A discrete element model (DEM) has been developed for an industrial batch bin blender in which three different types of materials are mixed. The mixing dynamics have been evaluated from a model-based study with respect to the blend critical quality attributes (CQAs) which are relative standard deviation (RSD) and segregation intensity. In the actual industrial setup, a sensor mounted on the blender lid is used to determine the blend composition in this region. A model-based analysis has been used to understand the mixing efficiency in the other zones inside the blender and to determine if the data obtained near the blender-lid region are able to provide a good representation of the overall blend quality. Sub-optimal mixing zones have been identified and other potential sampling locations have been investigated in order to obtain a good approximation of the blend variability. The model has been used to study how the mixing efficiency can be improved by varying the key processing parameters, i.e., blender RPM/speed, fill level/volume and loading order. Both segregation intensity and RSD reduce at a lower fill level and higher blender RPM and are a function of the mixing time. This work demonstrates the use of a model-based approach to improve process knowledge regarding a pharmaceutical mixing process. The model can be used to acquire qualitative information about the influence of different critical process parameters and equipment geometry on the mixing dynamics.
This study tested the effectiveness of using dynamic yield strength (DYS) and shear-cell experiments to calibrate the following discrete-element-method (DEM) parameters: surface energy, and the coefficients of sliding and rolling friction. These experiments were carried out on cohesive granules, and DEM models were developed for these experiment setups using the JKR cohesion contact model. Parameter-sensitivity analysis on the DYS model showed that the DYS results in the simulations were highly sensitive to surface energy and were also impacted by the values of the two friction coefficients. These results indicated that the DYS model could be used to calibrate the surface energy parameter once the friction coefficients were fixed. Shear-cell sensitivity analysis study found that the influence of surface energy on the critical-state shear value cannot be neglected. It was inferred that the shear-cell model has to be used together with the DYS model to identify the right set of friction parameters. Next, surface energy was calibrated using DYS simulations for a chosen set of friction parameters. Calibrations were successfully conducted for simulations involving experimentally sized particles, scaled-up particles, a different shear modulus, and a different set of friction parameters. In all these cases, the simulation DYS results were found to be linearly correlated with surface energy and were within 5% of the experimental DYS result. Shear-cell simulations were then used to compare calibrated surface-energy values for the scaled-up particles with the experimentally sized particles. Both the simulations resulted in similar critical-state shear values. Finally, it was demonstrated that a combination of DYS and shear-cell simulations could be used to compare two sets of friction parameters and their corresponding calibrated surface energy values to identify the set of parameters that better represent the flow behavior demonstrated by the experimental system.
Precise and effective feeding of small powder quantities remains a challenge in many fields, including pharmaceutical development and production. This paper demonstrates that a simple feeding principle can be applied to accomplish stable micro feeding (<100mg/s) and describes a gravimetric powder feeding system with a vibratory sieve mounted on a chute. Feeding was induced via vertical vibrations that can be adjusted within a broad range of frequencies and amplitudes. The feeding system was studied using different frequencies, amplitudes, sieves and powder properties. Feeding was characterized by means of a dynamic scale and high-speed camera recordings. The feeding system provided effective powder feeding even in a range of 1-2mg/s. It was shown that powder properties require special attention when the vibratory sieve-chute system operates at higher feed rates (or feeding times >30min), i.e., feeding at a higher throughput. A combination of discrete element method (DEM) simulations and compartment population balance model (PBM) was used to incorporate the proposed micro feed system into a continuous powder mixer (Gerike GCM250; Gerike Holding LTD., Regensdorf, Switzerland). It illustrates how oscillating feeding rates (the latter is a characteristic of the studied micro feeding system) affect the content uniformity of low dose blends, i.e., powder mixtures with a relatively low fraction of active pharmaceutical ingredient.
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