Abstract:
Jaw crushers are considered among the primary crushers in mining industry. The
size reduction process, also known as comminution, is not only an energy intensive
process but also energy ine cient. There have been numerous attempts which aim at
optimising the energy e ciency of jaw crushers. For instance, the use of chemicals
to induce cracks before the breakage has been suggested but that process raises
the overall cost of aggregate production. The main objective of this research is to
optimise the energy e ciency of a single toggle jaw crusher using Discrete Element
Method (DEM). DEM was employed in prediction of the energy consumption of the
jaw crusher for di erent operating parameters. In a jaw crusher, the throw, reduction
ratio and toggle speed frequency are very critical to energy consumption. These
parameters were varied according to the guidelines used by jaw crusher manufacturers
and which have also been validated by researchers. Simulation of the comminution
process requires modelling of feed material. In this work, modelling of the feed
material (rocks) was carried out using EDEM Academic software. The Bonded
Particle Model (BPM) was selected as the technique for modelling the rocks due
to its superlative features, in comparison to Particle Replacement Model (PRM)
and Fast Breakage Model (FBM). For instance, in BPM, the particle dynamics are
retained after breakage unlike in PRM and FBM where broken particles are replaced
by new ones. In addition, an irregular shaped rock particle was created using the
custom Application Program Interface (API) feature in EDEM software. The use of
API required coding using C++ language which in turn made it possible for custom
factories to be created. The wear distribution along the jaw crusher liners was also
investigated using EDEM software. The wear distribution was depicted using the
Relative Wear feature in EDEM software. The energy e ciency was calculated from
new surface area created from fracture of the BPM rock. The results were fed into
MINITAB software which developed the regression model showing the relationship
between energy e ciency, throw, reduction ratio and toggle speed frequency. A
Genetic Algorithm was used to obtain the optimal energy e ciency. The optimal
energy e ciency was obtained as 59:778% at a throw of 35 mm, reduction ratio of 4
and a toggle speed frequency of 160 rpm. There was a great improvement in energy
e ciency of the single toggle jaw crusher in comparison to the 6:023% e ciency
of the un-optimised jaw crusher. In addition, conventional designs have e ciencies
of less than 10% and hence the results obtained in this research have shown that
maximisation of energy e ciency is possible. During the comminution process, it was
observed that throw, reduction ratio and toggle speed have di erent levels of impact
on the energy e ciency. The throw and reduction ratio were found to have a higher
impact on energy e ciency than the toggle speed frequency. Wear distribution was
also prominent near the Close Side Set (CSS) of the jaw crusher.