The basic assumption of the parametric control charts is that underlying process follows specific distribution. appropriateness questionable when different industrial applications do not support this desired assumption. Recently, nonparametric have been introduced to overcome deficiency charts. Nonparametric same in-control run-length characteristics for all continuous distributions and are rob...

A new method is developed for a fast identification of the stability situation of industrial processes. The proposed method includes two factor ratios of the control constants for the upper and lower control limits to process these constants. An indication ratio is then defined as the ratio of the maximum data range value to the difference between the maximum and average values for individual d...

We propose a Shewhart control chart based on gauging theoretically continuous observations into multiple groups. This chart is designed to monitor the process mean and standard deviation for deviations from stability. By assuming an underlying normal distribution, we derive the optimal grouping criteria that maximizes the expected statistical information available in a sample. Control charts ba...

Count data appears widely in finance, biomedical science, psychology, actuarial insurance, road safety and many other areas of life, it is often multivariate. In this paper, we consider using the multivariate exponentially weighted moving average (MEWMA) control chart method to monitor count under assumption Poisson distribution, which derived by He [1] from another form gamma distribution. We ...