Combined Feedforward/Feedback Control of an Integrated Continuous Granulation Process View Full Text


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Article Info

DATE

2018-10-04

AUTHORS

Glinka Cathy Pereira, Shashank Venkat Muddu, Andrés David Román-Ospino, Don Clancy, Benoit Igne, Christian Airiau, Fernando J. Muzzio, Marianthi Ierapetritou, Rohit Ramachandran, Ravendra Singh

ABSTRACT

Continuous manufacturing offers shorter processing times and increased product quality assurance, among several other advantages. This makes it an ever-growing interest among pharmaceutical companies. A suitable efficient control system is however desired for continuous pharmaceutical manufacturing to achieve a consistent predefined end product quality. In order to control product quality more accurately, the effects of input disturbances need to be proactively mitigated. Therefore, it is desired that a combined feedforward/feedback control system integrated with suitable process analytical technology (PAT) be implemented over a traditional feedback-only control system. The feedforward controller measures and takes corrective actions for disturbances proactively before they affect the process and thereby product quality. The feedback controller considers the real-time deviation of control variable from a pre-specified set point and keeps it at a minimum possible value. The deviation of a control variable from the set point could be due to both measurable and unmeasurable disturbances. In this work, a combined control strategy has been developed for a continuous twin screw wet granulation (WG) process. An integrated flowsheet model was developed and simulated in order to evaluate the effect of control loops on critical quality attributes (CQAs). Different strategies of manipulation were evaluated and the best strategy was identified. In silico study on the combined feedforward/feedback control strategy and feedback-only control strategy demonstrates that the combined loop results in diminished variability of the CQAs. More... »

PAGES

1-27

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12247-018-9347-8

DOI

http://dx.doi.org/10.1007/s12247-018-9347-8

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https://app.dimensions.ai/details/publication/pub.1107372628


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