Statistical process monitoring of industrial batch processes
This White Paper summarizes the findings from three case studies involving the application of multivariate statistics to batch processes, and provides a comparison of different approaches to monitoring batch process operations.
By O. Marjanovic and B. Lennox, School of Engineering, University of Manchester; and D. Sandoz and D. Lovett, Perceptive Engineering Ltd.
THE MANUFACTURE OF high-value products involves many different batch processes, for example industrial fermenters. Such processes require high levels of consistency in their operation to ensure minimal losses of raw materials, utilities and product. Recent application studies have indicated that multivariate statistical technology can provide some support when trying to maintain consistent operation in complex batch processes.
This White Paper summarizes the findings from three case studies involving the application of multivariate statistics to batch processes. Two of the studies are taken from the fermentation industry with the third study involving a comprehensive penicillin production simulation model. The main focus of this paper is to demonstrate how realistic upsets in process operation can be detected and graphically presented using statistical process monitoring technologies. Further to this, the paper provides a comparison of different approaches to monitoring batch process operations.
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Author: World Batch Forum
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