In the powder processing industry, ball mills are common grinding equipment, widely used in mining, building materials, and chemical industries. If a user requires a processing capacity of 3 tons per hour and a finished particle size of 20 mesh (approximately 850 micrometers), a suitable model balancing capacity and particle size control must be selected.
20 mesh is considered a relatively coarse particle size, and the requirement for fine grinding is not high. Therefore, short-cylinder or grid-type ball mills are preferred. These types of equipment offer fast output and high efficiency, suitable for coarse grinding operations. For a processing capacity of 3 tons/hour, a wet overflow ball mill with a diameter of Φ1200×2400 (1.2 meters in diameter, 2.4 meters in cylinder length) or Φ1500×3000 is recommended. The former, with appropriate ball loading and rotational speed, can stably achieve a production capacity of 2.5–3.5 tons/hour; the latter offers higher redundancy, suitable for future capacity expansion.

For dry processing, it is recommended to configure a closed-loop process with a high-efficiency classifier to ensure the particle size is concentrated around 20 mesh, avoiding over-grinding. Meanwhile, the steel ball ratio should be adjusted according to the material hardness—for example, when processing medium-hard materials such as limestone, large balls of Φ60–Φ80mm can be used primarily to improve impact crushing efficiency.
Furthermore, the motor power, liner material, and automated control system must also be matched. For instance, a Φ1200×2400 ball mill is typically equipped with a 30–37kW motor, and manganese steel liners offer good wear resistance and long maintenance cycles.
In summary, for a working condition of "3 tons per hour, 20 mesh finished product," the Φ1200×2400 ball mill offers high cost-effectiveness and stable operation, making it an ideal choice. It is recommended to provide specific material properties before purchasing so that the manufacturer can design a customized solution to ensure optimal performance.