A STATISTICAL FRAMEWORK FOR ECONOMIC APPLICATIONS OF DOUBLE MULTIVARIATE EXPONENTIALLY WEIGHTED MOVING AVERAGE (DMEWMA) CONTROL CHARTS

This paper proposes an Economic Statistical Design of the Double Multivariate Exponentially Weighted Moving Average (DMEWMA) control chart and compares it with the Multivariate Exponentially Weighted Moving Average (MEWMA) control chart. Using Monte Carlo simulations and the Lorenzen and Vance Cost model, the cost-effectiveness of both designs is analyzed. Results show that the DMEWMA control chart offers superior performance in reducing production costs, particularly when monitoring multiple quality characteristics. Recent advances in statistical quality control further highlight the importance of efficient control chart design for minimizing costs in modern manufacturing environments.