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Lookup NU author(s): Dr Alexandros Simoglou,
Professor Elaine Martin,
Emeritus Professor Julian Morris
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Multivariate statistical process control (MSPC) is a tool for the comprehensive monitoring of the performance of a manufacturing process. There is now a real need to demonstrate the applicability of MSPC to complex manufacturing processes and highlight the benefits that can be derived from its implementation. Alongside this, is the increasing interest in predicting quality or important chemical quality variables associated with product yield and production. This paper demonstrates the performance monitoring potential of MSPC and the predictive capability of canonical variates analysis and projection to latent structures by application to an industrial fluidised-bed reactor. (C) 2000 Elsevier Science Ltd. All rights reserved.
Author(s): Simoglou A, Martin EB, Morris AJ
Publication type: Article
Publication status: Published
Journal: Control Engineering Practice
ISSN (print): 0967-0661
ISSN (electronic): 1873-6939
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