Automated production support for the bioprocess industry.
This paper describes the application of Artificial Intelligence and Multivariate Statistical Techniques to two industrial fermentation systems. In the first example, an Expert System is shown to provide tighter control of an important process parameter. This is shown to lead to improved consistency of operation. In the second application, Principal Component Analysis is applied to a final stage fermentation production facility. The results presented indicate that the algorithm can provide concise indicators of process faults that can be presented to the operators to assist them in taking suitable corrective actions.
Lennox
Barry
B
School of Engineering, University of Manchester, U.K. barry.lennox@man.ac.uk
Kipling
Kathryn
K
Glassey
Jarka
J
Montague
Gary
G
Willis
Mark
M
Hiden
Hugo
H
D000465:Algorithms; D005103:Expert Systems; D005285:Fermentation; D007218:Industrial Microbiology / Q000379:methods*; D015999:Multivariate Analysis; D011786:Quality Control; D013269:Stochastic Processes