AI: enabling new possibilities in mining

By Nermina Harambasic

The launch of ChatGPT in November 2022 heralded the arrival of artificial intelligence on the main stage in people’s lives.

Since then, generative AI has continued to capture public attention as it expands our personal capabilities through new, easy-to-use tools. The business world has now realised that AI cannot be ignored any longer. The floodgates have opened, and the implementation race has begun.

After decades of development, AI-enabled tools have reached the fast-moving stage at which their application is no longer lending itself to sit-and-wait approach. Businesses waiting for others to make the first move and then learn from their ‘mistakes’ will not be served well.

The introduction and assimilation of new technology to any organisation takes time, for different reasons. Starting with a simple AI application and building internal expertise to adapt technology to the business’ specific needs is a better strategy in this case.

As with any application of new technology, organisations are faced here with two questions:

1. What business applications are the best fit or the most beneficial for the implementation of AI? And…

2. Which AI platforms/tools to select for the application?

To answer these questions, we will first look at AI platforms/tools that have been developed so far, with a specific focus on the mining industry.

AI for mining – the current landscape

Difficult work conditions, remote mine locations, workforce availability (or scarcity) are just a few of the incentives for the application of AI in the mining industry.

Aside from a few early trials and implementations, the sector began its transition to autonomous haulage systems (AHS) in 2008, and advances in AI over the next decade enabled the development of other AI driven tools. Currently, AI applications in mining industry are mostly concentrated in the following areas:

1.           Exploration/Surveying/3D Mapping

2.           Ore/Waste/Water management

3.           Autonomous and remotely operated equipment

4.           Maintenance/Performance/Safety

Some of the more general business areas which can also benefit from AI-driven products applicable to mining include: supply chain, HR and market intelligence functions.

The following lists of companies which have developed AI-based tools for the mining industry is based on publicly available data. Although the list is not complete and will continue to evolve, it is a good start in understanding of the AI landscape in the mining industry.

1. Exploration/Survey/ 3D Mapping

1.1. Earth AI

Vertically integrated metals exploration company using AI to locate ore deposits, identify drilling target location with the intent to expand its mineral exploration expertise on other planets and asteroids.

1.2 ALS Goldspot

Data-driven mineral exploration and mining company with AI discovery focusing on computer vision image analysis for logging, modelling of mineral deposit, including its size, shape, grade, structure, and location. This information is used to make informed decisions about mining and processing operations, including mine design, resource evaluation, and decision-making related to investment and production

1.3 KoBold Metals

Is making exploration a repeatable science through comprehensive data aggregation, geoscience excellence, and artificial intelligence. Building the world’s largest collection of geoscience information. Using AI systems to interrogate data to model the sub-surface.

1.4 Kore Geosystems

Empowering geologists and mining professionals to extract more value from their data and use it to support decision-making across the mining industry. Technology includes core imagery, geologist-centric visual core logging software, and AI tools to automate various logging tasks.

1.5 OreFox

AI-based tools supporting remote geological data analysis using high resolution satellite images and advanced mapping software. These tools automated data collection and analysis while providing additional data analysis to exploration teams.

1.6 Newtrax

Mining data platform for 3D mapping, locating, evacuation and rescue management and other health and safety risk reduction solutions, such as collision avoidance, identification of training needs and equipment location. Now part of Sandvik.

1.7 Exyn technologies

Pilotless technology that delivers high-fidelity 3D data/ mapping, adaptable for custom sensor integrations to overlay a variety of readings, such as radiation, gas monitor, IR, heat maps, chemical detection, convergence monitoring, and more.

1.8 Minerva Intelligence

AI decision support tools for climate risk, mineral exploration and mining. Their products include tools used to understand and evaluate drill data to pinpoint superior drill targets, geometallurgical domains, and more through 3D modeling.

1.9 DroneDeploy

Uses aerial data to increase the efficiency and accuracy of stockpile management, inspections, and excavation. Measure stockpiles more often for a fraction of the cost. Visualise and compare site conditions to plan to estimate production. Conduct regular equipment and infrastructure inspections.

1.10 GeologicAI

Company uses proprietary core sample scanning hardware and AI to help geologists eliminate guesswork and improve workflow. AI tools make the process of analysing data more time-efficient and accessible. Manual data entry is replaced with AI.

1.11 DataRock

Data Platform sets the standard in secure, scalable, accurate and cost effective AI-augmented geological image processing, extracts valuable geotechnical and geological information from images, video and point clouds. After imagery is processed relevant data can be exported to client’s workflows.

1.12 Eureka Maps

Geospatial mapping technology empowers mining and exploration enterprises to locate deposits, irrespective of their depth or exposure. This technology facilitates targeted area searches, which Eureka says leads to a 98% reduction in the exploration footprint, thereby mitigating risk, cost, time, and financial expenditure.

2. Ore/Waste/Water Management

2.1 Life Cycle Geo

Provides broad range of services in the areas of geology, geochemistry and the data sciences, across the project lifecycle. Develops an advanced, site-specific understanding of geologic material and mine water characteristics using unsupervised and supervised machine learning methods, employing rock assay and water quality, with end goal of optimised mine material and water management.

2.2 O-Pitblast

Technical services and solutions directed to the optimization of rock blasting, including AI powered blasting guide that calculates drill and blast parameters using industry rules of thumb that helps plan main blast parameters, predict safety issues, operation results, vibration measurements, explosive energy.

2.3 Tomra

Automated ore/waste sorting systems. Although ore/waste/construction material sorting is not yet driven by AI, their wood sorting applications are.

2.4 OffWorld

Swarm robotic mining systems enable intelligent multi-robot operations for Earth and space applications. The Surveyor, Excavator, Collector, and Hauler robots are part of the Swarm Robotic Mining (SRM) excavation squad, their full potential is maximized when combined to perform complex mining functions.

2.5 Weir/MotionMetrics

Particle size analysis products for shovels, conveyor belts, haul trucks, and in a portable format that neither interrupt production, nor require reference scaling objects. Monitoring systems for shovels, loaders, and haul trucks includes missing tooth detection, tooth wear monitoring, particle size analysis, volume monitoring, and boulder detection.

2.6 MineSense

Provides detailed ore characteristics and classification at the extraction face. Reduce both ore losses and waste dilution at the front end. Creates better routing decisions through the precise definition of ore grade at truck level. Optimises blasting, mine planning, stockpile blending.

2.7 IntelliSense.io

Increases efficiencies across the mining and ore processing stream. Tracks and predicts both the metallurgical and physical properties of the material and their effect on the process in real-time. Provides granular knowledge of the material and metal accounting and associated uncertainty across the full value chain.

2.8 Hexagon

Provides surveying, design, fleet management, production optimisation and collision avoidance capabilities in a single, life-of-mine solution, from planning, operations and safety to enterprise intelligence and reclamation.

2.9 Airth

Provides solutions to maximise mine value chain efficiency, including mine scheduling designed to provide value-driven mine schedules, and a data platform that correlates planning, operational, and processing data. Advanced analytics drive improvements in mining operations, tools to tie planning and operational results to the financial model, and manage real-time production and short-term
plans.

3. Autonomous and remotely operated equipment

3.1 Sandvik

AutoMine is a product group for autonomous and remotely operated mobile equipment. It includes AutoMine Underground and AutoMine Surface Drilling product sub-groups.

3.2 Komatsu

Autonomous haulage system, including DISPATCH-optimized truck assignments that result in measurable operational efficiency. AHS helps increase truck availability, boosts uptime, maximises resources

3.3 ABB

Autonomous remote charger robot automatically detects boreholes and fills them with explosives and detonators without the presence of humans..

3.4 Epiroc / ASI Mining

Autonomous haul truck solution that is interoperable and scalable regardless of the original equipment manufacturer.

4. Maintenance/Performance/Safety

4.1 Norda Stelo

Predictive maintenance of static assets. This platform merges the data gathered during asset inspections and maintenance with human engineering knowledge, which will lead to machine learning models to improve the precision of predictions.

4.2 HikVision

Ensures workforce compliance with safety regulations, helping users conduct continuous monitoring in critical areas. Assists in predicting operational failures with intelligent video analysis including incidents such as temperature anomalies and fire hazards. Provides first line of perimeter protection to prevent intrusions.

4.3 KorrAI

Geotechnical risk, including monitoring of open pit slopes, tailing dams, waste dumps, mining areas, infrastructure, access roads, and production facilities. Monitoring of water quality, runoff, soil moisture.

4.4 IBM

Offers mine operators user-friendly real-time dashboards and reports with a complete overview of their production assets’ condition, including expert recommendations to enable faster repairs and the elimination of unnecessary maintenance.

4.5 Tomorrow.io

Weather intelligence for mining that provides real-time monitoring of air quality, monitors access road conditions to avoid weather related risks. Schedule blasting times according to optimal weather conditions in order to effectively disperse pollutants. Provides early warning system for risk of floods.

4.6 Interknowlogy

Operational risk management and mitigation tools, such as proactive traffic management to enhance safety, automation of trigger warnings for natural hazard events, improving safety and wellness performance, including transportation of personnel and material to remote mine sites.

5. Other/General

5.1 IBM Supply Chain

Enables proactive disruption management through smart alerts and real-time insights, intelligent dashboards, KPIs and end-to-end supply chain views. Offers an intelligent collaboration platform with AI Watson as an expert as advisor.

5.2 Akkio HR

Explore, visualise, and predicts employee retention and attrition.

5.3 Oracle HR

Optimise HR processes. Improve productivity, ensure compliance, and meet organizational goals by hiring, engaging, and working smarter.

Some additional AI-driven HR platforms can be found here.

Next steps

The AI adoption process in mining has already started, mostly by the major miners. However, AI can do a lot more to help automate the mining industry, improve design, optimise material flow, train and assist machine operators, and improve operational safety and the performance.

Understanding how AI can benefit the mining industry will require a collaboration platform, bringing together miners, system integrators and AI developers. This platform will facilitate a deeper understanding of AI capabilities on one side, and the problems the industry needs to solve on the other, so that both questions highlighted at the beginning of this article can be addressed.

As all major decisions start at the board of directors and the CEO/VP level, here is an opportunity for this generation of decision makers to create such a collaborative platform and help transform the mining industry.

Nermina Harambasic is an automation engineer. She is the Founder of O-MOD, and a capital project oversight/advisory/management consultant. This article is based on a blog post which was first published on Medium in August 2023