COMMINUTION
other upstream parts of the mining process when it comes to
digitalisation.
“The mining front-end (blast, mine, haul, drill) is very
automated/digitally advanced and the comminution teams are in catch-up
phase,” he said.
Still, Metso’s Özer said there was an increasing awareness across the
industry of the importance of instrumentation and control and the lost
opportunities that come with operating a processing plant without them.
“The industry is implementing sensors keeping an eye on equipment and
process responses, such as Metso’s VisioTruck™, VisioRock™, Smart Ear™
and VisioFroth™, VisioPellet™, all controlled by our expert control system
OCS4D™,” he said.
“With an expert system guiding the regulatory control system process,
performance is maximised 24 x 7, only limited by the programmed plant
constraints.”
Metso’s recently introduced Metso Metrics platform is one such system,
collecting data in real time and using it to feed predictive models that keep
unplanned shutdowns to a minimum.
FLSmidth, too, has introduced its own process plant digitalisation tool.
Its SAGwise™ solution optimises the performance of grinding mills through
the application of acoustic sensing and operational parameters to control
feed, speed and slurry density.
The company said it provides an up to 6% increase in production and 3-
6% lower power consumption (lower environmental impact), while reducing
maintenance costs through decreased liner damage by up to 45%. The
company said it recently sold its first SAGwise product to a mining
customer.
Such digital platforms could help with future product development,
according to Metso’s Özer.
“There is a wide acceptance that digitalisation will impact on how we
design and operate plants,” he said. “Metso already has digital twins, ie
virtual models, of its equipment as well as for process plants, allowing
equipment and process optimisation before the plant is built.”
And, from the maintenance and productivity perspective, digitalisation is
moving to the next stage of its evolution.
CEEC said: “Big data/artificial intelligence approaches have developed
rapidly, delivering a wider range of productivity improvement solutions at
sites.
“Progressively, the industry is connecting the steps across the mining
value chain and moving towards the ‘holy grail’ of real-time performance
and product optimisation from resource to customer.”
PETRA Data Science recently applied its big data and AI capabilities to an
iron more mine in Western Australia, which, according to PETRA Technical
Director, Zeljka Pokrajcic, was able to demonstrate the link between the
mineral resource and comminution.
“Using two years of historical data generated by the operation across the
entire value chain, experts at PETRA used machine-learning techniques to
track millions of tonnes of ore from the geological block model through
blasting, mining and haulage, and crushing and grinding. This information
was used to develop artificial intelligence algorithms that predict grinding
plant throughput using only geological features,” she said.
“This information is very valuable to the operation, it now has a
parameter in the geological block model that is an indicator of throughput
that can be to be used to optimise the mine plan and scheduling for
improved throughput and operability.”
Moly-Cop’s Dr Shelley said the advance of digital solutions with sensors
for the processing elements of the comminution circuit could provide a
whole new scale of visibility.
“In this environment, the throughput is maximised and circuit optimised
such that the total energy consumed is energy of comminution,” he said.
Moly-Cop is developing a sensor system for measuring key operating
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APRIL 2019 | International Mining 75