Robust multivariate quality control charts for enhanced variability monitoring

Abstract

Abstract In this research, it was proposed to create three new robust multivariate charts corresponding to the |S|‐ chart, which are robust to outliers, using three methods, an algorithm, namely the Rousseuw and Leroy algorithm, Maronna and Zamar, and the family of ‘concentration algorithms’ by Olive and Hawkins. Then the comparison between the proposed and classical method of the researcher Shewhart depends on the total variance (trace variance matrix), the general variance (determinant of the variance matrix), and the difference between the upper and lower control limits to obtain the most efficient charts against outliers through simulation and real data and using a program in the MATLAB language designed for this purpose. The study concluded that the proposed charts dealt with the problem of the influence of outliers and were more efficient than the classical method, in addition, the proposed robust chart (Orthogonalized Gnanadesikan‐Kettenring) was more efficient than the rest of the proposed charts.

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