Feedback control strategies for a continuous industrial fluidized-bed granulation process

Implementation of real-time and in-line feedback control for a fluid bed granulation process

The application of process analytical technologies (PAT) to monitor critical quality attributes (CQAs) provides an important approach to enhance process understanding and improve the reliability of pharmaceutical production processes. The present study focuses on the first PAT based feedback control system for a fluid bed granulation batch process. Real-time particle size measurement by in-line spatial filtering technique (SFT) using a modified time-based buffer system was applied to define a target particle size after spraying a specific amount of binder solution. After identifying an appropriate control variable, a suitable strategy for feedback control was established, followed by tuning of the control loop to obtain best performance of the integrated system. By adapting the final target particle size within a specified range good functionality of the system could be demonstrated. Investigations of the robustness further showed that the implemented system enables the production of a predefined target particle size also by varying process and formulation parameters. The effect of increasing spray rates and binder concentrations on the particle size could be compensated in a given range by feedback control ensuring a predefined product quality. The study provides an advanced approach for quality assurance of fluid bed granulation.

Parameter Identification For Continuous Fluidized Bed Spray Agglomeration

Agglomeration represents an important particle formation process used in many industries. One particularly attractive process setup is continuous fluidized bed spray agglomeration, which features good mixing as well as high heat and mass transfer on the one hand and constant product throughput with constant quality as well as high flow rates compared to batch mode on the other hand. Particle properties such as agglomerate size or porosity significantly affect overall product properties such as re-hydration behavior and dissolubility. These can be influenced by different operating parameters. In this manuscript, a population balance model for a continuous fluidized bed spray agglomeration is presented and adapted to experimental data. Focus is on the description of the dynamic behavior in continuous operation mode in a certain neighborhood around steady-state. Different kernel candidates are evaluated and it is shown that none of the kernels are able to match the first six minutes with time independent parameters. Afterwards, a good fit can be obtained, where the Brownian and the volume independent kernel models match best with the experimental data. Model fit is improved for identification on a shifted time domain neglecting the initial start-up phase. Here, model identifiability is shown and parameter confidence intervals are computed via parametric bootstrap.

Influence of Thermal Conditions on Particle Properties in Fluidized Bed Layering Granulation

Fluidized bed layering granulation is frequently used to formulate particles of high quality. From previous studies, it is well known that the dynamic behavior of the process, as well as the product properties depend on operating parameters. The process is characterized by heat and mass transfer between fluidized particles and the surrounding fluidization medium. To investigate the mutual influence between particle phase and fluidization medium, a dynamic model is introduced. The model comprises two parts: a population balance model to describe the evolution of the particle sizes and a system of ordinary differential equations to account for thermal conditions. For the first time, the dynamic model considers the bidirectional coupling of particles and fluidization medium in fluidized bed layering granulation. By means of simulations, it is shown that the derived model is capable of reproducing the experimental findings.