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Essential for the logistics sector of Brazilian mining companies, long-distance conveyor belts are responsible for carrying raw materials and inputs to the next stages of the production chain. Despite their relevance, problems such as overheating can generate technical difficulties, unexpected shutdowns, and even fires. The result is financial losses that could be avoided through preventive and predictive maintenance, in addition to greater agility in solving problems identified at different points along the belts. With iron ore prices returning to more common levels, efficiency in the various production stages must be at the focus of operations. After all, costs such as extraction, inventory, treatment, and shipping for export are directly linked to the effectiveness of the belts responsible for transporting the inputs, which need to travel long distances while presenting the minimum of technical failures. Research developed by the Dom Cabral Foundation (FDC) indicates that logistics expenses represented 12.37% of the gross revenue of Brazilian industry in 2017. In the mining sector, investment in logistics accounted for 26% of gross revenue, becoming the champion in spending on transportation solutions among the segments evaluated by the study. For a sector that reached R$ 209 billion in revenue in 2020, problems in the logistics infrastructure correspond directly to financial losses for mining companies. Directly linked to the search for more efficiency in the production chain, the logistics infrastructure is responsible not only for the flow and physical distribution of inputs, but also for the feasibility of the entire mining process; after all, the extraction hub is not always close to the flow routes. Activities linked to extraction planning are only possible thanks to an efficient transportation structure, which demands attention to a sector that relates directly to several other operational areas, including the search for greater efficiency and cost reduction.
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Predictive maintenance: smart, real-time inspection is capable of considerably reducing transport costs
In addition to the financial impact caused by technical problems on conveyor belts, it is necessary to consider the time spent on restoring operations in the event of unexpected stoppages. The possibility of monitoring the condition of the belts can not only prevent failures and fires, but also reduce health risks for maintenance workers. After all, besides being time-consuming, expensive, and inefficient, manual inspection can pose unnecessary risks to the mine operations team. ALSO READ: • Computer Vision: A Complete Guide to answering your questions
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Artificial intelligence to solve problems in the use of conveyor belts
Solutions presented through the use of Artificial Intelligence (AI) in the logistics infrastructure of mining companies have proven to be effective, making maintenance processes safer, more innovative, and with lower operational costs. Decision-making by technical teams and managers is optimized through data and information generated by the use of devices, including drones capable of monitoring the temperature of conveyor belt rollers. Deeptrack, a solution developed by Pix Force in partnership with Eneva, enables the action of drones capable of automatically identifying the heating of rollers on conveyor belts. Through Artificial Intelligence (AI), the exact temperature and georeferenced location of each roller are identified and reported in quick and precise reports, which can be analyzed simultaneously by the mine maintenance and operation team. The technology is capable of operating in harsh environments through autopilot and remote monitoring, allowing access to accurate information. Fast and lower-cost monitoring enables the introduction of solutions promoted by AI in the Brazilian market, connecting devices to people. In addition, an operations audit can be performed, since the recording generated by the drones' performance is available after processing. RGB and thermal images are made available, generating information on the functioning of the belts at specific moments and answering questions about interferences in the operation during certain periods of time. Based on information about rollers with normal and abnormal temperatures, it is possible to obtain a historical context on those that are showing operational depreciation. Sections of the conveyor belt with frequent problems can also be identified, optimizing the work of maintenance teams. Cost reduction with maintenance and unexpected stoppages on conveyor belts are just some of the benefits generated by the introduction of this technology to the Brazilian market. After all, the availability of information supports technical teams and managers in making more assertive decisions that can impact different stages of the production chain.
Fabio Caraça
Fábio Caraça is the Chief Growth Officer at Pix Force. He leads Pix Force's transformation into a scalable SaaS operation, combining strategic vision, culture, and high-impact execution.
