn control chart has been compared with the corresponding existing charts to detect increase and decrease in the process variability. It showed that the proposed HEWMTn control chart is uniformly better than its parallels for detection of shifts in the process variability. A numerical study is also given to understand the operationalization of the proposed control chart.
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