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Theodora Kourti
Researcher at McMaster University
Publications - 44
Citations - 5799
Theodora Kourti is an academic researcher from McMaster University. The author has contributed to research in topics: Statistical process control & Multivariate statistics. The author has an hindex of 22, co-authored 44 publications receiving 5536 citations. Previous affiliations of Theodora Kourti include GlaxoSmithKline.
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Statistical Process Control of Multivariate Processes
TL;DR: An overview of multivariate statistical methods use for the statistical process control of both continuous and batch multivariate processes and examples are provided of their use for analysing the operations of a mineral processing plant, for on-line monitoring and fault diagnosis of a continuous polymerization process and for the on- line monitoring of an industrial batch polymerization reactor.
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Process analysis, monitoring and diagnosis, using multivariate projection methods
TL;DR: Applications are provided on the analysis of historical data from the catalytic cracking section of a large petroleum refinery, on the monitoring and diagnosis of a continuous polymerization process and on the Monitoring of an industrial batch process.
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Analysis of multiblock and hierarchical PCA and PLS models
TL;DR: It is recommended that in cases where the variables can be separated into meaningful blocks, the standard PCA and PLS methods be used to build the models and then the weights and loadings of the individual blocks and super block and the percentage variation explained in each block be calculated from the results.
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Multivariate SPC Methods for Process and Product Monitoring
TL;DR: Statistical process control methods for monitoring processes with multivariate measurements in both the product quality variable space and the process variable space are considered.
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Application of latent variable methods to process control and multivariate statistical process control in industry
TL;DR: In this article, an overview of the latest developments in multivariate statistical process control (MSPC) and its application for fault detection and isolation (FDI) in industrial processes is presented.