Mining is a global industry that is fundamental to every product we use. A vital component of the mining industry is efficiency because most of the production revolves around transforming matter into different forms. It is often the case that small improvements in execution speed, process efficiency, or reduced downtimes separate a profitable operation from a complete failure. Nowadays, artificial intelligence is readily available in many of the products and services we use. Furthermore, cloud computing matured, hardware prices decreased, and machine to machine communication improved leading to unexpected advances in mining and industrial technology. Add the latest advances in analytics and artificial intelligence to the mix, and you get the perfect environment for improving efficiency in all areas of a mining operation.
In short, systems powered by artificial intelligence use different algorithms to organise and understand vast amounts of data with the purpose of creating of making optimal decisions. One immediate application of AI in mining is during the prospecting phase, especially for discovering deposits. For example, Goldspot Discoveries Inc. uses artificial intelligence for improving mineral exploration. The current practice of finding gold deposits is more an art than a science, thus Goldspot Discoveries Inc. intends to change that by developing AI systems capable of ingesting different data from which to discover potential gold deposit locations. AI is also used to understand better the environment and the terrain where new development will take place. In this space, Drone Deploy uses drones and computer vision to understand better the environment and the terrain where exploitation is to begin.
Artificial intelligence is not limited to systems capable of going through vast amounts of data. Some companies aware building intelligent systems for other phases of the operation. For example, the diamond mine Renard, in Quebec. There we see a smart system for waste sorting and disposal. This system is primarily used to improve the quality and quantity of the diamond recovery process. The algorithms use data from sensors and X-rays to increase the diamond recovery rate which helps recovering at least 96% of the weight of all diamonds larger than 1mm. Within the same space, Tomra, a Norwegian mining company, also developed a smart sorting system for minerals and ores. They are using computer vision and other AI algorithms powered by colour sensors and X-rays data. Finally, another successful example is Rio Tinto who now uses a fleet of autonomous vehicles inside the mine. These vehicles can be remotely operated and managed.