Tag Archives: ore classification

NextOre’s in-pit sorting advances continue with development of mining truck sensor

NextOre and its magnetic resonance (MR) technology have made another advance in the ore sorting and material classification game with the development of a new “open geometry” sensor that could enable mines to scan mining truck loads.

The company, in the last year, has surpassed previous throughput highs using its on-conveyor belt solutions, accelerated the decision-making process associated with material sorting viability with its mobile bulk sorter and made strides to branch out into the in-pit sorting space via the development of these open geometry sensors.

NextOre’s MR technology is the culmination of decades of research and development by the Commonwealth Scientific and Industrial Research Organisation (CSIRO), with the division spun out from the organisation in 2017. Since then, NextOre has gone on to demonstrate the technology’s viability across the globe.

NextOre’s MR analysers were first fitted on conveyor belts, yet interest in solutions for in-pit equipment predates the company’s inception.

“A significant portion of the time when CSIRO would show people the technology, they were working on for fitting on a conveyor belt, many would ask: ‘could you possibly put it around a truck somehow?’,” Chris Beal, CEO of NextOre, told IM.

After workshopping many ideas and developing increasingly large prototypes – commencing at the start with an antenna made up from a copper loop and a couple of capacitors – two in-pit solutions leveraging CSIRO’s open-geometry sensor have come to the fore.

The first – a 3-m-wide sensor – underwent static and dynamic tests using chalcopyrite copper ore grade samples in a material feeder setup in 2022, in Australia.

This test work, observed by several major mining companies, laid the groundwork for a bigger installation – a 7-m-wide ruggedised antenna that weighs about 5 t. This can be positioned over a haul truck and manoeuvred using a crane supplied by Eilbeck and guidance systems developed for NextOre by CSIRO and the University of Technology Sydney.

The advantage of MR in a truck load scanning scenario, just as with a conveyor, is the ability to make accurate, whole-of-sample grade measurements at high speeds. Yet, to operate effectively, this system requires significant amounts of power.

“The truck system we are building is between 120 kW and 200 kW,” Beal said. “For people in the radio frequency space, power of that magnitude is hard to comprehend; they’re used to dealing with solutions to power mobile phones.”

For reference, a NextOre on-conveyor system rated up to 5,000 t/h has around 30 kW of installed power. And conveyor systems above 5,000 t/h have 60 kW of installed power.

The idea is that this new MR truck sensor station would be positioned at an ex-pit scanning station to the side of the main haul road at a site and trucks will be directed to ore or waste as a result. The test rig constructed in NextOre’s facility has been built to suit the truck class of the initial customer, which is a major copper mine using 180-t-class and 140-t-class haul trucks.

The first prototype has now been built (as can be seen by the photo) and is awaiting of shipment to the mine where a one-year trial is set to commence.

While pursuing this development, NextOre has also been increasing the scale of its conveyor-based installations.

Around nine months ago, IM reported on a 2,800 t/h MR ore sorting installation at First Quantum Minerals’ Kansanshi copper mine in Zambia, which had just shifted from sensing to sorting with the commissioning of diversion hardware.

Now the company has an ore sensing installation up and running in Chile that has a capacity of 6,500 t/h – a little over 50% higher than the highest sensing rate (4,300 t/h) previously demonstrated by the company at Newcrest’s Cadia East mine in New South Wales, Australia.

Beal said the unit has been up and running since December, with the copper-focused client very happy with the results.

For those companies looking to test the waters of ore sorting and sensing, another big development coming out of NextOre in recent years has been the construction of a mobile bulk sorter.

Able to sort 100-400 t/h of material on a 900-mm-width conveyor belt while running at 0.3-1 m/s, these units – one of which has been operated in Australia – is able to compress the timeline normally associated with making a business case for ore sorting.

“As people can now hire such a machine, they are finding it either resolves a gap in proving out the technology or it can be used to solve urgent issues by providing an alternative source of process feed from historical dumps,” Beal said. “They want to bring a unit to site and, after an initial configuration period, get immediate results at what is a significant scale.”

Such testing has already taken place at Aeris Resources’ Tritton copper operations in New South Wales, where the unit took material on the first surface stockpile taken from an underground mine.

While this initial trial did not deliver the rejection rate anticipated by Aeris – due largely to rehandling of the material and, therefore, a reduction in ore heterogeneity ahead of feeding the conveyor – Aeris remains enthusiastic about the technology and Beal is expecting this unit to be redeployed shortly.

“We now know thanks to results from Kansanshi, Carmen Copper Corp/CD Processing, this new Chilean site and Cozamin (owned by Capstone Copper) that this in-situ grade variability can be preserved, and that mixing impacts directly on sorting performance,” Beal said. “Even so, we have seen really good heterogeneity persist in spite of the unavoidable levels of mixing inherent in mining.”

He concluded: “People want this type of equipment not in a year’s time, but next month. Capitalising the business to put more mobile units out in the world is a priority.”

JP Morgan-backed financing paves way for further MineSense growth

MineSense Technologies Ltd says it has closed a $42 million Series E financing led by J.P. Morgan Asset Management’s Sustainable Growth Equity team that, it says, will allow it to accelerate the commercial deployment of its solutions to drive further growth and profitability.

The funding round includes participation from new investor Evok Innovations, a climate technology and sustainability venture fund, and existing investors including Prelude Ventures, BDC Industrial Innovation Venture Fund, Cycle Capital and Chrysalix Venture Capital.

MineSense has been pioneering data-driven solutions that improve ore grade control, operational profitability and carbon intensity across the metals mining industry. It is doing this through a combination of its ShovelSense® and BeltSense® hardware, a digital platform and geoscientific insight that goes beyond purely grade-based orebody information.

ShovelSense provides precise ore/waste definition and unlocks unique, previously inaccessible data sets at the mine’s extraction face, according to the company. This real-time data enables removal of waste from ore and recovers valuable ore from waste by making smart routing decisions that also reduces the amount of waste processed, production of tailings, and energy, water, and reagent consumption. Metal recovery is increased materially, with production from operating mines increasing by 5-25% on existing infrastructure, according to the company.

The company has initially been focused on copper, with those mining companies that have signed up to use its solutions looking to maximise ore recovery, minimise dilution and enhance operational sustainability.

MineSense says it has tripled revenue over the last year, and was recently recognised as one of the fastest growing companies in North America by Deloitte.

It currently currently serves mines across North and South America, with notable deployments in British Columbia (Teck’s Highland Valley Copper, Copper Mountain Mining’s operation and Taseko Mines’ Gibraltar operation), Chile (Carmen de Andacollo) and Peru (Antamina).

The fundraising will allow the company to expand its coverage globally and extend into other critical metals such as nickel, cobalt, zinc and iron, it said.

Jeff More, CEO of MineSense, said: “We are pleased to partner with J.P. Morgan Sustainable Growth Equity and Evok to scale our ore grade data mining solutions. This funding and strategic support will allow us to continue executing on our strategy of delivering profit enhancement, operational efficiency, and carbon intensity reduction to critical mining operations.”

MineWare integrates mining value chain with new Argus tool

MineWare has introduced an advanced Material Classification module for its Argus Shovel Monitor to, it says, enable mine sites to save millions of dollars by reducing the amount of lost or contaminated ore.

The module integrates precise material information from each bucket, per the mine plan, with any fleet management system to give machine operators, haul truck drivers and processing personnel more accurate knowledge and feedback on the type of material being loaded and hauled, it said.

MineWare Vice President of Strategy and Marketing, Roy Pater, said by knowing upfront what exactly is being loaded at the face, the Argus Material Classification Module improves what material is being moved through the value chain – from pit to plant.

“Argus sets up the entire workflow for better success, providing the right feedback to more people and processes downstream to make informed decisions,” he said. “Shovel operators can now see in real time, via an intuitive, colour-coded display screen, the type and grade of material being loaded, not just the quantity of material.

“Unlike traditional systems that just track material via machine position, Argus precisely monitors each bucket fill and position, classifying the material in real time via a block model overlay on the Argus screen. The operator knows exactly what they’re digging, and where. Argus removes subjectivity when interpreting boundaries and reduces the risk of grade contamination at the dig face.”

Pater said operators no longer need to change grade manually or make assumptions on what they are digging, with the improvement in classification of material upstream having a positive effect on operations downstream.

“Better classification of material in the pit leads to better production output by knowing exactly what’s going in the truck and where it needs to go,” he said.

Argus feeds this material information from the shovel through to the mine’s fleet management system in real time.

Pater said: “The driver then knows exactly where to take the material based on its type and concentration – whether that’s a stockpile, waste point or straight to the crusher for processing.”

Poor stockpile management, ore loss, dilution and grade contamination are common challenges for mining operations, costing millions of dollars annually, according to Pater, with many of these downstream problems and efficiencies in mining directly linked to upstream load and haul processes.

“The misallocation of even a single bucket of high-grade ore can lead to significant monetary losses for mines, either in the pit or in the processing plant,” he said. “At the other end of the spectrum, highly acidic waste material must also be allocated correctly to ensure its safe removal and disposal.”

Pater said the new technology meets the global mining industry’s need for instant, on-demand access to information across a mine that can only be achieved by sharing data in real time between the various mining systems.

“By connecting more of the dots and closing the feedback loop between loading, hauling, dumping and crushing, Argus addresses these issues head on,” he said.

Detailed material classification compliance reports also help geologists, surveyors and reconciliation engineers meet their legal reporting obligations, with easier access to more accurate data on what and how material has been distributed on site, MineWare says.

Argus is an advanced monitoring system for electric and hydraulic loaders, designed to manage payload, mine compliance, machine health and situational awareness.