A study commissioned by a challenger to mining’s Autonomy 1.0 hegemony not surprisingly finds the economics of its alternative are compelling. Hopefully, though, it kickstarts a more rigorous and open dialogue on the topic since it appears to have serious implications for mine waste, efficiency, emissions, etc.
Silicon Valley tech company Pronto AI said earlier this year existing ultra-class mining autonomous haulage systems [AHS] were “too complex and expensive to be commercially viable for smaller fleets”.
“That’s where we come in,” the company said. Its low-cost and easy-to-fit offering meant AHS benefits were available to operators running small fleets and/or smaller trucks (up to 136 tonnes payload).
So Pronto – among a handful of small tech companies not aligned to the major mining equipment makers looking to impact the heavy industry automation market – commissioned Whittle Consulting to look at the economics of “autonomous swarm haulage” with smaller mining trucks.
Its study pits tiny vehicles (36t payload) against small ones (90t) to come up with a superior net present value (NPV) argument for smaller autonomous fleets. But the real adversary in the study is human-operated equipment, since there is no ultra-class gear to be seen.
“Autonomy is vital to unlock the benefits of the small equipment case,” the study report says.
The CEO of another Silicon Valley firm, SafeAI, recently suggested it needed to be all hands on deck when it came to meeting demand – and a real need – for more efficient and safer mining and quarrying. Bibhrajit Halder said the incumbents were playing their part in an automation revolution, and in fact had led the way in breaking down regulatory and cultural barriers.
Halder said the mining and construction heavy vehicle sector was a US$3 trillion market.
“About 1.5 million vehicles are out there in heavy industry and every year about half a million new vehicles come in,” he said.
“Only 1200 vehicles are autonomous today.
“The market is so massive at this time and there are not enough players [to meet the market need].”
The Whittle economic assessment is based on “a fictional, but realistic mining operation” with a catchy name, Marvin (may or may not be named after a glum android), and uses “the most powerful mining optimisation software in existence”, the cloud-based Prober program devised by venerable mathematical programmer Jeff Whittle (of Whittle Four-D and Four-X fame).
Whittle Consulting boss Gerald Whittle (son of Jeff) says the update on the company’s 2018 Autonomous Haulage Report is a more rigorous analysis that indicates “bigger is no longer always better” when it comes to automated mining haul trucks.
“The industry has long debated whether mining economics shift to favour smaller trucks when autonomous,” Whittle says.
“We’re excited to publish the first rigorous analysis that demonstrates that for most mines the answer is yes.”
The study report does point out “all mining operations are different and any benefits from using autonomous haulage will vary from case to case”.
Pronto CEO Anthony Levandowski added: “The results also illustrate why our strategy has been centred around making automation accessible to the majority of mines and quarries around the world that aren’t running the ultra-class trucks that the legacy AHS providers have been focused on.”
Levandowski says the Pronto-Whittle study backs his company’s past efforts to show smaller autonomous vehicles can lower maintenance and mine development (narrower benches, steeper pits etc) costs, speed operations, and boost overall fleet utilisation.
