Tag Archives: Artificial Intelligence

Orica to further optimise blasting and mine-to-mill initiatives with FRAGTrack Crusher

Comminution of minerals, IoT, Mineral processing, Mining equipment, Mining services, Sustainable mining, , , , ,

Orica has announced the release of its latest fragmentation monitoring solution, FRAGTrack™ Crusher, an automated pre-crusher fragmentation measurement tool delivering, it says, operational continuity in a safe and reliable way.

Based on the success of the existing suite of automated post-blast fragmentation monitoring solutions, Orica has developed FRAGTrack Crusher to meet growing demand from customers for downstream monitoring and optimisation solutions at every stage of the mining value chain, the company said. The technology leverages the latest deep neural network artificial intelligence (AI) framework along with “industry-proven” hybrid 2D and 3D particle size distribution (PSD) processing methods to deliver a fully autonomous adaptive fragmentation monitoring solution at the crusher dump pocket, enabling customers to measure material on the truck during the tipping operations, according to the company.

The company said: “FRAGTrack Crusher provides truck-by-truck PSD analysis of rock fragments during the dumping operation with unmatched accuracy and without impacting operations or productivity.”

The technology delivers constant performance tracking for both the drill and blast operations and the downstream processing functions, driving continuous improvements end-to-end in the mining value chain. When bundled with Orica’s FRAGTrack Conveyor technology in a fragmentation monitoring solution, it enables further analysis of the crusher’s performance and the impact of blasting parameters in a production workflow in real time, according to Orica.

Orica Vice President – Digital Solutions, Raj Mathiravedu, said: “The full adoption of AI technology into our architecture, coupled with our strategic partnership with Microsoft, allows us to expedite the delivery of capabilities that were not previously possible, and FRAGTrack Crusher is an example of how we leverage AI to help deliver intelligence and value to our customers.”

PSD data is provided via a real-time application programming interface and industrial open platform communication unified architecture protocol to drill and blast software and crusher distributed control systems, allowing seamless integration into the existing site operation workflows, Orica says.

FRAGTrack Crusher has already been gaining traction globally in the mining and quarry markets, where it is being used as a critical enabler of blasting optimisation and mine-to-mill initiatives, according to the company. “This signals a significant transformation from the subjective nature of existing manual PSD analysis methods while eliminating the safety concerns of on-bench photography and the extensive time required to manually process and correlate to relevant data sets, including fleet management data to determine the material’s blast of origin.”

In the most recent application of FRAGTrack Crusher in a Tier One low-cost gold operation in Western Australia, it successfully delivered an automated blasting optimisation workflow on site leveraging PSD as a primary key performance indicator to throughput and overall mill performance. The project included installation of a FRAGTrack Conveyor system, post crusher, allowing pre- and post-crusher PSD to be monitored. When combined with a fragmentation improvement process, the FRAGTrack solution enabled a continuous feedback loop that enabled the operation to rapidly optimise blast designs that drive overall project profitability, according to Orica.

Newcrest and Microsoft partner on digital twin and sustainability modelling projects

Automation, Base metals, IoT, Mining services, Mining software, Precious metals, , , , , , , ,

Microsoft has announced a strategic partnership with Newcrest, which will see the mining company adopt Azure as its preferred cloud provider on a global basis, as well as work on digital twins and a sustainability data model.

The two companies are collaborating on programs of work including the use of digital twins to improve operational performance and a high-impact sustainability data model, Microsoft said.

As an industry-leading user of Microsoft technology, Newcrest has migrated all key workloads, including SAP, from private cloud to Azure. Microsoft 365 is deployed across the organisation, as is Teams and Power BI.

Two priority projects are underway, with the first being the creation of a full value chain digital twin at Newcrest’s Cadia operation in New South Wales, which captures operational data spanning the full breadth of the site. Developed in collaboration with Microsoft, Willow and site operational experts, the digital twin displays data from both information technology and operational technology through easy-to-digest 3D visualisations of the mining process, Microsoft explained. This allows operators and managers to make tactical and strategic decisions in real time to improve performance.

A scenario planning tool will eventually be integrated into the digital twin to enable testing of simulated actions against live data before making operational changes in the field. Together with data on other critical operational metrics, such as recovery and costs, this solution will evolve into a full productivity model for each mining site, according to Microsoft.

Microsoft and Versor are also working with Newcrest on a sustainability data model, with the first release due by June 2022. The model is designed to improve sustainability and streamline environmental, social and governance (ESG) reporting. It will also reduce the time it takes to produce annual sustainability reports. Newcrest will eventually integrate a 3D visualisation tool into the data model to better view end-to-end sustainability performance across the value chain.

Gavin Wood, Chief Information Officer at Newcrest, said these platforms create a scaffold for new digital solutions that will provide predictive and prescriptive insights to help the company optimise operations.

“When you think about how big and complex a mine site is, particularly in regard to the processing done on site, how much energy and water it consumes, the ability to use the full power of AI to provide actionable insights across the value chain is going to unlock so much value for us,” Wood said.

“This is key to our broader ambition to use technology as an opportunity to build on our successes in safety, sustainability and efficient mining.”

He added that having Microsoft as a strategic partner delivered an important advantage for Newcrest.

“I’m a big believer that when it comes to technology – and I’m talking about all technology, not just the IT world – complexity is the thing that kills you,” Wood said.

“It’s better to have simpler architectures and technology portfolios with fewer partners, where you have deeper partnerships and you work closely together, and benefit from the integration that comes with this approach.”

Newcrest’s strategic partnership with Microsoft has been forged with that in mind, Microsoft said.

Microsoft’s global cloud, Azure, now supports the company’s operations around the world. Newcrest is also exploring how it can use Microsoft’s Cloud for Sustainability, which is designed to record, report and reduce carbon emissions through actionable insights.

Brett Shoemaker, Director of Sustainability, Microsoft ANZ, said: “We are proud to work with Newcrest to harness the power of technology to build a more sustainable future, reducing greenhouse gas emissions, conserving energy and water, and driving change.

“You can’t manage what you can’t measure, so data and AI are keys to success. If we can get insights to the right people at the right time, and use data and AI to automate responses where it makes sense, we can impact environmental sustainability. That’s at the heart of Microsoft Cloud for Sustainability.”

Working with Microsoft and Versor, and leveraging Azure and Power BI, Newcrest has already developed data models that are being used across production, safety, cost and people processes, and which will inform the sustainability data project.

IMDEX bolsters real-time rock knowledge with Datarock investment

IoT, Mineral exploration, Mineral processing, Mining mergers and acquisitions, Mining services, Mining software, , , , , , , , , , , , ,

IMDEX says it has boosted its rock knowledge capabilities with a deal to acquire an initial 30% stake in image analysis company Datarock for A$5.5 million ($4 million).

Datarock has, IMDEX says, extensive geoscience and data science expertise that has led to the development of a cloud-based platform which applies artificial intelligence and machine learning to automate the extraction of geological and geotechnical information from core imagery, videos, and point clouds. This automation creates high value datasets that drive efficiency within mining operations, IMDEX added.

IMDEX has an exclusive option to acquire the remaining interest in Datarock over the next four years in a two-tranche process, subject to Datarock achieving agreed strategic milestones.

The partnership will enable IMDEX and Datarock to work together to accelerate growth plans, including product development and market expansion, it said.

IMDEX Chief Executive Officer, Paul House, said Datarock’s existing and planned products complemented IMDEX’s existing software including ioGAS™, aiSIRIS, MinePortal, and its cloud-based platform IMDEXHUB-IQ™, and strengthened the company’s ability to deliver real-time rock knowledge answer products.

“The Datarock team and the products they have built are strongly aligned with our strategy, our existing product offering and our value proposition for clients,” House said. “Data collected by geologists and engineers inform operational and financial decisions throughout a mine’s life cycle. This data is commonly collected manually, which is slow, laborious and can be prone to human error. Datarock aims to eliminate this error and deliver high quality and auditable data that provides value for the entire life of the mine.

“We are looking forward to working with the Datarock team. Its members are experts in the field of geoscience, data science and AI, and like IMDEX, have a drive for developing technologies to solve the mining industry’s biggest challenges.”

Datarock is an Australia-based mining technology company servicing the global exploration and mining sector. It is owned by two private companies, Solve Geosolutions Pty Ltd and DiUS Computing Pty Ltd. Solve Geosolutions and Datarock recently combined to both operate under the Datarock name. Solve is one of Australia’s leading geoscience machine learning and data science consulting businesses. DiUS is an Australia-based consultancy that helps organisations build the future using its expertise in AI, machine learning, IoT, cloud computing and product development.

Datarock’s products are applicable across the mining value chain, from geotechnical analysis of drill core during drill out, through to the mining and extraction phase, according to IMDEX. It has an existing customer base with major mining companies globally.

Datarock Chief Executive Officer and Director, Liam Webb, said there were clear synergies between Datarock’s products and several of IMDEX’s offerings.

“By working together, we will add considerable value to both companies,” Webb said. “When we started seeking investment our primary goal was to align ourselves with a company who saw the future the same way we did and could help us achieve our goals. I feel by entering into this agreement with IMDEX, who we believe are one of the world’s leading mining technology companies, we have achieved this.”

Matrix Design Group leverages AI and machine learning in lastest collision avoidance platform

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Matrix Design Group has introduced its new OmniPro® collision avoidance system for surface mines, which uses Visual Artificial Intelligence (Visual AI) and machine learning to enable line-of travel, crosswalk and blind-spot pedestrian and vehicle alerting for mobile equipment.

Consisting of up-to-three 120° field-of-view cameras, the OmniPro system works without personal wearable devices or tags. OmniPro not only “sees” and identifies people and hazards, alerting with visual and/or audible alerts, it also photographs and reports zone breaches, according to Matrix. OmniPro is an application of the Matrix technology that received the 2020 NIOSH Mine Safety and Health Technology Innovations Award, which was presented in September at MINExpo 2021.

“Operations recognise that prevention is the most effective strategy for combatting mining accidents,” Brian Jones, Vice President of Business Development, said. “Those with safety initiatives will see OmniPro’s Visual AI system as an indispensable tool in helping protect workers and equipment.”

Through its Visual AI object recognition technology, OmniPro has been taught to identify and report on a library of “objects” including people, vehicles, equipment, stop signs and pedestrian signs.

The user can select what objects will be included, whether to integrate with the machine or operate as alert-only, and whether the alert will be visual, audible or tactile. Additionally, depending on the mine’s needs, OmniPro’s wireless solution can trigger a stop sign, pedestrian light, voice alert or crossing arm. All incidents are recorded and reviewed to provide insights for additional safety training as needed.

OmniPro’s cost-effective and customisable solution can be adapted to match any operating environment through its programmable field-of-view zone grid configuration tool, which enables it to meet the safety requirements of different mines, it said.

“OmniPro is effective on many levels,” Jones said. “Our customers have told us it brings awareness to workers and helps them feel the operation is investing in their safety.”

Position Partners to bring Presien’s Blindsight collision avoidance tech to Australasia

IoT, Mining safety, Mining services, Mining software, , , , , ,

Presien and Position Partners have announced a distribution agreement to expand access and implementation of Blindsight, an artificial intelligence-backed collision avoidance system for industries such as mining.

Unlike other alert systems and safety solutions, Blindsight’s integrated camera and AI software sees, understands and alerts operators to potential hazards, the companies say. The Blindsight system can be installed on mobile plant or fixed infrastructure, anywhere.

“We developed Blindsight because we wanted to create a world where every worker is safe, and every employer is successful,” Mark Richards, CEO of Presien, said. “Using AI allows us to protect workers in the most complex of situations and quantify safety metrics, all at once.”

Blindsight’s pre-trained AI automatically detects people, vehicles, traffic cones and custom objects unique to each work site. With automatic, over the air updates, the system is constantly learning and improving. The system’s in-cab visual, auditory, and haptic alerts immediately notify operators to the presence and direction of dangers in real time.

Through the distribution agreement between Presien and Position Partners, these capabilities will be available in Australia and New Zealand for the first time.

Martin Nix, CEO of Position Partners, said: “Increasing safety around working heavy machinery is of paramount importance to our customers, so we are excited to announce our agreement with Presien and introduce Blindsight to the building, civil and mining sectors in Australasia.

“Feedback from early adopters has been extremely positive, particularly around Blindsight’s automated detection of people without the need of a wearable tag. It is an excellent example of how artificial intelligence can be used to benefit humankind.”

Plotlogic’s precision mining pursuit bolstered with new investor funds

IoT, Mining finance, Mining services, Mining software, , , , , , ,

Plotlogic’s mission to deliver precision mining across the world has been given a boost with A$7.5 million ($5.5 million) of funding from international investors.

Plotlogic’s primary focus is on providing accurate real-time orebody knowledge to enable greater operational efficiency and resource utilisation. Its OreSense® technology has demonstrated its ability to improve health and safety, enhance overall mining operations and deliver tangible productivity gains, according to the company.

Andrew Job, former mining manager and company Founder, recently completed his PhD in artificial intelligence-based sensing at University of Queensland, and has said “Plotlogic’s technology is an exciting development in resource knowledge and forms an important part of our growth as we digitally transform our mining businesses”.

Plotlogic’s most recent international deployment of its OreSense system was to an Anglo American project in South Africa. This comes on top of deployments at BHP and South32’s operations.

The company says it continues to increase its global footprint with imminent deployments to South America, North America, Asia and Russia.

Precision mining with the help of technologies like OreSense have the potential to increase worldwide industry value by $370 billion/y, according to Plotlogic, while reducing carbon emissions and improving the sustainability of mines over their life cycle.

To support commercial expansion, Plotlogic’s team has grown substantially, with the team currently sitting at 30 people, up from only six a year ago. It also has plans to double in size before the end of this year.

LKAB to trial AI-backed XRF drill core logging with help of Minalyze and Sentian

IoT, Mineral exploration, Mining services, Steel and iron ore, , , , , , , , , , , , , ,

LKAB, Minalyze AB and Sentian say they have joined forces in a consortium to develop the latest technology for scanning drill core.

In March 2020, LKAB started a test with the Minalyzer CS drill core scanner where the goal was to improve the workflow for core logging – ie how the results of exploration drilling are analysed. The test led to a permanent installation in Kiruna (Sweden) and expansion to Malmberget where data from the Minalyzer CS is used to help geological logging of the drill core.

The consortium of LKAB, Minalyze and Sentian are now set to take the use of data to the next level when boreholes in LKAB’s deposits are to be investigated. The new artificial intelligence application being developed by the trio will make the analysis much faster, with the time to evaluate a drill core reduced from weeks to minutes, with increased accuracy.

This could see Minalyze’s X-ray Fluorescence-backed CS scanner analyse LKAB drill core while leveraging Sentain’s industrial artificial intelligence solutions to make real-time decisions relating to drilling and exploration activities.

The technology development driven by the consortium will be a world first, changing the entire industry, the companies say.

Jan-Anders Perdahl, Specialist at LKAB’s Exploration Department, said: “With the collaboration, the core logging takes a big step through machine learning and artificial intelligence. The geologist can, at an early stage, place greater focus on the parts of the core that show chemical or other changes. Opportunities are opened up to gain increased knowledge about ore formation processes and alterations in a completely different way than before. One can also get indications that you are close to mineralisation and where it may be located, and thereby streamline exploration.”

The technological leap will give LKAB’s staff increased competence, increased quality in and efficiency of the work, as well as reduced need for other analysis methods, according to the companies.

Annelie Lundström, CEO of Minalyze AB, said: “We are at an interesting time when the hardware to extract consistently high-resolution data from drill cores is available and we can now take the next step and generate value from data together with our customers. In this collaboration, we will develop algorithms that can map rock layers in so-called lithological logs with very high confidence. This can only be done by combining expertise from all three parties.

“The results from our collaboration will forever change how drill core logging takes place everywhere and will result in a more efficient, non-subjective and consistent process.”

Martin Rugfelt, Sentian CEO, added: “We see great power in the application of modern artificial intelligence to data from the mining industry and there is major potential in further combining our machine learning technology with Minalyze’s unique capabilities in data collection and analysis.”

Rio Tinto investigates Heliogen’s AI-backed solar technology to decarbonise Boron ops

Environmental, Industrial minerals, Mine operation news, Mineral project development, Mining services, Power supply for mines, Sustainable mining, , , , , , , , , , , , ,

Rio Tinto and renewable energy technology company, Heliogen, have announced an agreement to explore the deployment of Heliogen’s solar technology at Rio Tinto’s borates mine in Boron, California.

Under a memorandum of understanding, Heliogen will deploy its proprietary, artificial intelligence (AI)-powered technology at the Boron operation, where it will use heat from the sun to generate and store carbon-free energy to power the mine’s industrial processes.

The two companies will begin detailed planning and securing government permits for the project, with the aim of starting operations from 2022. They will also use the Boron installation to begin exploring the potential for deployments of Heliogen’s technology at Rio Tinto’s other operations around the world to supply process heat, which accounted for 14% of Scope 1 & 2 emissions from the group’s managed operations in 2020.

Heliogen’s high-temperature solar technology is designed to cost-effectively replace fossil fuels with sunlight for a range of industrial processes, including those used in mining. At Rio Tinto’s Boron mine, the company’s proprietary technology will use AI to control a network of mirrors that concentrate sunlight to capture energy used to make steam, the companies said. Heliogen’s system will also store the captured energy in the form of heat, allowing it to power night-time operations and provide the same uninterrupted energy stream offered by legacy fuels.

The Boron operation mines and refines borates into products ranging from fertilisers to construction materials and is producing lithium carbonate from a demonstration plant. The site currently generates steam using a natural gas co-generation plant and natural gas fired boilers. Heliogen’s installation will supplement these energy sources by generating up to 35,000 pounds per hour (15.9 t/h) of steam to power operations, with the potential to reduce carbon emissions at the Boron site by around 7% – equivalent to taking more than 5,000 cars off the road. Rio Tinto will also be assessing the potential for larger scale use of the Heliogen technology at Boron to reduce the site’s carbon footprint by up to 24%.

Heliogen’s mission of slashing global carbon emissions by replacing fossil fuels with sunlight, as well as its focus on industrial sectors, made it an ideal partner for Rio Tinto, which is committed to decarbonising its global operations, it said.

Rio Tinto Chief Executive, Jakob Stausholm, said: “This partnership with Heliogen has the potential to significantly reduce our emissions at Boron by using this ground-breaking solar technology, and we look forward to exploring opportunities across our global portfolio.

“Addressing climate change effectively will require businesses, governments and society to work together through partnerships like this one, to explore innovative new solutions throughout the entire value chain. Our work with Heliogen is part of Rio Tinto’s commitment to spend approximately $1 billion on emissions reduction initiatives through to 2025 and our commitment to work with world-leading technology providers to achieve this goal.”

Heliogen CEO and Founder, Bill Gross, said: “Since its founding, Heliogen has been laser-focused on decarbonising industrial sectors, including mining. As a result, this agreement with Rio Tinto is incredibly gratifying.

“We’re pleased to find a partner committed to cutting its contributions to climate change. We’re also pleased that Rio Tinto is exploring our technology to play an important role in helping reach its sustainability goals while dramatically reducing its energy costs. More broadly, we’re excited to take this important step as we pursue Heliogen’s goal of avoiding more than 1 gigaton of CO2 emissions – 5% of the world’s annual total – from the global economy by turning sunlight into an industrial energy source.”

Metso Outotec on ore sorting’s potential ‘revolutionary change’

Automation, Comminution of minerals, HOF, Metallurgy, Mineral processing, Mining equipment, Mining services, Mining software, Sustainable mining, , , , , , , , , , , , , , , , ,

Metso Outotec stands out among the mining original equipment manufacturers for having publicly acknowledged ore sorting is on its radar.

The Outotec business had a relationship with TOMRA Sorting Solutions dating back to 2014 when the two companies signed an agreement that would see the particle sorting company supply Outotec-branded sorting solutions to the mining and metallurgical industry. Metso, meanwhile, has previously disclosed it was developing “breakthrough proprietary technology to address the demand of high throughput accurate sorting”.

Close to eight months after the two companies merged to become Metso Outotec, IM put some questions to Erwin Huber, Vice President, Crushing and Conveying Systems; David Di Sandro, Business Development Manager – Optimisation and Test Labs; and Rashmi Kasat, VP, Digital Technologies, Minerals, to find out the current state of play with ore sorting at the mineral processing major.

IM: Back in November at your Capital Markets Day, there was mention of ‘AI-powered Ore Sorting Solutions’ during a presentation. Can you expand on what this offering might include? What stage is it at in terms of commercialisation?

DDS: Ore sorting is one of the most exciting recent developments in our industry. With improvements in sensor capabilities and adoption of artificial intelligence (AI), this may well become the revolutionary change this industry needs to sustain itself in the face of diminishing grades and orebody quality.

EH: With our ore sorting solution development, we are targeting the ability to deliver complete offerings of hardware and sensor-fusion platforms as it relates to both bulk and particle ore sorting. These platforms would utilise AI to optimise the feed material for the downstream process. Metso Outotec is uniquely positioned to understand and optimise that plant feed stream with deep knowledge and almost complete technology coverage in both the concentrator and tailings processing areas.

We plan to bring new solutions to the market in the short term and continuously launch new technologies to increase capabilities and capacities when the developments are mature enough.

IM: Will these solutions leverage existing tools within the Metso Outotec product offering? Will they make use of existing agreements with other companies (for instance, the agreement with TOMRA that Outotec previously had in place)?

EH: Metso Outotec carries out its own development of these solutions, and some partnerships are part of it once sensoring and analysing different minerals and elements are not possible with a single or only a few technologies. Mining and concentration are becoming more and more a digital world where breakthrough innovation is finding its space towards efficiency and sustainable possibilities. Smart systems will enable improved equipment uptime, efficiency and remote diagnosis of process and maintenance, and will be the bonding element between our traditional offering portfolio and new technologies.

IM: Previously Metso has talked about the development of a bulk sorting solution: do these ‘AI-powered Ore Sorting Solutions’ fit into that category, or are they more particle sorting solutions?

EH: Bulk ore sorting enables material selection at high throughput flows and particle technology is limited by capacity while bringing the benefit of high accuracy on selectivity.

RK: Bulk sorting is in its early stages in industry and no single sensor can determine minerals content across all ore types and mine sites. This is where AI algorithms play a significant role in ‘self-learning’ ore characteristics, mine site by mine site. It also provides great opportunities to do sensor fusion and more accurately determine the minerals content based on outputs from various sensors and sensor types. AI augments our expert’s tacit knowledge and provides a more reliable way over time to analyse big data generated from online mineral analysis.

IM: Where in the flowsheet do you envisage these solutions going?

EH: The earlier we can remove the gangue from the flow stream, the better our energy efficiency will be by reducing the volume of waste material that is processed by downstream equipment. Deposits in advanced development allow for in-pit backfill bulk ore sorters that may be deployed behind mobile in-pit crushers, or before the coarse ore stockpile where backfilling is not an option. There are several pre-concentration technologies that can be applied at each stage of mineral processing and the ideal operation should combine those tools to remove the liberated gangue at multiple stages of the processing plant in order to achieve the most sustainable process (ie bulk/particle ore sorting, selective breakage, coarse flotation).

IM: Will the benefits of your solution be felt beyond the crushing and grinding stage? Do you intend to use the data generated from the ore sorting solutions to benefit the whole downstream flowsheet?

DDS: One of the benefits of ore sorting is more efficient removal of waste from the process feed. Under certain circumstances, this also means removal of deleterious material which otherwise would adversely affect downstream process performance such as flotation recoveries. In these cases, the downstream benefits are intrinsic. The key would be understanding the geometallurgical mapping of all rock types and their mineralogy, so a philosophy of ‘include or reject’ can be applied on a metallurgical response basis. This mapping can be improved with SmartTag™ and GeoMetso™ technologies from Metso Outotec.

EH: The ability to sort, the geometallurgical mapping and metallurgical response obviously feed back into the block model and allow for more options in the mine plan and life of mine resource recovery, for example with the deployment of low-grade stockpiles. This further enhances the sustainability of the mining operation.

IM: Is the market ready for and receptive to such a powerful ore sorting solution?

DDS: As we all know, for good reason, our industry is full of early adopters rather than innovators. Most operations will need to see the technology succeed elsewhere before increasing their uptake of the technology. The initial implementation will likely occur in partnership with customers whose operations need this technology to be economically viable.

EH: The key is to understand the ore variability through the deposit and through the life of mine. Adopting ore sorting as an integrated processing step does not differ that much from testing and sizing flotation circuits, where small changes in ore properties can affect the overall recovery. It is important to understand these changes and how to react to them during operations.

The confidence level in sensor-based ore sorting testing will grow over time. We already see real-life examples where customers report on ore reserves based on lower cutoff grades due to ore sorting.

IM: Anything else to add?

EH: Despite the fact that the concept of ore sorting, and the sensors required to detect the valuable ore from the waste, have existed for several years, if not decades, the implementation of these systems in full-scale operations have been relatively restricted to particular cases with the right kind of orebody to make the process viable. Implementing ore sorting more broadly remains the challenge and requires the dual application of the right sensors working effectively with the right mechanical handling systems to detect and remove the waste stream efficiently and accurately. The skills required to solve these challenges are not just for the traditional mining and mineral processing engineers, but need to include a cross-disciplinary team addressing the issues from all angles.

This Q&A interview was carried out as part of the IM March 2021 annual ore sorting feature, to be published early next month

Robotics on its way to the exploration industry, QR’s Scott says

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Mining has entered a robotics boom as developers take substantial strides in artificial intelligence (AI), use of drones, and data capture and analysis technology that will deliver safety improvements and better managed mines, Queensland Robotics Executive Chairman, Andrew Scott, says.

Speaking at the IMDEX Xploration Technology Symposium, he said that with the development of autonomous haulage and drilling technology, the mining industry had moved through a “trough of disillusionment” around robotics and was rapidly accelerating towards the “plateau of productivity”.

The two-day online conference brought together experts in mining innovation and exploration industries to discuss the latest in new technologies, tools and advanced analytics.

Scott said acceptance of new technologies had been aided by restrictions caused by the COVID-19 pandemic, with the development of some digital transformation projects planned for the next three to five years being executed in three months.

“COVID is a significant accelerator and robotics is no exception,” he said.

Capital was available to fund new and emerging projects and was another clear indicator of a robotics boom, which Scott said would undoubtedly mean more jobs not less.

“There’s a lot of work that’s underway right now to really bring to the forefront a lot of automation and robotics to deal with enhanced data capture and execution of exploration programs and also within the mining environment,” he said in an interview ahead of the symposium.

“In the mining environment, we’ve seen the proliferation of automation in the form of autonomous haulage and autonomous driving, but now we’re seeing all the other ancillary services that are requiring automation and robotic solutions to take people out of danger but also to enable a highly efficient and productive system.

“We’re starting to see some of those capabilities move across into exploration, including the ability to deploy smart sensors in the field robotically, the collection of samples, and the analytical processing of those samples.”

He told the symposium the increase in robotics was aided by a reduction in sensor and computational costs, and, with more tools and technology available, there was increased adoption and acceptance.

“Robots are helping with the dirty, dull and dangerous, and distance challenges,” he said. “Applying robotics can definitely remove people from harm’s way. It can also augment what they are able to achieve by being able to explore in environments where until now we’ve been limited.”

This included in Australia, with areas subject to extreme heat, the high altitudes of the Andes, and subsea exploration.

“Robotics is surfing the wave of AI,” he said. “There’s a huge amount of development and growth in this area. We’ve gone past the AI winter, as they call it, and the acceleration of tools, and the ease of use of those tools is becoming a critical enabler.

“My prediction is that we’re going to see more and more solutions where they’re highly engineered highly capable, robust, highly configurable and easy to use.”