(371c) Particle Size Control Using Model Predictive Control for a Spray Drying Process
AIChE Annual Meeting
2019
2019 AIChE Annual Meeting
Computing and Systems Technology Division
Interactive Session: Systems and Process Control
Tuesday, November 12, 2019 - 3:30pm to 5:00pm
Christian Barreto-Hernández and Carlos Velázquez-Figueroa
Department of Chemical Engineering, University of Puerto Rico at Mayaguez
The process of drying pharmaceuticals mixtures is always a challenge in terms of controlling particle size and optimizing control parameters. Spray drying offers available solutions for both of these problems by taking a slurry mixture and drying it in a one-step continuous process. Spray drying its more effective producing smaller and controllable particle size than its counterpart, jet-milling.
In this research a spray dried machine is studied and modified with temperature, flow and pressure controls. Spray theory is applied to develop a relation between spray size droplets and particle size after the drying phenomena takes place. Consequently, particle size equations are then used to develop a mathematical model that can be implemented into a model predictive control algorithm with the aim of controlling particle size of the material. Individual low level PIDs are put in place to manipulate the temperature and flow of the products entering the chamber, as well as maintaining the temperature of the spray drier chamber to achieve proper drying. An open loop characterization test was performed by setting the controller output signal manually. The manipulated variable (MV) is then measured and recorded for various elements. The process variables are also recorded along with the MV. Process parameters where obtained by an inspection of the process reaction curve. A final tuning of the parameters was achieved by changing the controller to automatic and adjusting the parameters to produce a desire reaction.