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Predict to prevent: Transforming mining with machine learning - IBM Industrial IoT Case Study
Predict to prevent: Transforming mining with machine learning
IBM
Mining companies have a lot of data at their disposal. Sensors are seemingly everywhere in their underground operations. But thus far it has been very hard for mining companies to capitalize on all their data because of the difficulty in making sense of it all.So what’s the most important data for mining companies? The short answer: assets. Mining is one of the most asset-intensive businesses there is. At every point in the extraction chain— drilling, cutting, crushing, screening and removing ore-bearing rock—heavy equipment is critical. And it takes a beating. When equipment breaks down, requiring unscheduled maintenance, production takes a hit, costs rise and a critical measure of capital efficiency in mining—overall equipment effectiveness (OEE)—goes down.
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