A Systems Engineering Approach to Dry Milling with Grinding Aid Additives

Publication Reference: 
FRR-44-09
Author Last Name: 
Kwade
Authors: 
Anderson Chagas, Arno Kwade
Report Type: 
FRR - Final Report
Research Area: 
Systems Engineering
Publication Year: 
2023
Country: 
Germany

This 4 year project (3 years plus one extra year due to Corona) aims in developing a system engineering approach for understanding, optimizing and scaling industrial dry grinding processes, with a special focus on the manipulation of the material properties and, thus, the grinding and classification efficiency by the use of grinding or flow aid substances. In terms of process units for its first phase, the project deals with dry grinding circuits consisting of a ball mill and air classifier. The experimental effort done so far was conducted on a pilot scale circuit. 

From the literature and from experiments conducted, it was noted that during milling operations, grinding aids (GA) affect the process mainly in: tendency of fine particle agglomeration; amount of material coated on equipment surfaces; powder flowability; total mass of product inside the mill and mean residence time; as well as product fineness after grinding. In terms of the air classification process, it was observed that grinding aid show little to no direct impact of particle cut size. However, they play a stronger role on improving classification efficiency, by improving particle dispersion on air streams and promoting lower recirculation of smaller then target size particles back into the milling stage.

The project work was divided in four main work packages:

  1. Identify which aspects of the ball milling process are affected by different grinding aids
  2. Identify which aspects of the air classification process are affected by different grinding aids
  3. Validate the previous findings on closed circuit milling operations and observe the grinding aid impacts on individual units combines in the overall closed circuit process
  4. Modify process models from the literature to account for the presence of GA in the systems behavior, implement a flowsheet simulation tool and validate the flowsheet with mill-classifier circuit data