Tag Archives: Artificial Intelligence

How artificial intelligence is revolutionising the mining industry

Automation, IoT, Mineral exploration, Mining events, Mining safety, Mining services, Mining software, Sustainable mining, , , , , , , , , , ,

The mining industry has always been at the forefront of technological progress. From the steam engine enabling coal mining to be profitable, to advanced drilling techniques, innovation has played a pivotal role in improving productivity and efficiency, the organisers of IMARC 2023 say.

In recent years, the adoption of artificial intelligence (AI) has emerged as a gamechanger for mining, allowing for more efficient exploration, taking automation to new levels, generating greater yields, dramatically improving safety, and maximising extraction, maintenance and operational performance.

Improving mine site efficiency

AI-powered systems are being rolled out across mining operations to enhance resource estimation accuracy. By examining geological data patterns and incorporating historical mining data, AI algorithms can provide more precise estimates of mineral reserves. This helps mining companies make informed decisions regarding investment, production planning and resource allocation, ultimately maximising the economic potential of mining projects.

Mark O’Brien, General Manager for Digital Technology & Innovation at CITIC Pacific Mining, notes that AI is already having a sizeable impact within the mining industry.

“In South Australia, mining companies already have access to a massive library of core samples, which are literally centuries of data,” he said. “Using AI-enabled algorithms, we’re now finding resources that were originally missed. The process is relatively similar to the advancement in DNA technology that has allowed criminologists to review and solve old cases.”

Farzi Yusufali, co-Founder of Stratum AI, a company which provides bespoke, AI-driven solutions to help mine sites increase their yields with lower risk, says: “One of our clients noted that their yield predictions in terms of what was pulled out would swing 30% each way on quarter-on-quarter. If you are processing millions of tonnes of copper, that’s a problem. Now with the application of our AI system we found there has been 58% accuracy increase in predictions quarter-on-quarter for the last couple of years.”

AI also offers immense potential in streamlining mining operations and optimising asset management. Through the use of Internet of Things (IoT) devices and sensors, real-time data collection becomes feasible, enabling mining companies to monitor equipment performance, evaluate operational metrics and identify potential bottlenecks. AI algorithms can then process this data, generating valuable insights and predictive models that enhance decision making and prevent unplanned downtime.

Furthermore, AI-powered automation systems can significantly improve efficiency and safety in mining operations. Autonomous vehicles and machinery equipped with AI algorithms can navigate complex terrains, optimise routes and execute tasks with precision. This minimises human error, reduces the risk of accidents and enhances worker safety. Additionally, AI-driven predictive maintenance systems can monitor equipment health, detect anomalies and schedule maintenance activities proactively, maximising uptime and extending the lifespan of mining assets.

AI technology also holds promise in promoting environmental stewardship and sustainability in the mining industry. For instance, AI algorithms can optimise the mine planning process, considering environmental factors such as land reclamation and habitat preservation.

Alex de Jager, the Managing Director of Conundrum Australia, says: “Our technologies focus specifically on creating efficiencies in operations and production, the absolute benefit of all that is not only in the profitability, but it’s in making the mines greener. If you’ve been able to extract more material from what you have mined, you can dramatically lower your electricity and water usage thanks to AI systems.”

de Jager says sensors and remote sensing technologies, combined with AI algorithms, enable continuous monitoring of air and water quality, allowing rapid identification and response to any environmental disturbances. Such monitoring systems help ensure compliance with environmental regulations and promote sustainable resource extraction practices.

Bridging the skills gap

Gavin Lind, CEO of the Australian Minerals & Energy Skills Alliance (AUSMESA), says the rapid advancement of AI presents unparalleled opportunities for the nation’s industries, including mining. For example, he says AI presents opportunities to transform how the most basic tasks are undertaken to make them quicker, safer and more efficient.

“The core function of a mechanic, which is to fix and repair a vehicle, does not change with the adoption of AI,” he said. “With AI, however, a mechanic may not be needed in a garage on a mine site, but can be stationed at a remote operations centre thousands of kilometres away.”

Encouragingly, the mining industry in Australia has already taken some steps to develop digital skills and Lind says AI is also helping address one of the industry’s biggest challenges: attracting the workforce needed to meet global demand. He says mining is at a disadvantage compared with typical city-based employers, as potential recruits can’t just go down to their local mine to see what it’s like firsthand.

He said: “In countries where mining operations are remote, AI can allow us to tell that story from capital cities with the assistance of virtual reality to attract a new generation of workers to the industry.”

Is excessive risk aversion stalling progress?

There is no doubt the industry is inherently hazardous, and risk management is a priority to safeguard both people and the environment.

However, de Jager believes being excessively risk-averse can hinder progress and impede opportunities for growth. In this context, he says, countries with more progressive attitudes towards embracing innovation have surged ahead in AI adoption, gaining a competitive edge in efficiency and cost-effectiveness.

Conundrum Australia creates machine-learning software for the digital transformation of the metals and mining industry and de Jager believes Australia’s reputation for rigorous regulation means it can be a big challenge for a new innovator coming into the Australian market. Conundrum will be presenting at the 2023 International Mining and Resources Conference (IMARC) in Sydney later this year.

de Jager says: “The upside to this risk averseness is that no matter what industry you point to in Australia, the laws that govern that industry are incredibly tight and well thought out, well designed and well developed. Australia is a very innovative country, but it is also incredibly risk averse, and this can be a hurdle to market.”

He believes that by maintaining a low threshold to risk, Australia risks falling behind in the global race towards AI-driven mining solutions. Without embracing new technologies, mining companies in the country may face challenges in accurately estimating resources, optimising extraction processes and mitigating environmental impacts. Moreover, they may fail to capitalise on AI’s potential to create safer and more sustainable mining practices.

Trends in AI

When it comes to trends in AI, one of the most significant applications in mining lies in exploration and resource estimation. Traditional exploration methods can be time-consuming and costly, often yielding limited results. However, as Yusufali says, AI-driven technologies such as machine-learning algorithms and data analytics have transformed the exploration process.

She says there is a range of tools now available to analyse vast volumes of geological data, including historical drilling records, satellite imagery and sensor data, to identify promising areas for mineral deposits.

“With AI, geologists can optimise their decision-making by rapidly identifying potential mining sites, reducing the risk of exploratory failures, and saving valuable time and resources,” she says.

“AI in the exploration process can help mining companies find minerals and resources faster and more efficiently, by identifying patterns and anomalies in the data that might otherwise be missed by human geologists.”

International Mining is a media sponsor of IMARC 2023

Gradiant’s process water solutions to be used at SLB, Rio Tinto operations

Energy minerals, Environmental, Mineral processing, Mining services, Precious metals, Water management, , , , , , , , , , , , , ,

Gradiant, a global solutions provider and developer for advanced water and wastewater treatment, has announced partnerships with SLB (formerly Schlumberger), Rio Tinto and an Australia-based global mining company to, it says, improve productivity and sustainability in the mining industry with a focus on reducing carbon and water footprints.

The projects are in the US and Western Australia for resource recovery of critical minerals and industrial process water.

Gradiant’s collaborations with SLB and the Australia-based global mining company target the recovery of valuable metals such as lithium, nickel and cobalt. The mining of these materials is highly complex and water intensive. Moreover, with increased market demand and environmental regulations, businesses must identify cost-effective and sustainable technologies. Gradiant’s technologies enable sustainable, efficient and economical water governance through end-to-end customised solutions, it says.

Gradiant’s work with SLB integrates Gradiant’s technologies to concentrate lithium solution with SLB’s direct lithium extraction (DLE) and production technology process – allowing reduced time-to-market and environmental footprint for lithium extraction. The solution enhances the impact of the sustainable lithium extraction process by enabling high levels of lithium concentration in a fraction of the time required by conventional methods while reducing carbon emissions, energy consumption and capital costs compared with thermal-based methods, the company says.

Back in October, Gradiant and Schlumberger entered into a partnership to introduce a key sustainable technology into the production process for battery-grade lithium compounds.

For Rio Tinto, Gradiant will deliver a new facility in Western Australia to replace ageing facilities by employing the company’s proprietary RO Infinity membrane technologies and SmartOps Digital AI into existing mining operations. Gradiant has introduced two chemical-free technologies into operations to minimise chemical consumption and waste discharge, it said.

Lastly, Gradiant’s RO Infinity and SmartOps technologies will concentrate complex wastewater from nickel and cobalt production at a new facility in Western Australia for a global mining company, resulting in up to 75% cost savings with lower carbon and water footprints compared with conventional technologies, it says.

Prakash Govindan, COO of Gradiant, said: “Mining is a uniquely complex industrial sector with challenges of remote locations, large volumes of waste, wide fluctuations in water quality and the high-value end-product that demands relentless design and operations efficiencies. The real opportunity for water technology in the mining industry is resource recovery in wastewater coupled with machine learning AI. We are excited to work with the world’s leading mining operators to enter a new era of sustainable resource recovery. This is made possible by Gradiant’s deep understanding of the complex chemistry that underlies the production processes, which is then operationalised by machine learning digital technology.”

Weir Motion Metrics to expand into new state-of-the-art facility in Vancouver

Comminution of minerals, IoT, Mining equipment, Mining services, Mining software, , , , ,

Weir Motion Metrics recently cut the ribbon on a new state-of-the-art facility in Vancouver, British Columbia, that, the company says, will allow the business to better serve customers and provide employees with an innovative workspace for collaboration and development.

On March 13, Weir Motion Metrics opened the site, which is a combined manufacturing, R&D and demonstration space. At 19,725 sq.ft (1,833 sq.m), the new facility is an exciting next step for Motion Metrics, which was born in a business incubator at the University of British Columbia and has grown to a leader in innovative artificial intelligence (AI) and 3D rugged machine vision technology for miners worldwide. Weir acquired Motion Metrics in late 2021.

Mike Funke, Vice President of Weir ESCO, which oversees Weir Motion Metrics, said: “In recent years, there has beena very strong pull from mining leaders for AI-enabled digital solutions. This space will be the new home for Weir’s global centre of excellence for AI and digital solutions. The grand opening reflects our continued commitment to the Vancouver technology and business communities.”

Miners are increasingly focused on improving the safety, efficiency, productivity and sustainability of their operations. Weir Motion Metrics specialises in developing advanced monitoring solutions designed to attain these critical objectives. The facility will continue to support demand and customer needs for years to come, it said.

The company has recently embarked on an ore characterisation trial at a copper mine, leveraging its AI and 3D rugged machine vision technology alongside spectral sensors.

TALPA looking to democratise the data dynamic in mining

Automation, Communications in mining, IoT, Mining equipment, Mining maintenance, Mining safety, Mining services, Mining software, , , , , , , , ,

TALPA Solutions is a software platform provider that aims to democratise the data dynamic in mining, building platforms that, it says, integrate data, decisions and operations effectively, making it easier for mining companies to bring together multiple datasets into one interface with actionable insights.

The ability to do this can set solution providers apart in the mining industry.

Another differentiator for TALPA in this space is its independence. As an entity backed by venture capitalists, it is not tied to one specific OEM or equipment provider. This allows it to look not only at maintenance-related data but also at information that impacts productivity, safety and other on-site considerations. It gives TALPA the freedom to work with raw data and apply various data models directly on its cloud platform.

TALPA’s approach to obtaining on-board machine data is also unique, it claims. Instead of using APIs for already processed signals, it connects directly to the machine’s ECU data via a data logging device and multiple CAN bus interfaces. This approach ensures integration is both quick and easy, and that no potential data points are left behind.

According to Alexey Shalashinski, Head of Business Development at TALPA, such an approach is starting to be recognised by both the mining company community and the OEMs themselves.

TALPA has already partnered with several companies, including GHH and SMAG, to create digital solutions for their end users. For example, the GHH inSiTE Digital analytics solution offered by GHH to various underground mine sites has allowed significant reductions in MTTR (mean time to repair) at several mines owned by GHH’s biggest client in Germany and is now being populated across further sites internationally.

Referencing a project in North America with one of the industry’s leading tyre manufacturers, TALPA’s industrial AI platform has identified productivity improvement opportunities at an open-pit mine site by analysing the carrying capacity of haul trucks in operation, merging it with the tyre diagnostics on these vehicles as well as spatial and other contextual data. On this particular project, TALPA identified there was a potential 5-10% opportunity to increase the average payload on these trucks based on what the sensor data from various systems was saying.

Many mining OEMs claim to provide software solutions with insights on maintenance and productivity, but these normally cover only the product range of particular manufacturers, according to TALPA.

Shalashinski says mine sites find it difficult to get “buy-in” for several systems in the case of running mixed fleets from respective companies and integrating them into the workflow. TALPA is looking to provide that connection to clients so they can leverage all the major benefits that come from pulling data off hundreds of sensors on multiple pieces of equipment.

He concluded: “TALPA Solutions’ unique approach to obtaining on-board machine data, and its partnerships with various companies, make it a valuable partner for the mining industry.”

S5 System tapping AI technology to solve mine asset management issues

Automation, Communications in mining, Equipment maintenance, IoT, Mining equipment, Mining safety, Mining services, Mining software, , , , , , , , ,

Australia-based engineering company S5 System says it is out to solve three common mining workplace problems using artificial intelligence-based technology that takes minutes to install, is affordable and offers rapid payback on investment.

The company has produced three OEM-agnostic asset management products and is advancing research and development to expand the application range of its specialised monitors, sensors and control devices.

S5 System Founder and CEO, Davoud Nassehi (pictured at the recent IMARC event), says the company’s current focus is on growing awareness of three market-ready products – BoltTight, which monitors the tightness of bolted joints; WearMon, wear liners with real-time monitoring; and GETsmart, a ground engaging tool (GET) dislodgement detection system.

They are currently being used on Western Australia mine sites by the likes of Newmont and Mineral Resources Ltd.

Nassehi says he saw an urgent need for the products in his time working in the mining and telecommunications industries.

“Knowing that industries are going to Industry 4.0, I wanted to help them transition from Industry 3.0 and increase the available insights into machinery, plant and feed processes with more realistic data to use in later lifecycle stages,” he said.

“It makes the workplace safer, more secure and more agile, and saves money by allowing users to know what’s happening in their systems, through monitoring and all the good things that are becoming possible by using IoT.”

The wireless products can be fitted to any equipment brand, are suitable for the harshest mining environments and don’t rely on cameras to provide feedback, according to S5. Installation is not dependent on existing infrastructure, Nassehi added.

“They are plug-and-play products,” he said. “They require zero maintenance, are self-diagnostic and the batteries don’t need to be replaced for years.”

BoltTight uses patented technology to constantly monitor the compression force in bolted joints. The washers are designed in standard metric and imperial sizes, and send data using ZigBee wireless technology to a hub that collects data from all the nearby washers and transfers it to the server for analysis, monitoring and data storage purposes.

Any critical failure can be detected, and a real-time audio-visual alarms notify the operation and maintenance team of the exact location of the failed bolt in the plant’s 3D models, according to the company.

“Currently, in the market, there are very few bolted-connection intelligent solutions,” Nassehi said. “Some use ultrasonic or other non-destructive test tools, which are expensive and require manually checking every joint by experienced technicians. There are smart bolt options attempted in the market, however, embedding electronics inside a bolt compromises its specification and integrity.”

“Miners have been looking for a reliable way of detecting GET failures and locating failed parts for years”

Having experienced first-hand the expensive and time-consuming job of replacing wear liners in equipment such as mills, crushers, feeders and transfer chutes, Nassehi conceived the WearMon system.

The non-invasive online condition monitoring system can be directly installed on any type of mining plant liner material such as rubber, metallic, ceramic, polyurethane and polyethylene, it claims. Via battery-powered wireless wear sensors on one of the bolts, it offers accurate real-time and historical wear data; machine learning; predictive, condition-based maintenance; suggested shutdown planning information; accurate inventory requirements; and service forecasts, Nassehi says.

“This system continuously monitors the remaining thickness at each sensor location and reports to the server,” he said. “Information then is processed on the sever and forms a basis to predict the remaining life. If the next scheduled maintenance state is pre-set, then the shutdown date can be entered directly into the software and, if there is a planned shutdown date entered into system then the software algorithm will determine which liners will need to be changed out and predict the number and location of the required material accordingly.

“Alternatively, if maintenance dates are flexible, the system generates predictions with accurate estimate of the serviceable life of the liners and suggests a replacement date.”

S5’s GETsmart system also has sensors at its foundation. They are inserted into a shovel’s GET and shrouds, and connect wirelessly to the in-cab monitor, which actively scans all sensors. When it detects a tooth break, a real-time audio-visual alarm notifies the operator and they can remotely stop the downstream crusher.

Nassehi said unlike competitor options, the GETsmart system doesn’t rely on cameras – which can get dirty very quickly in a mining environment and so impair visibility – for feedback.

“Estimated to cost the mining industry between 1-5% of total production each year, broken GET are a massive global problem for the mining industry,” he said. “Miners have been looking for a reliable way of detecting GET failures and locating failed parts for years.”

Leveraging the intelligent mine concept for improved profitability, sustainability

Automation, Equipment maintenance, IoT, Mining equipment, Mining maintenance, Mining services, , , , , , , ,

The case for digitalisation is clear, according to AspenTech’s Jeannette McGill*, with digitalisation being critical for the metals and mining industry to achieve sustainability and operational excellence in the years ahead.

This is why the more forward-looking decision makers in the mining industry are embedding digital capabilities in their operations so they remain agile, competitive and profitable over the long term, while realising immediate and measurable benefits, she says. Technology providers have responded to the industry’s needs with solutions designed for the mining sector that directly address the dual imperatives of greater business efficiency and enhanced sustainability.

The intelligent mine

In their digitalisation initiatives, today’s operators also know that managing data more efficiently and effectively will be crucial in helping them to meet the challenges they face. Multiple difficulties remain in the way that organisations across the sector manage their data.

Senior mining company executives frequently make tough decisions but, in doing so, they must aggregate isolated pockets of data to generate insights that are relevant and actionable. For data to be available is no longer sufficient. The top priority for effective decision making is for appropriate management of diverse and disparate data sets in a range of locations.

The key is to integrate data and conduct high-level analysis with an understanding of the domain work requirements. Mining companies achieving this will establish what has become known as the intelligent mine. This is a concept that focuses on centralising information from multiple locations and business processes to reveal useful insights. It supports senior level decision making with designed-for-purpose analytical platforms.

Data held in 50 separate systems will not in itself drive operational efficiencies or support sustainable operations. By addressing several issues simultaneously, an organisation is more likely to move towards the intelligent mine.

First, though, businesses must implement automated data gathering systems to capture relevant data from various parts of the mining process and facilities. Second, organisations must have tools that detect bad data because only good data enables good decisions. They must ensure all changes are consistent, correct and improve data processing. Third, the business should assist the mine personnel by providing the capability to integrate data with built-in relevant analytics, so they process and act on insights in a meaningful time frame.

The predictive dimension

To create an intelligent mine, good data is important but only one part of the equation. Organisations must also analyse data in different ways within a context of the problem to be solved with appropriate predictive outcomes.

Companies need to predict the degradation of equipment that, if unattended, will lead to equipment breakdowns and unplanned maintenance, thereby adversely affecting both operational efficiency, reliability, sustainability and safety. Mining is equipment- and infrastructure-intensive with expensive machinery. It demands operational continuity for profitability and sustainability.

Bringing in prescriptive maintenance

Traditional preventive maintenance methods generally fail on the benchmark of equipment availability and performance. Earlier preventive maintenance efforts were unable to deliver sufficient time-to-failure warnings to deliver a significant impact on profitability.

That is where modern prescriptive maintenance plays a vital role. The technology monitors data from sensors on and around the machine to develop intense multi-dimensional and temporal patterns of normal operation, abnormal operation and explicit degradation patterns that precede breakdown. This provides early warnings, using artificial intelligence (AI)/machine learning digital technology to spot patterns that humans will never pick up.

Also surpassing human capability, the technology can assess the health of numerous machines every few minutes. It also delivers early warnings to maintenance teams, often with prescriptive advice on resolution. Facing tough challenges and spread thinly over large sites, workers benefit from warnings. Much of the intense repetitive analytics and engineering help them prioritise what matters most. Maintenance teams with such prescriptive maintenance tools ensure an intelligent mine makes significant progress in eliminating unplanned breakdowns.

Finding a solution

An asset performance management (APM) approach – with integrated prescriptive maintenance capability – ensures mines improve reliability, availability and uptime, simultaneously reducing the considerable cost of redundant equipment.

Operations teams often work on the assumption of lower availability by, for example, installing three machines when they only need two, or purchasing 10 trucks to ensure they always have eight up and running. These practices are now deemed too wasteful and have become unsustainable.

By embracing the most effective technology, mines can achieve benchmark reliability without the need for more people, equipment, or expenditure. Companies can operate at the required production levels and either mothball or switch off redundant equipment. Being able to do this with full confidence it will actually enhance overall outcomes, makes a significant contribution to the bottom line. It reduces emissions and increases sustainability.

Yet to develop an efficient digitalisation strategy, certain components must be in place. All too often, mines try to invest minimally in digital solutions to save money. Without domain-centric AI/machine learning analytics, this limits the reach and value technology can deliver. Successful digital strategies deploy solutions that draw on data from sensors and other sources. Enterprise resource planning systems, manufacturing execution systems, laboratory information management systems and advanced process control systems are all part of the mix, as well as general mine planning and design systems. Machine learning and other data science techniques require timely delivery of available data, so historian technology plays a vital role.

Across the industry, a growing numbers of mines are pursuing an APM approach. Australia-based gold miner, Evolution Mining, for example, has deployed Aspen Mtell software at the company’s Mungari Gold Operations, in Western Australia, to help reduce unplanned downtime and provide information to support productivity improvements.

Greg Walker, previously Evolution Mining Mungari General Manager, said: “Evolution’s Data Enabled Business Improvement program has achieved excellent results in recent years. With this new technology, Mungari Gold Operations can achieve further productivity improvements via increased asset availability.”

Looking to the future

Today’s mining industry is now sufficiently mature that it should fully embrace digital optimisation technologies. Operators that fail to adapt and build a strategy to utilise such technology are destined to struggle against competitors that do. Prescriptive maintenance delivers quick results by improving the use of existing capital assets and eliminating the surprise of unplanned downtime, which directly affects productivity, safety and sustainability.

The industry should understand how scalable prescriptive maintenance solutions add value to assets. This works as well with a single asset, conveyer system, a processing plant, a large mill, as it does with equipment across a worldwide enterprise. The truly intelligent mine empowers mining companies across a vast array of contemporary challenges. From reducing unplanned downtime and decreasing safety risks, to greater operational efficiency, sustainability and increased profitability, this approach will be essential for mining companies to surmount all their challenges in short and longer terms.

*Jeannette McGill is VP and GM of Metals & Mining at AspenTech

Orica ups the fragmentation monitoring ante with FRAGTrack Gantry

Automation, Comminution of minerals, Explosives and blasting, Mineral processing, Mining services, Mining software, , , , , , ,

Orica has announced the release of what it says is its most innovative fragmentation monitoring solution yet, FRAGTrack™ Gantry.

The company calls FRAGTrack Gantry a market-first haul truck measurement solution that combines real-time oversize detection alerts and accurate particle size distribution (PSD) of fragmentation on all models and sizes of haul trucks.

The new product combines the success of the existing suite of automated post-blast fragmentation monitoring solutions – covering the original FRAGTrack release and the release of FRAGTrack Crusher earlier this year – and the feedback from customers experiencing loss of production due to crusher blockage.

FRAGTrack Gantry uses advanced machine vision and machine learning technologies to enable autonomous triggering and processing, without interfering with the haulage operation, Orica claims

It leverages real-time oversized detection through artificial intelligence (AI), with the machine-learning capability applied to real-time detection accomplished within seconds, with alerts syndicated via Fleet Management Systems (FMS), email or SMS for the re-routing of trucks. Operators can also predetermine customisable oversize limits, enabling a reduction in crusher blockage/damage frequency due to oversize material, the company says.

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 Gantry is another example of how we are leveraging AI to help deliver intelligence and value to our customers.”

The reliable and accurate fragmentation information from FRAGTrack Gantry enables customers to optimise their drill and blast operations for downstream processes without impacting the haul circuit operation, Orica says. The addition of a Gantry option complements the suite of FRAGTrack measurement systems currently available for shovel-, crusher- and conveyor-mounted configurations.

Detect to roll out T-Pulse AI-based safety software across Vedanta ops

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

Detect Technologies has announced a global agreement with Vedanta for deployment of T-Pulse, its artificial intelligence (AI)-based workplace safety software.

Vedanta is among the top producers of commodities including zinc, lead, silver, iron ore, steel, copper, aluminium, and oil and gas. The group engages more than 65,000 employees and contractors, primarily in India, Africa, Ireland and Australia.

Managing health, safety and environment (HSE) for such a diverse and spread-out organisation is a massive challenge, Detect says. Driven by its commitment to GOAL ZERO, Vedanta started exploring AI-based solutions to infuse efficiency into this process. T-Pulse was piloted across various industries of Vedanta and was finally awarded the mandate to implement its solution across all Vedanta sites.

Since its deployment, T-Pulse has significantly increased the visibility of workplace risks, leading to early identification of more than 4,000 critical HSE non-compliances, it says.

Daniel Raj David, CEO and Co-founder, Detect Technologies, said: “We appreciate the continued conviction Vedanta has shown in Detect and are excited to enable them in their journey towards improvements in ESG and safety compliance. This is another testament to our mission of driving change through AI and advanced technologies to create a better world.”

T-Pulse, Detect says, offers a centralised and scalable technology stack designed for plug and play deployment. Engineered for risk minimisation and mitigation through actionable insights, T-Pulse has witnessed growing deployments across major caution-intensive workplaces such as construction, petrochemicals, logistics, power, metals, mining, pharmaceuticals and fabrication yards.

Vedanta Group CEO, Sunil Duggal, said: “This partnership will further augment Vedanta’s capabilities on technology-led safety enablement. Detect Technologies’ AI and computer vision solutions will help us enhance our digital safety monitoring across all business units.”

Strayos, Squadrone combine AI and drone mapping nous to optimise Indian mining sector

Automation, IoT, Mine surveying, Mining services, Mining software, , , , , , , , ,

US-based Strayos and India-based Squadrone have announced a new partnership that will combine mine-to-mill artificial intelligence-based solutions with drone surveying to “bring futuristic mines to more sites in India”, Strayos CEO, Ravi Sahu, says.

Squadrone bills itself as being one of the most progressive companies in the application of aerial intelligence in the mining industry in India, providing tailor-made UAV solutions for various applications from mining to drilling & blasting to disaster management. It provides drone mapping, surveying and site digitalisation services to its clients to efficiently manage their site’s day-to-day operations in mining, it says.

Strayos is an AI-based company that uses data from a diverse range of smart tools, edge devices and sensors, including drones, to create 3D digital models of sites. Site digitalisation is further enhanced by Strayos’ end-to-end site AI tools that analyse data from various sources to shape safe and immediately usable key insights, automation and accurate predictions, it says.

This collaboration will pave the way for novel holistic site-level insights, according to the companies. Along with the digital 3D site model created from drone data, users can now leverage Strayos’ Geology Detection AI, Drill & Blast AI and Site Analytics AI, with inventory management. With the addition of these tools, mining stakeholders across numerous site operations will be able to pool and access data from the entire operation, according to the companies.

For instance, blasting engineers will have access to geological data when designing blasts, drillers will be able to accurately predict how their drilling affects the mill’s performance and mine engineers will be able to plan site design with precision based on up-to-date geology and optimised drilling & blasting to reduce load and haul costs.

Brad Gyngell, COO, Strayos, said: “Mining in India is going through a major transformation presently, with drones and AI being the perfect tools to accelerate these advancements. We couldn’t be more excited to collaborate with Squadrone and deliver superior solutions to our customers in India.”

Cyriac Joseph, CEO, Squadrone, Bangalore, India, said: “We pride ourselves on being able to provide the mining industry with the best services and the best products in open-pit mining, drilling and blasting, rock mechanics, mine safety and underground mining. Our boots on the ground and Strayos’ cloud-based Al tools will greatly benefit the Indian mining industry with these specialised applications to facilitate amazing analytics with visual intelligence through drone technology.”

Metso Outotec consolidates, adds to minerals and hydromet digital tools with Sense series

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

Metso Outotec has reorganised its portfolio of intelligent instruments under the Sense series; tools that are designed to solve specific process challenges and enable optimisation for minerals and hydrometallurgical processes.

The market’s most comprehensive portfolio of intelligent instruments is part of Metso Outotec’s Planet Positive offering, the company said. Covering the entire flowsheet, Sense series instruments are suited for both new and existing operations.

“Metso Outotec Sense series includes specialised instruments that provide data for analytics and a better understanding of processes,” Veli-Matti Järvinen, Vice President, Automation product group at Metso Outotec, said. “They utilise the latest technologies, such as artificial intelligence (AI) and neural networks for extra insight. These additional tools for process problem solving and data mining can significantly help improve production within customer operations.”

Included in the series are:

Metso Outotec FrothSense+™ – takes flotation optimisation to the next level with the latest technology and capabilities. It has completely new and redesigned software and hardware. It includes the best features from two legacy systems, FrothSense and VisioFroth™, and adds new capabilities such as froth height measurement, history analysis and AI with deep learning algorithms to detect flotation properties.

The new Metso Outotec RockSense™ product family will take comminution optimisation to the next level with better knowledge of particle size distribution (PSD) on the belt, the company says. RockSense consists of a renewed, two-level offering: RockSense 3D and RockSense 2D, formerly known as VisioRock™. They enable online, continuous on-belt coarse PSD. RockSense 3D also adds new capabilities with AI and deep learning algorithms to detect oversized lumps and foreign objects, for example.

Metso Outotec MillSense™ provides online volumetric charge analysis by direct measurement of charge position. It is now available, together with SmartEar™, as a bundle. SmartEar uses sound to give an additional measurement of charge impacts and liner wear. The bundle fuses acoustic, vibration and force sensor information for improved online analytics of mill operations. This enables new ways of optimising grinding performance, according to Metso Outotec.

In total, Metso Outotec intelligent instruments include more than 10 technologies to optimise the mining process:

  • RockSense 2D: An online particle size analyser system for rocks moving on a conveyor belt that uses 2D imaging technology;
  • RockSense 3D: Accurate, continuous on belt coarse particle size distribution and volume flow using 3D imaging;
  • MillSense: Analysis of toe and shoulder position and total volume of the charge. Enables load control and mill optimisation;
  • FrothSense+: New system with best features and capabilities for froth flotation analysis. It adds AI neural network, multiple regions of interest and froth height measurement;
  • CycloneSense™: An online measurement of hydrocyclone air core data enables measuring and visualisation of their performance.
  • LevelSense™: Using electrical impedance tomography, LevelSense improves the slurry level measurement of flotation cells;
  • CarbonSense™: An online measurement of carbon concentration in carbon-in-pulp and carbon-in-leach applications;
  • CellSense™: Tankhouse monitoring system that automatically measures electrolyte temperature and voltage in individual cells;
  • SmartEar: Online impact analyser uses sound to provide additional measurements of charge impacts and lifter/liner wear;
  • VisioTruck™: Advanced vision technology for estimating rock size distribution of mine truck loads;
  • SmartTag™: An innovative system for open-pit and underground mines to track ore from the mine to the processing plant, and beyond; and
  • VisioPellet™: A pellet size-control system that measures the size of green pellets using proven camera technology installed in a pelletising disc or drum.