Correlation between process parameters and milling efficiency

• Main Author: Johansson, Anna
• Format: Others
• Language: English
• Published: Uppsala universitet, Oorganisk kemi 2012
• Subjects: Milling; Ball Mill; WC; Cemented Carbide; Particle Size
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-179625

An experimental ball-milling study was performed to compare the deagglomeration behavior and the evolution of the particle size distribution with increasing milling time of two relatively coarse WC powders used for the production of cemented carbide cutting tools. The WC-powders were found to have distinctly different particle size distributions and particle morphologies prior to milling. Lab-scale WC samples were made using a range of different process parameters and milling times. These were then analysed by means of microscopy, laser light scattering, gas adsorption BET analysis and X-ray powder diffraction, XRD, to attain particle size distribution, specific surface area and a mean crystal size, respectively. The results suggested a linear relation between log(particle size) and log(milling time) between 10 and 80 hours milling. The viscosity was shown to have a minor effect on the milling efficiency. Both the number of collisions of milling balls per unit time as well as the kinetic energy of the milling ball affected the size reduction; more collisions or higher energy resulted in a higher milling efficiency. The evaluation of the effect of the process parameters on milling efficiency was facilitated by the use of simple scaling factors. For example, all milling curves for samples with different WC amounts coincided when rescaling the milling time using a scaling factor based on the weight of the WC and milling balls. The same scaling factor could be used with success for rescaling the results from different trials obtained with laser light scattering, gas adsorption and XRD. The results of this work are useful for future work on modeling of the milling process which should lead to more accurate predictions of the outcome of milling unit operations.