We derive a dynamic model for roller compaction process based on Johanson’s rolling theory, which is used to predict the stress and density profiles during the compaction and the material balance equation which describes the roll gap change. The proposed model considers the relationship between the input parameters (roll pressure, roll speed, and feed speed) and output parameters (ribbon density and thickness), so it becomes possible to design, optimize, and control the process using the model-based approach. Currently, the operating conditions are mostly found by trial and error. The simulation case studies show the model can predict the ribbon density and gap width while varying roll pressure, feed speed, and roll speed. The roll pressure influences the ribbon density much more than roll speed and feed speed, and the roll gap is affected by all three input parameters. Both output variables are very insensitive to the fluctuation of inlet bulk density. If the ratio of feed speed to roll speed is kept constant, neither ribbon density nor gap width change, but the production rate changes proportionally with feed speed. Based on observations from simulations, a control scheme is proposed. Furthermore, Quality by Design of the roller compactor can be achieved by combining this model and optimization procedure.

• Purdue University

• Control
• Modeling

1. Control
2. Dry granulation
3. dynamic modelling
4. Johnson's rolling theory
5. modeling
6. process control
7. Quality by Design (QbD)
8. Research Article
9. Roller compaction