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Through big data, IBM can predict when mining equipment will fail and save companies billions

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(Credit: Reuters) The image shows the corporate logo of IBM.IBM
February 20
11:33 AM 2014

IBM doesn't have a crystal ball but it can predict when mining equipment has had enough. The technology giant said that through the use of big data, it can help mining firms determine when their equipment is going to stop working, VentureBeat reported.

The company is able to help industrial companies find solutions to a problem that causes them huge financial headaches by getting data from equipment sensors and using supercomputing power. Companies like Thiess, a mining equipment operator, could possibly gain billions of dollars in annual savings with IBM's new technology. IBM Almaden Research Center and Thiess lead the research which resulted to the modeling and analytics work, the report said.

In an interview with VentureBeat, IBM Research Smarter Planet Modeling and Analytics Manager Matt Denesuk said the technology has the potential to change the mining equipment operations business valued at $5 trillion. According to Denesuk, the natural resource industry only allocates 1% for information technology spending compared to the 5% to 7% allocated to the space by other businesses, the report said.

However, he noted that sensors that can send data to communications hubs are a standard part of majority of heavy mining equipment for reasons like safety. That data is usually stored only in monthly reports for the infrequent review of analysts to determine usage of the equipment, the report said.  

IBM, however, is going to make the analytics immediately available, in real-time. Denesuk said IBM will take data from various sources so that it can make specific forecasts about particular pieces of equipment. IBM uses such data as the load carried by the trucks, the environment conditions it moves in, rates of fuel consumption and repair history, among others and makes the necessary computations before giving insights, the report said.

Denesuk said, "We plug that into the analytics and we optimize the whole business operation. We can look for patterns and come up with risk assessments and costs."

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