Material Handling and Human Capital Will Increase Productivity
When it comes to enhancing material handling, the mining industry must solve ore separation challenges through intelligent machines and plants, say leading experts. Additionally, the need to improve productivity demands higher levels of cleanliness for fluids and water to decrease waste and lower operating costs. The industry insiders concur that having prepared human capital is key to improving these areas.
Regarding the handling of materials, tailings dams have long since been identified as risks that might lead to major environmental and social issues. Mining companies should start to look at the adaptation of new technology to replace traditional approaches with higher risks of failing. Diego Torroella, General Director, TAKRAF, explains that implementing an approach such as the Dry Stack Tailings (DST) system offered by his company provides significant environmental and social benefits, as well as financial advantages.
Ore sorting technology can generate a major operational shift in the industry due to the importance processing has in the mining supply chain. High-tech companies are developing machines that, using 3D cameras, lasers, inductors and X-rays, can sort any ore and quickly detect its value. This technology can reduce the mining operator’s capital expenditure as well as save valuable energy and water in the process. “Flotation cells are widely used to separate, recover and concentrate valuable minerals. Water reuse systems are also important, as companies require better liquids management to recover most of the increasingly scarce water,” Torroella said.
According to Alvaro Rendon, Director ECN Scientific, ECN Automation, variations in feed size along with ore composition and grindability strongly affect the mill performance. Furthermore, the online measurement of these variations is crucial to define the mill throughput model. Product sizes are used to determine the optimal size of the feed for maximum efficiency and determine which feed size losses occur in the plant to reduce these issues. Technology can help to make this process faster and more precise.
Since 2015, deep convolutional neural networks (DCNNs) have been used to efficiently extract features for classification and regression tasks. Using a DCNN for bulk solid size distribution estimation for a conveyor belt is a novel approach. In 2019, the first embedded system using GPUs running DCNN was introduced to measure particle size distribution in fine ore-feeding primary ball mills using high-resolution cameras.
In addition, Rendon explains that traditional technologies have some limitations in recognizing small rock sizes below 3mm as well as fine ore cracking that can generate segmentation detection errors. New technology based on deep learning techniques guarantees smaller size detection and avoids detection errors.
Since technology represents high upfront costs, companies will be careful with what kind of equipment they acquire. “Technological appliances are difficult to sell. Companies want to see your product being applied somewhere else before deciding their purchase and it becomes even more complicated since they want to see the solution functioning in a project resembling theirs,” said Antonia Talarico, Vice President of Operations, Centric Mining Systems.
Experts believe that the efficient planning of a mining project is crucial when companies are looking to enhance their productivity. "When designing any system, you must look at all different angles and integrate these issues holistically to design mining tunnels in the most efficient way," said Fred Stanford, CEO, Muckahi.
“GRUMIMEX believes in starting from the beginning, it is important to conduct both internal and external analysis to determine which modifications in the mining process should be made. We encourage customers to consider potential changes in the original plan and create adequate spaces for such changes. Doing this will prevent potential bottlenecks,” added Cynthia Villa, General Manager, Grupo Minero Mexicano (GRUMIMEX).
However, industry insiders believe that integrating machinery and technology based on extensive planning is insufficient; companies must take a look at their human capital, too. Villa mentioned that said bottlenecks are sometimes caused by a lack of effective communication rather than failing technology, which leads to a lack of knowledge of a particular part of the process. Similarly, companies must be careful that their talent is involved in changes if new tech is implemented. “People only resist change when they are excluded from the process, so workers must become a part of this shift. I find it more productive to allow the people that will be affected by the change to have a say in it,” said Stanford.
“Continuous training of workers plays a determining role in technology implementation. It does not matter if you utilize up-to-date equipment if you do not have trained workers or properly communicate with them,” Torroella agreed.