High CAPEX and production cost in the mining industry makes efficiency and productivity one of the important focus areas. Volatile commodity prices put additional pressure to maintain cost efficiency. Hence, It becomes extremely important to increase asset lifecycle and predict failures before they lead to downtime or asset degradation. This is also critical from the safety aspect which is undoubtedly very critical for mining companies.
AI is enabling mining companies to become insight-driven enterprises that utilize data to derive key benefits of improved efficiency, enhanced safety, and positive ROI.
Accelerate the prospecting, discovery, and exploration phase by predicting target zones. AI platform that consumes a variety of data- geological, topography, geo-mechanical, and engineering obtained through satellite imagery, aerial photographs, and 3D maps. Advanced algorithms for analyzing composite samples for quantification and impurity estimation.
Decrease sourcing lead time, minimize risk through AI based Advisory agents that help in effective decision making for spot buying, supplier selection & category management. Algorithms to classify suppliers into risk profiles based on various parameters. Automatic handling of transactional activities like service requests, proposal requests etc.
Reduce downtime and enhance safety by analyzing the huge amount of high-resolution sensor and production data to identify anomaly conditions and failure patterns. Predict equipment failure and send alerts to maintenance way ahead of the actual breakdown. Insights on variables that need to be manipulated to extend the equipment lifecycle. Prescribe specific maintenance actions and generate maintenance schedules.
Increase efficiency by automating repetitive manual time-consuming tasks like data extracting, uploading and validating. Automate calculations such as metals balancing using data aggregation from production and lab information systems integrations with metals accounting system. Leverage chabots for content search intensive activities like searching equipment maintenance manuals , safety procedures, policies or vendor data.