Chemometric techniques in multivariate statistical modelling of process plant

M Hartnett, G. Lightbody, George Irwin

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

The techniques of principal component analysis (PCA) and partial least squares (PLS) are introduced from the point of view of providing a multivariate statistical method for modelling process plants. The advantages and limitations of PCA and PLS are discussed from the perspective of the type of data and problems that might be encountered in this application area. These concepts are exemplified by two case studies dealing first with data from a continuous stirred tank reactor (CSTR) simulation and second a literature source describing a low-density polyethylene (LDPE) reactor simulation.
Original languageEnglish
Pages (from-to)749 - 754
Number of pages8
JournalRoyal Society of Chemistry
Volume121
DOIs
Publication statusPublished - 1996

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