Today’s mining industry fleets operate some of the most impressive inventions of engineering thought – from 400-ton ultra-class haul trucks powered by 4,000 horsepower engines to 90-meter-high bucket-wheel excavators. Miners constantly seek innovative ways to improve the productivity, operational efficiency, and environmental footprint of their heavy-duty assets.
In the meantime, the specialized heavy-duty machines represent, according to different sources, only 10 to 20% of the mobile equipment units currently in use in the mining industry. In other words, on each haul truck, drill, or loader in a mine, there are five to ten units of light-duty utility vehicles. This equipment may include 1-ton pickup trucks, personnel carriers, forklifts, and other vehicles used for logistics and various production support purposes.
Ensuring the visibility of mining heavy-duty assets utilization, productivity and reliability is already a challenging task: the data availability and communication protocols specification differ across various makes, models, and even model years, especially when a multi-vendor mining fleet is concerned. The challenge is compounded when the light-duty vehicles are taken into account. A real-life mine may operate a thousand units-strong fleet produced by heavy equipment companies such as Caterpillar and Komatsu and road vehicle manufacturers like Ford and Toyota. These vehicles should be operated in line with the best standards of productivity, efficiency, and ESG. The vendor data lock-in, creating an additional barrier to data visibility on the fleet scale, may hamper the efforts to achieve the desired quality of operations.
Symboticware’s 4-Sight.ai is a telemetry management system that enables capturing operational and environmental data of both heavy- and light-duty mobile assets across different makes and models. The technology relies on the unique library of data ports and protocols to bring the data from the entire fleet to one platform. Some of the advantages of having a single source of telemetry data for heavy- and light-duty vehicles include:
- Increased productivity and efficiency of operation by benchmarking the performance of the assets
- Enabled predictive maintenance based on machine learning and AI-ready datasets
- Access to ESG reporting-ready data accumulated from across the fleet
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