Performance of Modified Exponentially Weighted Moving Average (M-EWMA) Control Charts Using Transformed F-Distribution

The Modified Exponentially Weighted Moving Average (M_EWMA) control chart is a novel statistical tool designed to enhance process monitoring, particularly in scenarios involving F-distributed data. This research investigates its effectiveness by analyzing control limits, process variability, and shift detection capabilities. Results indicate that the M_EWMA chart offers stable control limits and low variance under normal conditions, ensuring a reliable framework for maintaining process stability. The study evaluates the impact of the smoothing parameter λ on the chart's sensitivity. Smaller λ values result in tighter control limits, enabling the detection of minor shifts, while larger λ values allow for greater tolerance, reducing false alarms. The chart's adaptability to varying process monitoring requirements highlights its versatility across industrial applications. A comparative analysis with the method proposed by Saghir et al. (2021) demonstrates the superior performance of the M_EWMA chart. Unlike traditional approaches, the M_EWMA chart achieves immediate detection of large shifts, maintaining consistent Average Run Length (ARL₁) values irrespective of shift magnitude or λ. This finding underscores its robustness and efficiency in rapid shift detection. In conclusion, the M_EWMA control chart represents a significant advancement in statistical process monitoring. Its ability to balance sensitivity and robustness makes it an indispensable tool for modern quality control practices, offering a reliable and effective solution for detecting process deviations and maintaining operational excellence.