On-line Monitoring of a Sugar Crystallization Process

• Type: Article in International Scientific Journal
• Date: 2005

Authors

A. Simoglou (Author) Other; P. Georgieva (Author) FEUP; E. B. Martin (Author) Other; J. A. Morris (Author) Other; S. Feyo de Azevedo (Author) FEUP

Journal

Title: Computers and Chemical Engineering

Vol. 29 No. 6

Pages: 1411-1422

ISSN: 0098-1354

Publisher: Elsevier

Indexing

ISI Web of Science

Scopus

COMPENDEX

Scientific classification

FOS: Engineering and technology > Chemical engineering

CORDIS: Technological sciences > Engineering > Chemical engineering

Other information

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific