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Multivariate Methods for Process Data Analysis – A Batch Process Application
Author(s) -
Krennrich G.
Publication year - 2001
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/1521-4125(200112)24:12<1235::aid-ceat1235>3.0.co;2-f
Subject(s) - process (computing) , multivariate statistics , computer science , batch processing , resampling , partial least squares regression , data mining , process engineering , engineering , artificial intelligence , machine learning , operating system , programming language
How can available process data be used in conjunction with multivariate techniques to analyze and improve existing batch processes? One particular application of the Partial Least Squares method is reviewed. Using a real‐world example from the chemical industry, the structure of the process data as well as appropriate resampling and data pretreatment techniques are described.