An EWMA Chart for Monitoring Generalized Gamma Distributed Process

High-quality processes pave the way for zero-defect manufacturing systems, making traditional control charts practically inapplicable. To address this issue, control charts that monitor the time between events (TBE) of nonconforming products are adopted in monitoring high-quality processes. The generalized gamma (ggamma) distribution can effectively be adopted to represent a variety of critical distributions in process monitoring of TBE data. To monitor high-quality processes, this study focuses on developing an exponentially weighted moving average (EWMA) control chart for the ggamma-distributed process. The optimal parameters and values of the average run length, standard deviation of the run length and average time to signal of the proposed chart are obtained using the Markov chain approach. Comparative results demonstrate that the proposed chart is more sensitive to process shifts than the existing modified unbiased ggamma chart. An example is provided to illustrate the implementation of the proposed chart.