Liquid‐to‐solid ratio control as an advanced process control solution for continuous twin‐screw wet granulation |
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| Authors: | Niels Nicolaï Fien De Leersnyder Dana Copot Michiel Stock Clara M Ionescu Krist V Gernaey Thomas De Beer |
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| Affiliation: | 1. Dept. of Pharmaceutical Analysis, Faculty of Pharmaceutical Sciences, Laboratory of Pharmaceutical Process Analytical Technology (LPPAT), Ghent University, Ottergemsesteenweg 460, Ghent 9000, Belgium;2. Dept. of Data Analysis and Mathematical Modelling, BIOMATH, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, Ghent 9000, Belgium;3. Dept. of Electrical Energy, Metals, Mechanical Constructions and Systems, Research Group on Dynamical Systems and Control, Ghent University, Technologiepark 914, Zwijnaarde 9052, Belgium;4. Dept. of Data Analysis and Mathematical Modelling, KERMIT, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, Ghent 9000, Belgium;5. Dept. of Chemical and Biochemical Engineering, CAPEC‐PROCESS Research Center, Technical University of Denmark, Building 229, Kgs. Lyngby 2800, Denmark;6. Dept. of Pharmaceutical Analysis, Faculty of Pharmaceutical Sciences, Laboratory of Pharmaceutical Process Analytical Technology (LPPAT), Ghent University, Ottergemsesteenweg 460, Ghent 9000, BelgiumThomas De Beer and Ingmar Nopens shared last authorship. |
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| Abstract: | Assuring compliance of intermediate and final quality attributes in a continuous pharmaceutical manufacturing campaign is of utmost importance. Application of corrective actions might be required in real‐time. This work exemplifies the steps needed to identify a linear pulse transfer function for the dynamic behavior of the granule liquid‐to‐solid ratio (%w/w) at the end of the granulation unit of a commercial ConsiGmaTM‐25 production line. Near‐infrared spectroscopy was used to monitor the granule composition in‐line. The outcome for both the tracking and regulator problem using either conventional or model predictive control was implemented and evaluated. Dynamic setpoints were correctly followed and an RMSE of 0.25%w/w with respect to the setpoint was obtained when inducing artificial disturbances. Important practical challenges were also tackled. Examples are fouling, computational limitations, and the limited flexibility of the automation software. Applying the proposed advanced process control solution offers an answer to upstream material flow rate deviations. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2500–2514, 2018 |
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| Keywords: | spectroscopy in‐line monitoring system identification feedback control |
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