Tag Archives: Artificial Intelligence

TOMRA taps into deep learning AI network for latest ore sorting advances with OBTAIN

Automation, Comminution of minerals, Environmental, Mineral processing, Mining services, Mining software, Sustainable mining, , , , , , , , ,

TOMRA is looking to leverage artificial intelligence as part of a plan to unlock new opportunities for mining operations using its sensor-based sorting technology.

The company explained: “The ability of computer systems to mimic human thought and decision making to perform tasks that traditionally required human intelligence has played an important role in TOMRA’s sensor-based sorting solutions for decades, automating the process and improving the accuracy and efficiency of the sorters, unlocking value for mining operations.

“Over the years, sensor-based sorting technology has developed, and TOMRA has been using machine learning in its X-ray Transmission (XRT) and Near-Infrared (NIR) sorters for the last 10 years.”

Now TOMRA Mining is opening a new era in sorting with its latest innovation, OBTAIN™, which leverages deep learning to bring single-particle precision to high throughput particle sorting, it says. This solution takes capacity, quality and recovery to a new level, and unlocks value through a wealth of extremely detailed and accurate data for better-informed decision making, it added.

This software uses a neuronal network to identify the properties of each particle accurately and independently of the sorter’s capacity, achieving new-found precision and reliability in detection and ejection. Based on its specific requirements, the mining operation has the flexibility to either enhance the throughput of the sorter while maintaining consistent sorting efficiency or improve sorting precision without compromising the existing throughput.

TOMRA says: “OBTAIN proves advantageous for a fully operational mine by enhancing recovery rates and elevating product quality within the existing throughput. Conversely, in mines with additional capacity, it facilitates increased throughput without compromising product quality. Furthermore, this innovative technology has the capability to unlock untapped value from low-grade ore, waste dumps, or materials previously deemed uneconomical for processing.”

OBTAIN will also add value to a mining operation with a wealth of extremely detailed and accurate data, such as precise online particle size distribution of the feed.

When used in combination with TOMRA Insight, it can provide the customer with detailed reporting on the performance of the sorter and its components to help them optimise the process, as well as enable them to plan for predictive maintenance, the company says.

The OBTAIN software has been developed for TOMRA’s XRT sorters. It will be available on new models, but there will also be an upgrade package available for existing machines, providing a significant opportunity for customers already operating TOMRA XRT sorters, to substantially enhance the sorting performance where it proves to be a suitable solution.

TOMRA has partnered with two customers to test the OBTAIN in real working conditions. The software has been operating for close to 18 months at the Wolfram Bergbau & Hütten tungsten mine in Mittersill, Austria, where it has delivered consistent and reliable performance. The vicinity of the mine to TOMRA’s development team, based in Germany, has made it a suitable testing ground for the first phase, as they have been able to monitor it closely. A second phase of testing to quantify the improvements has been carried out with a trusted long-standing customer in a magnesite application. The successful tests have shown that OBTAIN is ready to transform sensor-based XRT sorting in numerous applications, according to TOMRA.

Hexagon to Augment blast movement offering with AI-based partnership

Explosives and blasting, Mining services, Mining software, Sustainable mining, , , , , , ,

Hexagon has announced it is partnering with Western Australia’s Augment Technologies to help mines maximise ore yield and optimise operational efficiencies by accurately accounting for blast movement.

The partnership will harness a blend of block model data, artificial intelligence (AI), bespoke movement models and measured 3D movement data to create a blast movement solution that enables mines to unlock significant value, Hexagon said.

The Hexagon MinePlan Block Model Manager enables users to simultaneously and effectively design, populate, manage and share block models while centrally managing the amount of sample points, variables and outputs associated with orebody data.

Augment Technologies, meanwhile, leverages a physics engine powered by an AI algorithm to create a Muckpile Block Model™ that is continuously improved through a machine-learning process. The process uses vast amounts of blasting data to ensure that the model’s controlling parameters and simulated physics are as accurate as possible, resulting in a bespoke solution for each customer, the company says.

The collaboration between Hexagon and Augment will allow customers to view and manage the Muckpile Block Model that retains all the data and fidelity of the grade control model, with high accuracy and resolution. Users will have the option of incorporating Hexagon’s Blast Movement Monitors as an additional measure for blast movement and for training the AI model, with transparency into all the data inputs and output, it says. They can also combine operational data with insights from the Hexagon Block Model Manager API to help optimise upstream and downstream processes, all within its geological modelling software platform.

“The implications for the industry are profound,” James Dampney, Vice President, Resource Optimisation, Hexagon’s Mining division, said. “Ore loss, dilution and misclassification cost mines millions of wasted dollars a year. Our partnership with Augment Technologies will help mines to optimise digging locations and downstream handling of ore, resulting in valuable processing efficiency and reductions in energy consumption.

“Customers will save training time and operation time by remaining in the same software used to model their ore. The incorporation of an industry-first block model manager provides auditability and traceability to reduce errors while managers and corporate stakeholders will see time-stamped changes of the block model.”

Augment Technologies co-founder and Chairman, Greg Hardwich, said the partnership was setting a new industry standard in minimising ore loss and dilution due to blast movement, bringing enormous efficiency to mining processes.

“We’re very excited to be working with global autonomous technology leader Hexagon to inject our AI-powered capability to create a Muckpile Block Model, transforming the way blast movements are modelled and measured to create significant value for our customers,” he said. “Through this partnership, Hexagon’s customers will have the opportunity to realise demonstratable reductions in ore dilution, allowing miners to return more consistent grades, and higher tonnages of ore for processing.”

Eramet’s SLN leverages Rockwell control system to improve uptime at nickel furnace

Automation, Base metals, Mine operation news, Mineral processing, Mining services, , , ,

Société Le Nickel (SLN), part of the Eramet Group, has managed to improve uptime at its nickel furnace in New Caledonia by leveraging a new control system from Rockwell Automation.

Processing ores is a complex activity requiring the stable control of the rotary furnaces’ temperature profile and automating operations across different operating ranges. Feed ore introduced into the rotary kiln undergoes calcination as it travels through the length of the furnace. If the calcined product is not at a high enough temperature, product quality is compromised.

Heat is distributed across the furnace with air being supplied for combustion to occur. If there’s too much air supplied, more fuel needs to be burned to maintain the same product temperature, thus decreasing energy efficiency. Excess oxygen must be minimised to a safe level to reduce operating costs and greenhouse gases.

SLN was using an expert system, an existing fuzzy logic controller, designed to automate the operation of the furnace. However, the company faced several challenges with the legacy system, particularly with varying ore content and variable heating values leading to temperature spikes and frequent electrical trips, Rockwell explained. Trips were being caused by high product temperature, which compromises both the quality of the product, and the integrity of the equipment.

“The fuzzy logic was unable to reduce fuel fast enough to prevent trips from occurring and when in manual operation, the operators were not able to react quickly enough,” Leslie Hii, one of Rockwell Automation’s Advanced Process Control Engineers responsible for delivering the SLN project.

“Maintaining the required furnace temperature can be complex and challenging given the number of variables that need to be managed. Fuel type can be oil, coal, or a mixture of the two – each with their unique thermal characteristics. Moreover, the rate of feeding material impacts the furnace temperature and needs to be carefully managed.”

SLN upgraded to Rockwell Automation’s FactoryTalk Analytics Pavilion8 to boost efficiency and performance (image copyright: Société Le Nickel, part of the Eramet Group)

The expert system can only be turned on when the furnace is operating normally and, in the event of any instability, the operators turn it off and take control. The expert system also rated poorly in terms of user friendliness and ease of maintenance, both factors contributing to low system uptime, Rockwell said.

To rectify the situation, SLN upgraded to Rockwell Automation’s FactoryTalk® Analytics™ Pavilion8®. This model predictive control (MPC) solution offers an intelligence layer that sits on top of automation systems and continuously assesses current and predicted operational data, according to the company. It then compares this data with desired results, and drives new control targets to reduce process variability, improve performance and boost efficiency – all autonomously and in real time.

“Using a MPC solution is an ideal example of how Rockwell Automation is using artificial intelligence to drive better operational results by making use of available data,” Hii said. “In this project, we also used machine learning, process knowledge and data to develop kiln models tailored to SLN’s operations.”

The initial phase of the enhanced solution was successfully completed in just 13 months in contrast to the years it took to implement the expert system. It has already been implemented in five rotary furnaces at SLN’s facility. Operators now have the option to minimise the usage of high value fuel oil while maximising lower value pulverised coal during mixed mode operation, Rockwell said.

Mickael Montarello, Process Control Manager, SLN, said: “The MPC application can handle significant variability on ore feed and heating values and prevents trips from occurring, allowing the furnace to stay in operation at a higher rate. The calcined product temperature error was reduced by 6% and the furnace temperature profile variability reduced by 16.1%.

“The average uptime of Rockwell’s MPC is 83% compared with 70% with the earlier expert system. The new solution allows the furnace to stay in operation for longer.”

He added: “Users appreciate the tool’s user-friendliness and flexibility. In the event of a problem with one element of the process, operators can easily intervene on the element in question, while allowing the MPC to continue controlling the other manipulated variables.

“Thanks to this tool, new opportunities for optimising control and management are opening up, which were not possible with the old fuzzy logic controller. Our target for 2024 is to achieve a 90% utilisation rate.”

Testing: the secret sauce of Sandvik R&D

Automation, Communications in mining, Environmental, Explosives and blasting, IoT, Mining equipment, Mining maintenance, Mining services, Mining software, Power supply for mines, Sustainable mining, , , , , , , , , , , , , , ,

Jani Vilenius has his plate full at Sandvik Mining and Rock Solutions. As Director of Research and Technology Development, he is brought into most conversations the business area has about future mining products.

In fact, he even works across the Sandvik Rock Processing business area on occasion, as well as overseeing the design centre in Bangalore, India, which provides “value engineering” across Sandvik Mining and Rock Solutions divisions.

“We coordinate research programs and projects, not products,” Vilenius told IM recently in the company’s newest office in Tampere, Finland. “This may be overseeing the concept machines that we have been producing for several years, as well as technology partnerships with universities.

“We aim to think long term within the Research and Technology Development and Services team, but not too long term as the world is much more agile nowadays than it used to be.”

This means Vilenius’ team has to coordinate all of the activities taking place at the Test Mine in Tampere, provide a ‘steer’ on engineering services and safety processes needed to satisfy today’s and tomorrow’s requirements and regulations, drive cybersecurity and sustainability developments across Sandvik Mining and Rock Solutions in the R&D phase, plus integrate the thinking between the rapidly-expanding Digital Mining Technologies division within Sandvik Mining and Rock Solutions and the R&D team.

And, as of a month ago, his team also coordinates testing at the new Surface Test Pit: a new surface mining test bed being developed 40 km northwest of the underground test mine.

This is all underwritten by the strategic priorities across the business area he primarily works in, as well as the Sandvik group goal of ensuring 25% of revenue comes from products that are less than five-years-old.

To tackle these tasks, he has a sandbox (soon to be two) that all equipment providers would like to have.

The Test Mine in Tampere comes with 6 km of tunnels at a depth of 40 m, with potential to expand further. Positioned beside a glass factory and close to the company’s rock drills factory, this test mine offers the company and its customers everything they need to make strategic business decisions in an environment that can, for instance, replicate the heat and humidity of a deep underground mine in South Africa, as well as the biggest and widest mine galleries the industry has on offer.

This facility – which has everything your typical underground mine has except a daily throughput target – allows the company to run all its underground drills through a rigorous testing procedure prior to customer dispatch. It also allows the various divisions under the business area a chance to test out prototypes, applications and products from time to time.

For the concept machines Sandvik is becoming renowned for, the test mine acts as a place to validate conceptual thinking in a real-life environment, helping engage customers in detailed discussions as to what on-board and off-board technology elements would provide the greatest value to their operations in the near-, medium- and long-term.

The aim is to replicate this process on surface with the Surface Test Pit, providing the catalyst the company needs to reach its ambitious surface drilling market goals over the next several years.

IM sat down with Vilenius to find out how he coordinates all this R&D work, and how day-to-day testing works from a practical perspective.

IM: I imagine your department is inundated with requests from various business lines when it comes to testing. How do you go about prioritising these requests and turning them into an easy-to-follow roadmap that can lead to commercial solutions?

JV: I’ll answer that by taking a step back.

We have a technology focus built on supporting both Sandvik Mining and Rock Solutions and Sandvik group strategy. We then have roadmap items where we try to leverage technologies across many applications. These technology platforms are not always 100% suitable for both surface and underground mining, but there are elements that have similarities. For example, our latest electric concept surface rig uses the same thinking and philosophy used on other concept machines for underground. Of course, there are new elements included, but the platform thinking remains in place.

Jani Vilenius, Director of Research and Technology Development

Based on this, we have different forums and conversations with the divisions and the R&D heads, discussing together where we need to put the focus in terms of testing. There are, of course, differences in sizes of the division with those who invest a bit more in R&D entitled to more access, but we also have to remain strategic about how to capture the market attention within Sandvik Mining and Rock Solutions; knowing when and what to launch, as well as what developments will allow us to achieve the required technology momentum to support both our own internal goals and the goals set by our customers.

With all these technology developments – projects, concept machines, theoretical testing – there needs to be a value proposition. For the concept machines, for instance, there is value from a marketing perspective to showcase Sandvik as a technology leader, but there is also the value of engaging with customers in conversations that, through the actual machine development, allow them to comprehend what the technology may mean for them on a practical operational level.

This rapid agility – which I would say is unique to Sandvik – means we can receive valuable customer feedback on these concept machines before we commercialise certain elements. It allows us to effectively manage risk in a market calling out for technology breakthroughs to solve complex challenges.

IM: How many tests/trials can you have going on at the same time at the Test Mine?

JV: It varies. All underground drill products are tested there before they go out to customers, which puts a lot of load on the facility, while ensuring that when customers get these units, they have been run in an environment similar to a real-life mining operation.

Then we have new prototypes not under my remit that are tested ahead of becoming ‘products’, for example in underground drilling. Then, we have several technologies we test on a daily basis with different types of test benches and subsystems.

The reality is that we would not be as agile as we are without this test mine. It is not easy to go to a customer site and get permission to test equipment as it can negatively impact their (the customer’s) production. The ability to test at our own facility gives us a layer of comfort and confidence ahead of getting to the customer site.

We cannot try or test every application in our test mine, but those scenarios we do test provide real value.

IM: Are there plans to expand the test mine further?

JV: We have a roadmap for our test mine, but this is determined with a cost versus value equation. We don’t want to have empty tunnels without testing going on regularly.

We have all the opportunities to have a third, fourth and fifth level at the Test Mine. We have, for example, recently expanded into a new area to support our underground drill products to allow testing for that. This is a function of the offering getting wider and the need to expand the tunnels to make sure the new products receive the same testing opportunities as the existing ones.

We have expansion plans focused on automation and electrification too.

IM: Speaking of automation, is fully automated (without any personnel involved) battery swapping one of the ongoing projects you are working on?

JV: I can say we have some ideas on this. It is a topic that needs addressing and discussing as automation is coming on all our equipment and all processes in the future.

Fully automated battery swapping testing is, of course, part of the roadmap.

IM: I also understand that your team originally came up with the MineGame tool for modelling battery-electric equipment fleets and infrastructure. What was this designed for?

JV: Yes, this is a tool we needed to develop to support fleet-wide electrification. It is not designed to recommend the type of machine you will get; it is more about how you implement the many electric machines in the mine, what impact this has on infrastructure, how many tonnes we can get out of different fleets, etc.

This modelling tool gives comfort to customers about the value proposition of fleet-wide electrification, while also showcasing how new, developing technologies can be implemented in greenfield and brownfield mines.

This tool – on top of those from Deswik and Polymathian within the Digital Mining Technologies division – will be a game changer for us.

IM: What about the interaction of manual and autonomous equipment? Is this something you are already testing at the Test Mine?

JV: This is an ongoing requirement from customers, who look to always alleviate production stoppages.

It is not an easy challenge to address though. Everyone knows we want to get safe systems in place with a mixed fleet as not all machines are currently automated.

There is obviously a value case for this, and the Test Mine is a good place to test it out.

All I can conclude with is to say we have many tests going on in the Test Mine…

IM: A cheeky question, I know…What will be the next concept vehicle? You’ve set yourself a big challenge with bringing one of these out every year. How are you keeping up with this?

JV: We have smaller concepts, and we have bigger concepts on the table. We need to ensure we develop the technology to get those concepts done in a timely manner and in a way that, as I keep saying, provides value.

Maybe the next one coming out will be one of those smaller concepts.

Then, of course, we have wild ideas for underground equipment further down the line.

IM: The Digital Mining Technologies division is becoming a much bigger part of SMR. Do you see a point where you will start using the day-to-day data coming off sensors on your machines to revamp existing machine designs and come up with new machines?

JV: Yes, this is mandatory for us to do at some point in time. Integrating data from the field and systems into the engineering process is a tried and tested policy in many industries – some of which Sandvik are serving – so we need to do that more in mining.

The big step I foresee on this front is when we truly understand the value of using artificial intelligence in mining. Leveraging these tools will ensure there is a continual optimisation loop that goes throughout our software, hardware and services.

SentianAI

Weir expands digital capability with acquisition of AI-focused SentianAI

Automation, Comminution of minerals, IoT, Mineral processing, Mining mergers and acquisitions, Mining software, Sustainable mining, , , , ,

Weir has acquired Sweden-based SentianAI in a move that, it says, will accelerate its technology roadmap and expand its digital capability to provide enhanced productivity and sustainability offerings to customers. SentianAI is a developer of artificial intelligence-based solutions that optimise performance in minerals processing. Founded in 2016, it is based in Malmö and has a team of software developers and data scientists.

The software that SentianAI develops uses advanced AI algorithms that continuously learn and adapt to the dynamic processes within a mine, providing continuous improvement and optimisation over time, Weir says. Jon Stanton, CEO of The Weir Group, said: “Digital technology has an important role in helping address the challenges of declining ore grades, production efficiency and CO2 emissions for our customers. SentianAI’s advanced software solutions complement and will bridge our Synertrex® and Motion Metrics™ technologies well. Together, these will enable us to provide holistic performance monitoring and optimisation for smart, efficient and sustainable mining.”

Earlier this year, SentianAI and Xore Analyzers formed a strategic cooperation to combine XORE’s XRF analysers, which provide real-time data on metal content, with SentianAI’s machine-learning technology, which adapts to variations in ore properties. The pact, SentianAI says, could allow mining operations to improve their recovery rates and overall efficiency.

IM interviewed SentianAI Founder and CEO Martin Rugfelt last year on its technology and approach. He said it already had a flotation project targeting increase of recovery rate but also the stabilisation of the circuit performance. It was also working on optimising a crushing and grinding circuit with the primary goal of an increase in throughput.

Martin Rugfelt, SentianAI Founder and CEO

When asked how its approach differed to other AI approaches in industry he commented: “A lot of the ‘traditional’ AI systems we see are actually AI toolkits/platforms that are sold on the basis that the customer can create AI logic that they need to solve specific problems without having to understand the detailed data science. Unfortunately, without knowledge of the underlying AI and data science, creating AI for complex systems eg control processes is very difficult. As a result, many ‘traditional’ AI systems are abandoned after purchase. Sentian has taken a different approach. Our SentianController is explicitly designed to optimise control of industrial processes, so when customers buy it, they already have the AI algorithms developed and tested for the complexity of control system optimisation. It is effectively a point solution that means you do not need a large data science team to build and run the AI solution.”

He added on the underlying technology: “SentianAI has worked for many years to select the best algorithms and refine how these algorithms work to deliver a unique AI system that has been designed to control and optimise industrial processes. This is very complex and requires some of the latest technologies in AI to be able to achieve the necessary control. We have also developed a system that can uniquely be applied in stages as data quality improves and operator confidence increases – going from making recommendations to fully autonomous control at the speed our customers want. This allows customers to build confidence before committing to fully autonomous control. We have chosen not to patent our solution as it would have exposed the technology, however, we would argue it is very unique.”

He said the system is also capable of self-adaptation, which can be achieved when you have both the right data and the right AI models. “The AI creates a dynamics model that is made from both historical and ‘live’ operational data. It can then choose the set of control parameters that deliver optimum performance towards a specific goal, eg maximum production for minimum energy usage. In comparison to traditional supervisory control systems it adapts to changes in the process. For example, if the process changes for some reason, leading to new data points, the AI incorporates these into its model, new predictions are made, and new control parameter settings are used. New goals can also be set, resulting in SentianController choosing the best control parameters to achieve those goals.”

Humyn.ai and Dundee Precious Metals put out call to accelerate mineral discoveries

Mineral exploration, Mining services, , , , ,

Humyn.ai has partnered with Dundee Precious Metals to launch a crowd-sourced open data competition looking to fast track the discovery of mineral deposits.

The competition, which will run until May 2024, is a worldwide call for geologists and data scientists to collaborate with the DPM team and develop innovative ways to accelerate mineral discoveries.

Humyn.ai says: “Mineral exploration currently has a less than 1% success rate globally, in terms of discovering new economic orebodies. One of the challenges, especially on the near-mine data rich exploration environment, is the increasingly complex and multi-layered datasets that geologists need to collect and further integrate with already available heterogenous historical data.”

Dundee Precious Metals sees this challenge as an opportunity to work closely with geologists and data scientists, to share industry, technical and site-specific knowledge in order to collaboratively develop an innovative targeting approach applicable in such an environment, Humyn said.

The Future Explorer Challenge comes with the chance to win up to $250,000 in prizes, as well as the prospect of future closer collaboration with the DPM team, Hymun.ai says.

David Rae, President and Chief Executive Officer of Dundee Precious Metals, said: “We are excited to be launching this innovative competition. While the overall objective is the potential discovery of significant new deposits, we are also targeting the opportunity to work with top innovators – both geoscientists and data professionals – to develop new ways of unlocking the value in our data.”

Humyn.ai Founder and Director, Holly Bridgwater, said: “This crowd-sourced data competition will engage a global community of innovators, many of whom have no experience with the mining industry. We can’t wait to see how people with diverse skills from around the world will contribute to solving a hard problem faced by industry.”

Micromine introduces cloud-based AI capabilities to software suite

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

Micromine has revealed its 2024 release, saying the update comes with new features and enhancements across the company’s entire product suite, further underscoring its mission to deliver state-of-the-art technology to reshape the industry.

Kiril Alampieski, Micromine’s Chief Strategy and Product Officer, said: “Addressing the ever-evolving needs and requirements of our clients is the driving force behind our relentless focus on innovation to ensure the industry can achieve more by integrating technology within the client operational workflows and reducing data errors and productivity bottlenecks.”

Powered by the company’s cloud-native data sharing and collaboration tool, Micromine Nexus, the 2024 release introduced two significant features: Micromine Origin Copilot and Micromine Geobank Panorama, enhancing the company’s exploration solutions.

Alampieski said: “The ground-breaking feature, Micromine Origin Copilot, is poised to revolutionise geological and resource modelling. The cloud-based AI companion can process data categorised or quantified and employs advanced machine-learning techniques to craft thorough and robust models autonomously.

“Micromine Origin Copilot plays the role of a skilled ally, offering a supplementary perspective to support and authenticate conventional resource estimation methods, thereby empowering geologists with greater confidence and peace of mind in their models. This AI journey begins with grade modelling and will be implemented to other features throughout Micromine Origin and the wider Micromine ecosystem.”

Micromine Geobank’s Panorama feature also benefits from AI and cloud-computing assistance, able to automate the labour-intensive task of creating a seamless down-hole image from drill core imagery, the company says.

The company’s three mine planning solutions received updates for the 2024 release.

Micromine Alastri, the company says, expands on its industry-leading battery-electric haulage modelling capabilities. The functionality allows mine planners to analyse, validate and implement robust decarbonisation strategies that describe what the mine of the future looks like in practice.

Micromine Spry evolved with a broader set of tools and industry-leading visualisation to tackle the demands of modern coal and soft-rock mine planning head-on. The updates are designed to provide a better understanding of mine data and more straightforward methods to communicate results.

Micromine Beyond improves strategic scheduling with new pit optimisation and materials management capabilities. The new functionality builds more confidence and certainty when developing life-of-mine plans.

Alampieski said: “Micromine’s mine planning and scheduling tools are engineered to meet the needs of mine planners at each planning horizon and primary mining method. The 2024 release is future-focused, delivering precise and dependable outcomes for today’s mine planners.”

Lastly, Micromine’s mine production, control and fleet management solution, Micromine Pitram, adds significant improvements, making it easier to track shift progress and gain valuable insights, as well as reducing time spent on data extraction and manipulation.

MaxMine talks up data-led emission reductions for open-pit mines

Environmental, Mining equipment, Mining services, Mining software, Sustainable mining, , , , , , , , ,

MaxMine has been talking up the potential of data in the quest for reducing emissions and boosting productivity at mine sites, with Tom Cawley, Executive Chair and Interim CEO, arguing that there is still plenty of low hanging fruit for mining companies to leverage on their way to achieving longer-term net zero mining targets.

MaxMine, the company says, is an automated, high-resolution data-based business reporting tool that combines advanced data acquisition technology with AI analysis to fully optimise mobile equipment and operator performance within mining and other mobile equipment-based operations, measuring performance differently and using gamification to change behaviours.

According to Cawley, the average open-pit mine can reduce Scope 1 emissions by up to 10-15% by leveraging data, with MaxMine insights enabling this average open-pit mine to improve productivity while also reducing its carbon footprint by around 15,000-20,000 t of CO2.

IM put some questions to Cawley to find out more.

IM: In terms of your expanding product portfolio, where are clients receiving the biggest and potentially quickest return on investments (ROIs) from your solutions?

Tom Cawley, Executive Chair and Interim CEO of MaxMine

TC: MaxMine has the most extensive dataset in the open-cut load and haul mobile mining equipment sector. We continuously collect data from all sensors across 10 original equipment manufacturers or equipment manufacturers. We have around eight million hours of data, enabling MaxMine to provide unique levels of measurement in the mining sector and equip us with an unparalleled range of potential applications. This enables us to cover a broad scope across all mines while delivering tailored solutions to our clients, depending on their requirements from site to site.

The areas of the highest value proposition for our clients include improved TMM (total material moved) by increased payload, reduced cycle times via driver feedback, improved haul road conditions, enhanced safety and faster incident investigations. Cost reductions are delivered by reduced queueing, off-haul travel, idle time, and improved tyre life. High-resolution data is used to measure the performance of and diagnose mining trucks delivering greater efficiency via engine performance improvements and increased availability via predictive analytics and faster fault resolution.

IM: Although you have a specific product focused on decarbonisation (MaxMine Carbon), would you say the majority of your solutions are providing emission reduction benefits? In terms of adding new clients, is this where a lot of the emphasis is?

TC: Yes, there is a strong correlation between productivity and fuel intensity reduction. The better productivity, the better the carbon intensity.

MaxMine Carbon enables mine sites to measure fuel burn on every asset, every second of the day. MaxMine’s high resolution data allows the difference between business as usual and improved operations to be measured, allowing the fuel saved to be included in the productivity benefits.

MaxMine’s high resolution data is used to:

  • Measure actual truck performance, identify trucks operating below design efficiency and provide diagnostic information; and
  • Provide granular feedback to drivers, which can be used to reduce fuel burn.

MaxMine Carbon isn’t only a separate fuel-saving feature; its capability allows open-cut mining companies to measure, manage and reduce their carbon footprint associated with Scope 1 diesel emissions and reduce operating costs related to diesel consumption.

IM: Where is the development of MaxMine Carbon for underground mining? What timelines do you have around the development and rollout of this solution?

TC: Open-cut mining is a large sector and offers significant opportunities for growth. It is much more energy-intensive at the equipment level compared with underground mining.

MaxMine is growing robustly in this area, and we’ll continue focusing on further penetration in the open-cut mining space in the near and medium term.

IM: Is your market proposition stronger at bulk mining operations than others?

TC: Our market is focused on open cut-mining and larger-size trucks, with a size class greater than 100 t.

IM: Outside of your existing portfolio, where do you see room for growth with different solutions? Are you actively engaged in pursuing such opportunities?

TC: We continue to focus and remain disciplined on our core markets, and our unique selling proposition delivers huge opportunities for MaxMine and the open-cut mining industry.

Orica and Caterpillar set for mine to mill collaboration

Automation, Explosives and blasting, Mineral processing, Mining services, Mining software, Sustainable mining, , , , , , , , , , , ,

Orica’s Digital Solutions segment continues to make major inroads across the mining value chain, with its latest mine to mill initiative set to involve a collaboration with Caterpillar.

Speaking during the company’s FY23 financial results webcast, Sanjeev Gandhi, Orica Managing Director and Chief Executive Officer, said demand for software, sensors and data science continued to increase as orebodies become increasingly hard to find and extract against a backdrop of high commodity prices and increasing ESG obligations and commitments.

“Customers are continuing to seek operational efficiencies across the mining value chain and unlocking the value of digitisation and automated workflows is key to achieving these efficiencies,” he said.

Orica was reporting Digital Solutions’ first full year result, with Gandhi highlighting a doubling of earnings alongside a significant improvement in margins.

“This was driven by growth across all three sub-verticals, namely Orebody intelligence, Blast design and Execution solutions, GroundProbe,” he said.

The Digital Solutions business has been identified as one of Orica’s key growth verticals as it continues to build and invest in the next generation of digital technologies and solutions, beyond its blasting core.

This was witnessed during the company’s most recent financial year, when, among other developments, it acquired Axis Mining Technology, a leader in the design, development and manufacture of specialised geospatial tools and instruments for the mining industry; as well as released what it said was its most innovative fragmentation monitoring solution yet, FRAGTrack Gantry.

Gandhi said: “Innovation continues to be a focus, and this year we have released 15 new digital features, with a focus on artificial intelligence-based solutions to support our customers.”

And, as the industry and Orica’s customers look to solve their biggest challenges through partnership, Gandhi announced its new collaboration with Caterpillar, saying the two companies had signed a memorandum of understanding (MoU) to explore opportunities to integrate key elements of their respective domains.

He explained: “The initial focus will be on the potential integration between Orica’s Rhino™, BlastIQ™ and FRAGTrack™ technologies with Cat® MineStar™ Terrain technologies.”

Rhino (graphic pictured above) is an autonomous drill string-mounted geophysical sensor that measures unconfined compressive strength while drilling. It enhances orebody knowledge in real-time, enabling miners to make better blast planning, improve fragmentation profiles and increase throughput, according to Orica. The technologies in the BlastIQ platform, meanwhile, are, Orica says, designed to deliver economic and operational value individually, with the benefits maximised when integrated in a systemised process. And finally, FRAGTrack is Orica’s state-of-the-art fragmentation measurement tool designed to provide rapid insights into the outcome of blasting processes.

Caterpillar says of MineStar Terrain: “Cat MineStar Terrain uses high-precision guidance technologies, material tracking and more to help your machines work according to plan – increasing efficiency, reducing variability and helping you get the most out of your drilling, digging, loading and grading operations…The solution helps you increase drill capacity, crusher throughput and material accuracy while driving consistency in payloads and bench heights.”

Gandhi said on this MoU: “The goal of this integrated workflow is to provide customers with high-fidelity rock property information enabling significant improvements to on-bench safety, drilling and blasting program accuracy and productivity, along with higher quality blast outcomes that generate enhanced mill performance.”

In the future, the two companies intend to extend their collaboration to optimisation of the entire value chain, from mine to mill, according to Gandhi, who said the approach aligned with both organisations’ ambitions to create sustainable solutions and services that will build the momentum for more intelligent and solution-driven mining ecosystem.

Volvo Construction Equipment leveraging AI to optimise fluid conditions

Environmental, Mining consumables, Mining safety, Mining services, Sustainable mining, , , ,

Volvo Construction Equipment has unveiled its new Fluid Analysis program, tapping into the artificial intelligence realm to identify wear metals and contaminants on equipment or changes in fluid conditions.

The solution expands on its existing Oil Analysis program and encompasses lubricants, diesel fuels, AdBlue and coolants, and comes alongside a 250% increase in global testing capacity, which is equal to 20 labs globally.

The new digitised process – including a cloud-hosted customer portal and Fluid Analysis mobile app – uses AI data analysis to provide customers with easy-to-understand reports and insights with the highest levels of accuracy which can help them make better informed decisions, it says. This allows customers to take preventive actions against contamination and wear, leading to improved uptime and contributing to a lower total cost of ownership (TCO).

Volvo CE says: “AI accelerates the testing process, making analysis quicker and easier. This allows lab technicians to focus on more sensitive testing issues – such as analysing abnormal or critical samples, those of greatest concern to clients – and, thereby, offer more useful insights and recommendations.”

Alongside the expansion of the program, Volvo is partnering with an industry-leading testing provider to, it says, ensure consistency and efficiency on a global level. Besides leading to a significant increase in testing capacity, this partnership will also reduce lead time and simplify the sampling and analysis process.

With 75% of repair costs and equipment downtime traceable to the use of contaminated lubricants and fuels, and up to 65-75% of all bearing failures traced back to to lubrication issues, the importance of effective fluid analysis cannot be overstated, the company says. Through early identification of possible contamination or wear, customers can take proactive action before any unplanned downtime occurs, helping them to maintain productivity and avoid any potential repair costs.

Volvo CE says the expanded program has taken the potential of fluid analysis to the next level, providing customers with efficient and easy-to-understand reporting. The digitised process is quick, straightforward and provides reports to the highest levels of accuracy.

Once a sample is taken from the machine it is sent to Volvo’s newly expanded global laboratory network. Here it is analysed with a diagnosis performed as required based on any trace elements found.

Once testing is complete, reports – along with recommended actions – are made immediately available via the Volvo Fluid Analysis customer portal. This cloud-based platform features a user-friendly interface which presents reports in a highly visual and easy-to-analyse format, the company claims. It is also the first fluid analysis solution on the market which uses AI data analysis, providing an intuitive solution to deliver consistent and easy to understand recommendations.

The process is made easier still with the Fluid Analysis mobile app. This enables users to register their samples from anywhere in the world, quickly and easily access sample reports, and receive notifications should anything require urgent attention.

Routine fluid analysis is proven to reduce downtime by 15%, Volvo CE says.

“Through a more efficient testing process, increased testing capacity and intuitive reporting, Fluid Analysis from Volvo has made it significantly easier for customers to gain the insight needed to take corrective actions which can help avoid expensive repairs and unexpected downtime.”