Product-Property Guided Scale-Up of a Fluidized Bed Spray Granulation Process Using the CFD-DEM Method

In this work, a method to predict the surface structures of particles produced by fluidized bed spray layering granulation using the CFD-DEM method was developed. A simple state-variable/event tracking approach was implemented to capture indirect quantifiers of the progression of structure-forming microprocesses. The state of the droplet at the time of impact on the particle surface, as well as the time required for drying, is correlated to product properties that quantify surface structure morphology such as roughness. A workflow for scale-up of fluidized bed granulation guided by product-property predictors is presented. The approach was tested on a demonstration case from the literature, where a particle core is coated with sodium benzoate solution. The experiment was scaled-up by a factor of eight to pilot-scale using the developed method. Varying the number of nozzles in use in the pilot-scale granulation affected the particle surface roughness due to the differing drying conditions encountered. On this basis, the ability of the tracked-quantity approach to capture the relationship between product properties and geometric feature or process conditions is demonstrated.

Automated summary

This work developed a method to predict the surface structures of particles produced by fluidized bed spray layering granulation using the CFD-DEM method, implemented a state-variable/event tracking approach to capture indirect quantifiers of the progression of structure-forming microprocesses, and successfully demonstrated the ability to capture the relationship between product properties and geometric features or process conditions.