Intelligent real-time performance monitoring and quality prediction for batch/fed-batch cultivations.
Supervision of batch bioprocess operations in real-time during the progress of a batch run offers many advantages over end-of-batch quality control. Multivariate statistical techniques such as multiway partial least squares (MPLS) provide an efficient modeling and supervision framework. A new type of MPLS modeling technique that is especially suitable for online real-time process monitoring and the multivariate monitoring charts are presented. This online process monitoring technique is also extended to include predictions of end-of-batch quality measurements during the progress of a batch run. Process monitoring, quality estimation and fault diagnosis activities are automated and supervised by embedding them into a real-time knowledge-based system (RTKBS). Interpretation of multivariate charts is also automated through a generic rule-base for efficient alarm handling. The integrated RTKBS and the implementation of MPLS-based process monitoring and quality control are illustrated using a fed-batch penicillin production benchmark process simulator.
Undey
Cenk
C
Department of Chemical and Environmental Engineering, Illinois Institute of Technology, 10 W. 33rd Street, Chicago, IL 60616, USA.
Tatara
Eric
E
Cinar
Ali
A
D000465:Algorithms; D019149:Bioreactors; D003198:Computer Simulation; D003199:Computer Systems; D005103:Expert Systems / Q000295:instrumentation; D008954:Models, Biological; D015999:Multivariate Analysis; D010406:Penicillins / Q000378:metabolism
D010406:Penicillins