The discrete element method (DEM) is used extensively for the simulation of wet granulation process. However, DEM is typically limited to modeling short time durations and cannot predict long time process properties (such as granule residence time and agglomerate final size). Moreover, the number of model particles in a DEM simulation cannot be chosen arbitrarily high due to limitations in computational power. To solve those issues, we first use a coarse grain approach that consists in selecting a region with a sufficiently large number of particles enough to extract macro properties. Then, based on these macroscopic properties, the wet granulation equipment is separated into compartments within which flow rates and properties are uniform and scaling up guidelines can be developed. Finally, using population balance modeling (PB), process properties are predicted for different materials and equipment geometries. In our study, we use the pan granulator as a case study. The objective and steps of this work are listed below:
Ahmed Jarray has an Ing. in chemical and process engineering (2011, Gabes, Tunisia), MSc in chemical and process engineering (2012, Lyon, France) and a Ph.D. in chemical and process engineering (2015, Toulouse, France). His research work focuses on wet granulation processes and agglomeration mechanisms, with a strong interest in small scale modeling and computer aided simulation methods. His work also focuses on experimental characterization of agglomerates and binder-solid interactions.