Stockpile Management Challenges in Mining

EKA > Stockpile Management Challenges in Mining
Sep 20, 2017

Stockpile Management Challenges in Mining

September 20, 2017



Copper and Iron Ore stockpiles across the world have risen steadily in the last 12 months. Recently there has been news of record levels of iron ore stockpile in China. Apparently there’s enough Iron Ore to build 13,000 Eiffel Towers. As for Copper inventories, one can look at how stockpiles have increased at LME registered warehouses. If one adds increase in bonded copper stocks held in free trade zones in China, to this mix – it will be easy to see how Copper stockpiles have risen over the last 12 months.


Having a stockpile provides distinct advantages for mining companies – For ex: It acts as a buffer against supply fluctuations and it enables grade maximization by blending. However, managing stockpiles has a cost to it and having excess levels of stockpiles will only negate the benefits. How then, are mining companies expected to manage costs associated with rising stockpiles in Iron Ore and Copper?


One of the biggest challenges with stockpiles, is the measurement of quantity and quality parameters. Mining companies would ideally like to measure their stockpiles A) Accurately and B) Frequently. But often, these two objectives are at odds with each other.


Accuracy in measurements is a challenge because stockpiles are usually several feet high and are spread across areas comparable to football fields. Measuring such stockpiles, would require surveyors to physically move around the stockpiles, often taking several hours or days, inspecting shape/size and collecting data points for measurement. It’s very common for errors to creep in. For ex: Poorly defined base of the stockpile or poor surveying of stockpile top due to accessibility issues or inclusion of unwanted material/ vegetation in measurements. Adding to this complexity, mineral stockpiles often undergo changes in their composition as weather conditions vary. Besides, contamination from dust and moisture can also result in quality variations.


This isn’t to say that accurate measurement isn’t possible at all. In fact, there are several ways to measure accurately – For instance, Laser based measurement or using aerial surveys etc. While these techniques increase accuracy, they also add up to the time and cost of measuring stockpiles, making it difficult to use them frequently. On the other hand, not measuring stockpiles frequently also has cost implications, because mining operations run 24×7, which means that stockpiles change shape and size frequently, as minerals are stacked or reclaimed from the stockpile. While mining companies would love to measure stockpiles accurately and frequently – often these two objectives are at loggerheads. This often results in inventory mismatch and write-offs


Of late, companies have started using advanced technologies, such as drones, to address this issue. Using drones, one can take aerial photographs of a stockpile and easily get measurement data in a matter of hours, instead of days. It’s also a lot cost effective as compared to paying someone to fly a plane over the stockpile and click photographs. On the flip side, drones generate a lot of data. By it’s very nature, photogrammetry is data intensive and a lot of factors govern the accuracy of data. While drones can get the photogrammetry data in a matter of hours, often understanding and fixing the data is a tedious process. Besides the companies that make drones, though technically sound, are usually not experienced in the nuances of stockpile measurement.


In this context, it becomes very important for mining companies to have a solution, such as Eka’s stockpile solutions, that uses advanced algorithms and data from measurement devices such as Laser, Radar, and Drones to generate a real time 3D volumetric model of their stockpile and equipment thus enabling accurate as well as real time tracking of quality & quantity levels of a stockpile.


Eka’s 3D Stockpile Manager System utilises advanced deposition and material flow algorithms to generate a 3D height map of stacked material. The model takes into account different material parameters including bulk density, angles of rill and repose, stacker discharge rates, and stacker discharge point in 3D space to represent stockpiles with high detail and accuracy. Stockpiles are displayed to the operator in a 3D ‘fly-around’ view and are updated in real-time as stacking and reclaiming operations are performed. In addition to viewing past quality results, site operators can simulate future results when making stacking and reclaiming decisions. The solution can also consider measurement inputs from Laser, Radar and Drones and can even be used to define safe working zones to prevent collisions between equipment and stockpiles – thus increasing safety.