Executive Summary
Milling is commonly deployed in many industrial sectors for intended particle size
reduction. In this project, we aim to develop a robust methodology to link material
grindability with particle dynamics in a mill in order to provide an innovative step--
change in mill fingerprinting and optimization. This involves characterizing the stressing
events that prevail in a milling operation and establishing material grindability in the
context of the stressing events. The material grindability will require a detailed study of
the fundamental fracture and breakage mechanisms of individual particles under different
loading regimes, and how they relate to the mechanical properties and the final size
distribution. This will provide the fundamental scientific basis for developing appropriate
grindability measure capable of analysing particle breakage subjected to particle impact,
compression, and shear etc. pertaining to a milling process, which in turn will provide the
basis for an improved particle breakage model calibrated against the defined grindability.
The centrifugal impact pin mill has been selected as the first mill to be studied for this
project, in collaboration with Hosokawa Micron Ltd. The work performed in Year 4 of
the project is summarized here. UPZ100 pin mill experiments were conducted with the
effect of rotary speed and feed rate examined. Six parameters including particle size
distribution, median product size, relative size span, bond’s grinding energy, size
reduction ratio and specific surface area are chosen to characterize the milling results. In
particular, the relationship between relevant parameters is investigated. The grinding
energy approximately follows a linear relationship with the size reduction ratio. The
alumina particle requires more grinding energy as compared to the zeolite particle. The
population balance modelling (PBM) is used to predict the product size distribution in the
milling impact tests. As indicated by the general form of PBM, it shows that two
functions, i.e. selection and breakage functions have to be considered. The capacity of
PBM is exemplified by predicting product size distribution in the impact pin mill
considering two simple selection and breakage functions. The coupling framework of
PBM-DEM is presented considering the deficiency of PBM, which forms the platform
for the follow-on work.