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On-line monitoring of a sugar crystallization process

Lookup NU author(s): Dr Alexandros Simoglou, Professor Elaine Martin, Emeritus Professor Julian Morris

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Abstract

The present paper reports a comparative evaluation of four multivariate statistical process control (SPC) techniques for the on-line monitoring of an industrial sugar crystallization process. The process itself is challenging since it is carried out in multiple phases and there exists strong non-linear and dynamic effects between the variables. The methods investigated include classical on-line univariate statistical process control, batch dynamic principal component analysis (BDPCA), moving window principal component analysis (MWPCA), batch observation level analysis (BOL) and time-varying state space modelling (TVSS). The study is focused on issues of on-line detection of changes in crystallization process operation, the early warning of process malfunctions and potential production failures; problems that have not been directly addressed by existing statistical monitoring schemes. The results obtained demonstrate the superior performance of the TVSS approach to successfully detect abnormal events and periods of bad operation early enough to allow bad batches and related losses in amounts of recycled sucrose to be significantly reduced. © 2005 Elsevier Ltd. All rights reserved.

Publication metadata

Author(s): Simoglou A, Georgieva P, Martin EB, Morris AJ, Feyo De Azevedo S

Publication type: Article

Publication status: Published

Journal: Computers and Chemical Engineering

Year: 2005

Volume: 29

Issue: 6

Pages: 1411-1422

ISSN (print): 0098-1354

ISSN (electronic): 1873-4375

Publisher: Pergamon

URL: http://dx.doi.org/10.1016/j.compchemeng.2005.02.013

DOI: 10.1016/j.compchemeng.2005.02.013

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