Robust multivariate quality control charts for enhanced variability monitoring

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 Haw...

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Bibliographic Details
Published in:Quality and reliability engineering international 2024-04, Vol.40 (3), p.1369-1381
Main Authors: Ali, Taha Hussein, Sedeeq, Bekhal Samad, Saleh, Dlshad Mahmood, Rahim, Alan Ghafur
Format: Article
Language:English
Subjects:
Algorithms
Control charts
Control limits
Multivariate analysis
multivariate quality control charts
outliers
Outliers (statistics)
Quality control
robust
Robust control
S|‐Chart
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Summary: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.
ISSN:0748-8017
1099-1638
DOI:10.1002/qre.3472