Artificial Intelligence in the Mining Industry
Mining is the major global industry that produces anything from coal to gold, gone are the days where traditional methods of manual work and animal labour were required and safety was at risk, modern mines are now more advanced, machine intensive, data-driven and quite smart artificial intelligence (AI) ecosystem are being developed around them to provide valuable data that can be used to overcome major inefficiencies in the mining business.
Through Cognitive Science and Design Principles, companies have developed solutions to digitize the plants, machinery and processes with end-to-end data analysis helping the stakeholders right information at their finger-tips in customized and user-friendly dashboards.
- Mineral exploration: Geological, topographical and mineralogical data are processed using machine learning (ML) algorithms and artificial intelligence (AI) to find potential exploration areas, let's not forget Goldspot, a Canadian company that extracts nearly 90% of gold through AI data or Earth AI which promises to explore mineral deposits 50X better than the traditional exploration methods. Using big data and predictive analytics will highlight potential ore bodies with extreme details as well as help improve mineral exploration efficiency in supplying sufficient metals and minerals for present and future generations.
- Mineral sorting and extraction: We are marching into the idea of "man less mines" where it is possible to monitor automated mining activities from a distance. AI-powered automated drill rigs, robots and vehicles are virtually on-the-job 24/7 helping with drilling, blasting, loading, evacuating without break and working with great accuracy and control. Smart sensors are able to separate valuable mineral ores from dirt by colour recognition and use of X-ray and infrared rays resulting in improved efficiency.
- Safety: Yearly 15,000 deaths are not a good number on paper, AI can help to develop a more secure industrial environment where we can foresee failures having a productive impact, not just production, but also possibly can save a life. AI-enabled sensors are capable of analyzing the working conditions and helping to make preventive maintenance predictive, which also reduces the exposure of the workers to dangerous situations. AI has a huge contribution in converting people-oriented industries to process-oriented hence raising the standard of safety and efficiency.
- Sustainable mines: Embedded AI technology in pre-existing mining activities helps to reduce environmental footprints by assessing low impact mining techniques and thus reducing surface destruction. AI data also helps to suggest how we can explore and extract minerals from surfaces in a sustainable way.
- Simplify mining operations
- Improves time management
- Prevents breakdown and predict failures
- Better and faster decision making
- Improved health and safety measures
- Greater productivity
- Less environmental footprint
- Better accuracy
- Reduces operating cost
The companies are using artificial intelligence (AI) and machine learning (ML) to improvise on speed, extraction, and efficiency with resulting in successful and profitable operations in mining.
Data is collected in different types and formats by the AI application and then data is sorted. By using soil samples from a few test surfaces it determines discovery and exploration by predicting target classification of total surface area and soil composition. ML algorithm streamlines Ore fragmentation assessment with the help of 3D maps and satellite imagery. AI systems integrate drill data, sample results, and survey reports recommending techniques to optimize ore deposits. The data helps streamline processing and sorting procedures to conserve energy and minimize truck rolls.
Some companies use robotic automation and industrial IoT(IIoT) to manage autonomous drilling systems and hauling fleets with multivariable modelling to predict possible outcomes. AI data provides insight into safer extraction and processing. Overall the AI seems to be a very promising move in the mining industry yet one biggest challenge is to manage the entire value chain as one operation.