Normality is a common assumption for many quality control charts. One should expect misleading results once this assumption is violated. In order to avoid this pitfall, we need to evaluate this assumption prior to the use of control charts which require normality assumption. However, in certain cases either this assumption is overlooked or it is hard to check. Robust control charts and bootstra...

In the development of industrial processes there are situations where it is necessary to control or simultaneously monitor two or more quality variables of the production process. The problems of process monitoring where several related variables are studied can be controlled by means of multivariate control charts. The objective of this work is to describe the implementation of the control cha...

In this paper a multivariate quality control procedure is offered in which several correlated stages are present in production systems and in each stage there are several correlated control variable. Using Hotelling's T2 statistic, first, each stage is tested for being out of control. Then out of control variables are selected using Murphy's method. The remainder of the research involves evalua...