MaxEWMA Control Chart for a Weibull Process with Individual Measurements

To monitor a Weibull process with individual measurements, some methods such as power transformation, inverse erf function, and Box–Cox transformation have been used to transform the Weibull data to a normal distribution. In this study, we conduct a simulation study to compare their performances in terms of the bias and mean square errors. A practical guide is recommended. Additionally, we present the maximum exponentially weighted moving average chart based on the transformation method to monitor a Weibull process with individual measurements. We compare the average run lengths of the proposed chart and the combined individual and moving range charts under the three cases including mean changes, sigma changes, and both mean and sigma changes. It is shown that the proposed control chart outperforms the combined individual and moving range charts for all three cases. Moreover, two examples are used to illustrate the applicability of the proposed control chart.