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Title: A new robust multivariate EWMA dispersion control chart for individual observations
Authors: Ajadi, JO 
Zwetsloot, IM
Tsui, KL
Issue Date: May-2021
Source: Mathematics, May 2021, v. 9, no. 9, 1038
Abstract: A multivariate control chart is proposed to detect changes in the process dispersion of multiple correlated quality characteristics. We focus on individual observations, where we monitor the data vector-by-vector rather than in (rational) subgroups. The proposed control chart is developed by applying the logarithm to the diagonal elements of the estimated covariance matrix. Then, this vector is incorporated in an exponentially weighted moving average (EWMA) statistic. This design makes the chart robust to non-normality in the underlying data. We compare the performance of the proposed control chart with popular alternatives. The simulation studies show that the proposed control chart outperforms the existing procedures when there is an overall decrease in the covariance matrix. In addition, the proposed chart is the most robust to changes in the data distribution, where we focus on small deviations which are difficult to detect. Finally, the compared control charts are applied to two case studies.
Keywords: Covariance matrix
EWMA
Individual observations
Multivariate dispersion chart
Non-normality
Publisher: MDPI
Journal: Mathematics 
EISSN: 2227-7390
DOI: 10.3390/math9091038
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
The following publication Ajadi, J.O.; Zwetsloot, I.M.; Tsui, K.-L. A New Robust Multivariate EWMA Dispersion Control Chart for Individual Observations. Mathematics 2021, 9, 1038 is available at https://doi.org/10.3390/math9091038
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