A Bootstrap Approach to Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) Control Charts for Monitoring Process Means

This research proposed a bootstrapped method for setting control boundaries and detecting out-of-control signals. The proposed approaches for determining control limits are designed to address the issues of distributional assumptions and out-of-control signal detection. It enables the setting of control limits, which can improve the detection of the out control signal, according to the results of the performance evaluation. When compared to previous methods, bootstrapped methods improve the discovery of out of control signals in any process mean. The methods outperformed the conventional CUSUM, EWWMA and EWMA CUSUM control chart in detection of early shift in a process mean.