Researchers from Brazil Potash Corp have recently launched an artificial intelligence (AI) based optical ore-sorting trial at the Autazes Project in Brazil. Their goal was to enhance operational efficiency and reduce overall costs in potash extraction and processing, a critical mineral for agriculture and other industries.
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Novel Technology Enhancing Ore Separation
This initiative utilizes AI-powered X-ray Transmission (XRT) technology to enhance the separation of potash ore/minerals from waste rock, resulting in a more accurate and efficient sorting process. This initiative represents a significant step toward sustainable and economically viable mining, showcasing how AI can transform traditional operations.
Evaluating Economic and Operational Benefits
This trial assessed the economic and operational benefits of AI-powered sorting technology at the Autazes Project, which is expected to become a significant source of potash for Brazil’s agricultural sector. This initiative is crucial, as Brazil imported over 95 % of its potash in 2021, despite having one of the world’s largest undeveloped potash basins.
Researchers evaluated the AI sorting system’s ability to pre-sort ore, either underground or at the surface, before processing. Their approach aims to reduce the size of both the main mine shaft and the processing plant, lowering construction and operating costs.
The methodology utilizes X-ray sensors and machine learning to identify and separate minerals from waste rock in real-time, improving ore recovery and increasing the grade of material sent to the processing plant. The trial also tested the AI system's reliability under real mining conditions to observe the success seen in other potash operations, where ore volume was reduced by approximately 50 % before hoisting.
Key Outcomes from the AI and X-Ray Trial
Preliminary results indicate that the AI-powered optical ore-sorting technology can concentrate ore by approximately 50 % underground before it is hoisted to the surface. This improvement significantly reduces the amount of material requiring processing, resulting in lower energy use, reduced environmental impact, and improved operational efficiency.
The surface processing plant could be built with a lower capacity, resulting in substantial cost savings. Constructing a smaller main shaft could further reduce construction time while enabling future production increases with minimal additional investment. The trial confirmed that increasing the potassium chloride content of ore delivered to the processing plant enhances efficiency and reduces operating expenses.
These findings align well with the mining sector’s shift toward sustainability. By concentrating ore underground, the operation reduces material handling, lowers emissions, and enhances resource efficiency. The trial demonstrates how AI technology can modernize mining practices, improving both economic performance and environmental responsibility.
Broader Impact on the Mining Industry
AI-driven optical ore sorting has significant implications that extend beyond the Autazes Project. As the global mining industry faces increasing pressure to improve efficiency and reduce environmental impacts, this technology provides a model that other operations can adopt. It is particularly relevant for projects targeting critical minerals, where economic viability depends heavily on the effective separation and processing of resources.
By reducing material-handling and processing requirements, the risk of accidents decreases, improving overall site safety. The trial further shows how AI and machine learning techniques could support better real-time decision-making, paving the way for advanced ore sorting.
As Brazil Potash continues to refine the technology, the potential for global adoption becomes evident. The ability to enhance ore recovery, reduce costs, and lower environmental impacts positions AI as a key driver of the future of mining.
Paving the Way for Future Mining Practices
The integration of AI in mining, as demonstrated by Brazil Potash, offers clear economic and sustainability benefits.
The trial of AI-powered ore sorting at the Autazes Project marks a pivotal step toward transforming the mining industry. The findings demonstrate that AI can enhance efficiency, reduce costs, and facilitate sustainable resource extraction.
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This study highlights the value of innovation in addressing environmental and economic challenges within the sector.
As demand for potash and other minerals continues to rise, AI-driven technologies show strong potential to reshape mining operations.
Brazil Potash’s commitment to adopting advanced systems serves as a model for different companies, underscoring the key role of technology in driving progress. This trial suggests that AI could become essential in building an efficient, responsible, and future-ready mining industry.
Journal Reference
Brazin Potash Corp. (2025) Brazil Potash Initiates Artificial Intelligence Powered X-Ray Ore Sorting Trial as Technology Shows High Potential to Substantially Reduce Costs. [Online] Available at: https://ir.brazilpotash.com/news-events/press-releases/detail/49/brazil-potash-initiates-artificial-intelligence-powered-x-ray-ore-sorting-trial-as-technology-shows-high-potential-to-substantially-reduce-costs
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