Investigation of Particle Properties and Dynamic Modelling of Fluidized Bed Spray Granulation for Its Autonomous Control with Intelligent Digital Twin

During fluidized bed spray granulation process, the particle moisture content and bed temperature are of high importance due to their influence on the final product properties such as morphology, flowability and hardness. However, the classical time-consuming loss on drying method for measuring particle moisture content usually leads to delayed process control and defect production. Hence, inline monitoring of particle moisture content becomes necessary. Additionally, the influence of process parameters on the particle moisture content and bed temperature should be modeled with flowsheet simulation to ensure a faster process prediction, which contributes to the development of a digital twin for the autonomous control of fluidized bed processes.

In this work, microcrystalline cellulose particles are coated in a lab-scale fluidized bed spray granulator, with the inline measurement of the particle moisture content based on microwave transmission. Important process parameters are varied, including the flow rate and the temperature of the fluidization air, the water spray rate and the bed mass. The resulting inline particle moisture content and bed temperature are correlated with the process parameters using the response surface methodology. The desired process parameter ranges are determined.

The dynamic behavior of particle moisture content and bed temperature during granulation are modeled based on drying kinetics. The established models are implemented in the open-source dynamic flowsheet simulation software Dyssol [1] and validated with experimental results. The simulation input parameters and results serve further for the development of a digital twin for the autonomous control of fluidized bed spray granulation.

[1] Skorych, V., Dosta, M., Heinrich, S.: Dyssol – an open-source flowsheet simulation framework for particulate materials, SoftwareX, Volume 12 (2020), 100572, DOI: 10.1016/j.softx.2020.100572