Unit Interval Time and Magnitude Monitoring Using Beta and Unit Gamma Distributions

Quick detection of an assignable cause is necessary for process accuracy with respect to the specifications. The aim this study monitor time and magnitude processes based on unit-interval data. To end, maximum exponentially weighted moving average (Max-EWMA) control chart simultaneous monitoring event proposed. be precise, beta unit gamma distributions are considered develop Max-EWMA chart. chart’s performance accessed using run length (ARL), standard deviation (SDRL), different quantiles distribution through extensive Monte Carlo simulations. Besides a comprehensive simulation study, proposed charting methodology applied real data set. results show that more efficient in detecting small medium-sized shifts. also indicate shifts detected quickly as compared pure shift.