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Updated: Feb 16, 2026

Twin-Screw Extrusion Process to Produce Renewable Fiberboards
Published on: January 27, 2021
Transparent predictive modelling of the twin screw granulation process using a compensated interval type-2 fuzzy
Wafa' H AlAlaween1, Bilal Khorsheed2, Mahdi Mahfouf1
1Department of Automatic Control and Systems Engineering, The University of Sheffield, UK.
Abstract:
In this research, a new systematic modelling framework which uses machine learning for describing the granulation process is presented. First, an interval type-2 fuzzy model is elicited in order to predict the properties of the granules produced by twin screw granulation (TSG) in the pharmaceutical industry. Second, a Gaussian mixture model (GMM) is integrated in the framework in order to characterize the error residuals emanating from the fuzzy model. This is done to refine the model by taking into account uncertainties and/or any other unmodelled behaviour, stochastic or otherwise. All proposed modelling algorithms were validated via a series of Laboratory-scale experiments. The size of the granules produced by TSG was successfully predicted, where most of the predictions fit within a 95% confidence interval.
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