Joint Monitoring Non-Parametric EWMA Control Chart Based On Normal Transformation

Control chart is one of the important tools for monitoring the stability of the production process in statistical process control.Most of the traditional control charts which are used to monitor the mean and variance of the quality characteristics are all based on the assumption that the related quality characteristics follow normal distributions when constructing the control limits.However,in practice,there are also many variables whose distributions are substantially different from normal distributions.When product quality characteristics is non-normal,it may reduce the efficiency of the control chart.We have proposed a new joint monitoring location parameter and scale parameter non-parametric EWMA control chart using two methods of data normalization,and discussed the effect of two data normalization methods on the control efficiency of control charts under different conditions.The results show that when the initial distribution is non-normal,our method has better monitoring efficiency than before.Finally,we give an example of a practical application to show that our control chart is still of practical value.