Improvements in operational efficiency, predictive maintenance, and asset optimization are more likely to draw the attention of mining companies than the latest technology trends. But the industry will find many new opportunities to accomplish its business objectives by harnessing the huge volumes of information that now flow through mining firms – commonly referred to as Big Data.
Tapping into the Internet of Things
In mining, as in most industries, machines and other equipment are often now embedded with “smart objects” that connect to the Internet through wireless devices. Mining companies can use this “Internet of Things” (IoT) connection to collect and analyze large volumes of data in real, or nearly real, time. The data gathered from smart devices on trucks alone is quite extraordinary – showing how well an engine runs, for example, or whether the tire pressure is appropriate.
IoT can also open new business opportunities. Consider Rio Tinto, a respected international mining company with a mine in Western Australia that it controls from a remote operations center in Perth. The mine features a driverless intelligent truck fleet and remote control intelligent drills that use connectivity made possible through smart objects and the IoT.
Using 3D visualization to enhance exploration
Advanced tools for automatically gathering and analyzing drilling data can readily create 3D visualizations based on information that is highly granular. With such transparency, mining companies can rapidly find the greatest concentrations of ore, gain better insight into the geology of their drilling sites, and more quickly adjust their mining schedules to maximize the output of their operations.
This technology has provided major improvements for safety and training as well. Joy Global, a leading international manufacturer of mining equipment, has benefited greatly from adopting 3D visualization technology. The company has improved the safety of its equipment and augmented its training of new and current employees by being able to present trainees with visualizations that bring the training to life in a way no 2D schematic could.
Employees see during training what they’ll see in the field, depicted with precise accuracy. This leads to less retraining and fewer on-the-job mistakes. Joy Global now spends far less on training because it is able to reuse engineering schematics to feed its 3D visualization tool, while providing better quality training on its products.
Increasing operational efficiency
The collection and analysis of Big Data can also give mining companies greater insight into their overall operational efficiency – making it easier to determine, for example, how many truck turns occur daily at a particular mine, what the average load levels of those trucks are, what kind of stockpiles are available at various processing plants, and how those stockpiles change over time. Companies can compare efficiency across multiple mines and identify potential productivity or maintenance issues. They can also compare reported results against actual data.
An article in McKinsey Quarterly recently described how a mining company used Monte Carlo simulations to evaluate the cost of a project. Using historical data to model the potential impact of natural events, the company was able to optimize handling and storage capacity across its facilities and reduce related capital expenditures by 20 percent. According to research by SAP Performance Benchmarking, companies that use real-time monitoring of production and parametric data about processes, materials, and operations have a 10% higher capacity utilization rate.
Using in-memory technology to drive Big Data insights
In-memory computing technology has been shown to help organizations in many industries manage and analyze huge amounts of information more effectively and efficiently. Recent advances in hardware and software now make it possible to handle information from many different sources in real time at an affordable cost.
Going forward the ability to use and analyze Big Data will be a key factor in the survival of mining firms. Companies that take advantage of this tool should realize dramatic improvements in operational efficiency, predictive maintenance, and asset optimization.
