Journal article

Copula-based monitoring schemes for non-Gaussian multivariate processes

Pavel Krupskii, Fouzi Harrou, Amanda S Hering, Ying Sun

JOURNAL OF QUALITY TECHNOLOGY | TAYLOR & FRANCIS INC | Published : 2019

Abstract

Multivariate statistical monitoring charts are efficient tools for assessing the quality of a process by identifying abnormalities. Most commonly used multivariate monitoring charts, such as the Hotelling T2 rule, however, assume the availability of uncorrelated Gaussian observations. Unfortunately, very often, real data do not satisfy these assumptions, and thus limit the usefulness of these techniques in practice. Furthermore, in many real applications, changes can occur in the shape of the multivariate distribution of the process while its mean or variance remains the same. Conventional process monitoring charts, such as the T2 chart, fail to detect such changes in the distribution. In th..

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University of Melbourne Researchers

Grants

Awarded by King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR)


Funding Acknowledgements

The research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No: OSR-2015-CRG4-2582.