DocumentCode
2450577
Title
Statistical approaches to industrial process plant modelling
Author
Hartnett, Margaret ; Irwin, G.W.
Author_Institution
Dept. of Electr. & Electron. Eng., Queen´´s Univ., Belfast, UK
fYear
1998
fDate
35809
Firstpage
42552
Lastpage
42559
Abstract
The objective of this contribution is to describe the role of the increasingly popular multivariate SPC (MSPC) methods in the context of process engineering. This involves a discussion of some of the techniques used, the application areas in which they are being implemented and some of their limitations which are being addressed in recent algorithm modifications. To illustrate some of the topics raised, a case study is briefly described in which a principal component analysis based approach is used for predictive modelling of an overheads condenser reflux drum system
Keywords
statistical process control; industrial process plant modelling; multivariate SPC; overheads condenser reflux drum system; predictive modelling; principal component analysis; process engineering; statistical approaches;
fLanguage
English
Publisher
iet
Conference_Titel
Multidimensional Systems: Problems and Solutions (Ref. No. 1998/225), IEE Colloquium on
Conference_Location
London
Type
conf
DOI
10.1049/ic:19980166
Filename
668213
Link To Document