DocumentCode :
300593
Title :
Multi-stage batch process monitoring
Author :
Dong, Dong ; McAvoy, Thomas J.
Author_Institution :
Dept. of Chem. Eng., Maryland Univ., College Park, MD, USA
Volume :
3
fYear :
1995
fDate :
21-23 Jun 1995
Firstpage :
1857
Abstract :
Batch processes are very important to the chemical and manufacturing industries. Techniques for monitoring these batch processes to ensure their safe operation and that they produce consistent high quality products are needed. Nomikos and MacGregor (1994) present a multi-way principal component analysis (MPCA) approach for monitoring batch processes, and test results show that the method is simple, powerful, and effective. However MPCA is a linear method, and most batch processes are nonlinear. In this paper a nonlinear principal component analysis (NLPCA) method (Dong-McAvoy, 1993) is used for batch process monitoring. The main focus of this paper is on multi-stage batch process monitoring. The proposed approach and special problems for multi-stage batch processes are illustrated through a detailed simulation study
Keywords :
batch processing (industrial); chemical industry; manufacturing industries; monitoring; process control; chemical industries; manufacturing industries; multi-stage batch process monitoring; multi-way principal component analysis; nonlinear principal component analysis; Chemical engineering; Chemical industry; Chemical processes; Costs; Ear; Educational institutions; Monitoring; Principal component analysis; Production; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
Type :
conf
DOI :
10.1109/ACC.1995.531208
Filename :
531208
Link To Document :
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