monitoring mean and variability by gini chart for skew-normal distributed data

In order to monitor mean and variability of a process, the gini controlcharts based on the skewnormally distributed random samples is proposed. throughcomparing the false alarm rates of current scheme with those of existing mean anddispersion control charts, it is found out that the design structure of gini chart canimprove over other classic schemes based on assumption of skewnormal distributionfor the data. moreover, the superiority of the gini chart is studied by comparingthe discriminatory power curves of the skewnormal distribution with some existingcontrol charts. simulated studies and a real data example illustrate the usefulness ofthe proposed approach.