Fluidized Bed Coating

Improving the fluidized bed coating process with PAT & AI

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On the morning of February 25, 2015, a doctoral defense was performed by Carlos Alexandre Moreira da Silva, Master in Chemical Engineering from University State of Campinas (Unicamp), under Prof. Dr. Osvaldir Taranto Pereira’s supervision.

UNICAMP Geisi Rojas Barreto Malvern

From left to right: Prof. Dr Fábio Bentes Freire* (Universidade Federal de São Carlos); Prof. Dr Marcos Antonio De Souza Barrozo* (Universidade Federal de Uberlândia); Prof. Dr Maria Aparecida Silva* (Unicamp); Dr. Carlos Alexandre Moreira Da Silva (Author); Prof. Dr Sandra Cristina Dos Santos Rocha* (Unicamp); Prof. Dr Osvaldir Pereira Taranto* (Doctoral Supervisor) and Geisi Rojas Barreto (Applications Scientis at Malvern Instruments, Inc).
*Doctoral Defense Committee Members.

The thesis titled “Application of Process Analytical Technology and Artificial Intelligence to monitor and control a fluidized bed coating process” developed in Chemical Engineering Faculty at the State University of Campinas, set an innovation in the study of the key parameters involved in fluidized bed coating and granulation processes. The research group already has extensive experience with relevant publications in the characterization of the physical properties of solids, in addition to the investigation of coating particles in moving bed equipment (fluidized bed, spouted bed, vibrofluidized bed, rotating pulsated fluid bed).  Malvern’s team followed the process closely during this hard but rewarding work, and could not help but share the news!

The main concept of this PhD thesis was to develop real-time monitoring and control strategies for fluidized bed coating processes. In this process used for coating particles, a stream of hot air moves the particulate material dynamically and heats it. A liquid stream (binder) is atomized on the particles and the coating begins to happen when the atomization and drying conditions are properly balanced.  This process is widely used in various fields, because it is possible to cover large amount of material and still perform the drying of the particles in the same equipment. Due to the high mass and heat exchange, facilitated by the fluidization movement, the coated particles generally have a uniform coating.

This thesis aimed to apply the Gaussian spectral analysis methodology based on pressure fluctuation signals processing for the development of a control system based on Fuzzy Logic, to monitor the stability of the fluidization regime in the coating process. Comparisons between the fluid dynamic conditions of the processes with and without control were analyzed. To assess the quality of particles, an in-line particle probe (Parsum IPP 70S) was used to verify the initial signs of undesirable agglomeration. With the automated system, it was possible to associate the instability of the fluidization in relation to high agglomeration rate.

Understanding the relationship between the fluid-dynamic behavior of the phases and the evolution of the particle size is not easy and there is evident need to study further. One of the major questions of the thesis is “can a stable fluidization regime be obtained with process control to ensure the growth kinetics progress appropriately?”. For coating process, the coating layer median thickness was evaluated, the atomization end-point phase and the start of drying process, as well as ability to detect the initial formation of agglomerates (undesirable phenomenon) in the bed. All studies were carried out on laboratory scale.

The Process Analytical Technology application (PAT – Parsum IPP 70S probe) in the coating process allowed a better understanding of particle growth dynamicss in the fluidized bed. Coating and agglomeration growth phases were observed and could be properly evaluated using the Parsum probe in addition to the impact on the dynamic behavior by varying the operating conditions in the coating suspension flow rate as it is atomized onto the particles and while applying process control.

In-line median particle size results obtained by Spatial Filter Velocimetry (Parsum probe) were proven using traditional offline methods, such as, laser diffraction (Mastersizer 3000) and an innovative analysis tool, the static automated imaging of particle size and shape (Morphologi G3).

Automated image analysis allowed evaluation of particle shapes, and confirm formation of agglomerates, showing that from Circular Equivalent mean diameter of 420 microns, the process of coating microcrystalline cellulose with aqueous suspension is resulting in agglomeration, even if process conditions are controlled by Fuzzy Logic. At this point the mechanism of coating individual particles is no longer prevalent and the process is transforming into a granulation. Use of the in-line particle size analysis equipment from Malvern Instruments helped in defining the end point of the process for producing the required coating thickness while reducing the risk of loss of stability in the fluid bed.

This doctoral thesis used the most modern and reliable tools available to monitor and control the formation of unstable behavior in fluidization regime and excessive agglomeration. This study is an important because monitoring the appearance of the defluidization phenomenon and agglomeration in the early stages is critical to ensure the attainment of particles with uniform size distribution, low moisture content and homogeneous dispersion of the film coating on the materials.  Congratulations to Carlos on this exceptional work – we look forward to seeing where it takes him in the future.

Article written with the help of Carlos Alexandre da Silva.