Loss-on-Drying Prediction for a Vibrated Fluidised Bed Dryer by Means of Mass and Energy Balances

Abstract

PurposeContinuous wet granulation and drying require an adequate process control strategy to ensure the product quality. The most important critical quality attributes of dried granules are the granule size distribution and moisture content. Process analytical technologies (PATs) are available for real-time monitoring of moisture content by, e.g., near-infrared spectroscopy (NIRS), which requires additional installation and complex multivariate validation. Thus, a mass and energy balance (MEB) was derived for a vibrated fluidised bed dryer, which is part of the QbCon® 1 intended for continuous wet granulation and drying.MethodProcess parameters that are frequently logged were used for the derivation of a MEB. The predicted MEB was compared with the measured loss-on-drying (LOD) for two different formulations.ResultsThe model-derived data were in good agreement with the observed LOD, leading to RMSE values of 0.12–0.45.ConclusionThe implemented MEB can predict the LOD over time and thus might be suitable as a soft sensor without the installation of additional sensors. The obtained energy flux gives insight into the heat transfer, and the derived energy balance might be used to determine the required energy under certain drying conditions.