o3 BLOG | Trends
Artificial Intelligence in Mining
AI is increasingly being used in the mining industry to optimize processes, improve decision-making, extract value from data, and increase safety. A well-executed AI implementation strategy can prevent the following:
- Loss of revenue
- Bottlenecks and downtime
- Change risk
- Safety hazards and health risks
While AI provides numerous advantages in mining, it is a relatively new technology and there is continual innovation within this space. Over the past decade, the mining industry has made vast technological advancements to boost productivity. Many large scale mining companies have already begun or are in the process of their digital transformation, most notably through investments in autonomous and IoT-based technology. Although some large scale operations are adopting innovative technologies, many are still lagging behind.
The continuous use of manual and cabled readings over wireless systems connected to digital mining assets is a clear signal of the prominent change-aversion within the industry. Some barriers to new technologies like wireless readings exist, such as low funding due risk-aversion.
We’ll look at how the most forward-thinking mining operations are utilizing new technology and AI to stay ahead of the competition, and how adopting these technologies may make mining operations safer, more productive, cost-effective, and have less of an impact on the environment.
Automation in Machinery and Mining Vehicles
The technology behind mining trucks that operate independently has been around for about two decades. Autonomous vehicles revolutionized mining because they allowed humans to connect with and control machinery remotely. As a result, they’re suitable for use in underground mines and other locations where employee safety may be at risk. The majority of self-driving mining machines are semi-autonomous rather than fully automated, which means in some instances they still require human assistance. These subterranean excavation trucks are made autonomous by equipping them with remote-controlled tools, sensors and cameras, which allow users to conduct testing, gather data, and view the surrounding region from afar. Currently, the focus has changed away from the original autonomous mining trucks and toward developing an “autonomous mining system,” which can perform tasks automatically or with limited external intervention, allowing for the potential for full automation through robotic technology.
Machine Learning for Resource Extraction: Detecting Deep Mineral deposits
Mineral resources provide key materials for commerce in the Canadian economy, especially critical minerals with a limited or unreliable supply and high demand. As large, near-surface mineral deposits decline around the world, mining and exploration companies must develop new approaches for detecting economically viable deposits at significant depths. However, due to limited existing geological data and the limitations of the geophysical technologies employed to collect it, excavating from smaller ore deposits can be difficult. Without resorting to time and resource-intensive methods, machine learning can aid in the development of improved models for the prediction of rock type and economically viable mineral deposit areas for extraction.
Improved Safety and Work Conditions
Faster decision-making is required to create a safer workplace for frontline mineworkers. AI can identify process failures and avoid accidents and injuries by using real-time quality data and analytics. Mine managers will still need to receive additional training to prevent accidents, however, as we move closer to full autonomy, the need to expose workers to high-risk environments will decrease significantly. Further, mining operations can deploy self-controlling machinery to avoid placing their workers in danger by making data-driven decisions.
AI allows for more accuracy during excavation. By mapping out landscapes using data and other insights, AI can help avoid costly mistakes. Pattern matching and predictive analytics are combined with AI, to make more precise predictions. Some organizations employ artificial intelligence (AI) and machine learning (algorithms that develop over time) to detect the size and grade of a mineralization, dramatically reducing human error.
More Sustainable Operations (Reducing Carbon Footprint)
Creating sufficient ventilation in an underground mine is an energy-intensive process. Energy output can be predicted using AI and machine learning which can improve automatic ventilation system modifications, reducing the amount of energy used by a mine site. Another growing trend in the mining industry is the use of drones and computer vision-based machine learning to provide continuous monitoring of underground operations, and their impact on the environment.
O3 Mining implements the latest technology available to the mining industry and is committed to ongoing R & D and innovation. With the support of machine learning and artificial intelligence, we have identified many targets on our properties in Québec, which have led to positive drill results, further supporting our confidence in the size and quality of our mineral deposits. The adoption of AI and machine learning is just one of the steps we are taking to improve exploration and mining processes. Artificial Intelligence offers significant financial, safety, and environmental benefits to the mining industry and we look forward to incorporating machine learning technologies to further support our commitment to delivering long-term value to our shareholders.
O3 Mining is a Canadian Junior Mining company that delivers superior returns to its shareholders and long-term benefits to its stakeholders. To learn more about our ongoing projects and investment opportunities, book an appointment with our executive team today.
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