The mining industry continues to practice using ‘operational silos’ where different parts of an organisation work in isolation to achieve goals that only affect themselves. While this may keep costs from getting out of hand for their narrow segment of the mining process chain, it can have devastating effects on the overall bottom line. This issue is commonly ignored as, very often, different groups have different opinions on what’s important.
Essentially, a mine is a ‘metal manufacturing process’ where what matters most is overall cost per tonne to deliver a saleable product. So why is it so hard to get everyone ‘singing from the same page’, so to speak?
In the mining industry, the customer-supplier (mill-mine) relationship is hampered by two issues: the customer is not clear and consistent in communicating what’s important to them, and the supplier does not know how to deliver it.
Process optimisation can help all the ‘singers’ understand how a better quality mill feed affects overall economics. Take blasting. Blast fragmentation can strongly affect mill throughput – particularly for autogenous or semi-autogenous grinding circuits. Finer blast fragmentation can increase mill throughput by 20 to 30% or reduce the specific energy requirements (kW per tph) by 30%. Although changes in blasting practices can increase drill and blast costs by up to 50%, they can reduce mill operating costs by as much as 4 to 10 times. (See the first article in this newsletter on how mill throughput can be improved.)
SRK can perform benchmarking reviews of existing operations and provide clear indications of the benefits of such a process optimisation study. This benchmarking can involve the use of modelling and simulation tools to examine what-if scenarios and show the effect of changes upstream on downstream performance. Such simulation results can justify making operational changes as they can estimate the potential for efficiency gains.
It is also possible to include estimates of plant performance (tph, $/t, kWh/t, recovery, concentrate quality, etc.) in the resource block model. These tools can be used to improve the mine planning/scheduling process and provide a more accurate estimate of plant production.
