Using drones to reduce drill and blast costs

Drones have become a common sight in quarries over the last few years.

The industry overcame early teething issues of hardware reliability, operator training and regulatory licensing, with many sites bringing their drone operations in house. The biggest challenge quarry managers now face is how to use their drones to generate real cost savings.

Most sites start using drones for aerial inspections and basic mapping and surveying. This provides benefits by removing people from unsafe situations and increasing surveying efficiencies. Still, these do not impact major cost drivers in the quarry value chain.

A quarry manager’s primary focus should be safely and sustainably reducing total cost per ton. This generally means increasing plant throughput rates or reducing spending on fuel, maintenance and explosives. The question managers should ask, then, is how can drone data help us achieve this?

Advancements in artificial intelligence unlocked a range of possible applications for drone data. But it is important to start with a clear understanding of the main value drivers at sites in order to prioritize the solutions that will have the most impact.

Primary crusher throughput

If a primary crusher is bottlenecking a site, increasing crusher throughput will lead to a direct reduction in cost per ton. Either more material can be produced for the same fixed cost base, or the same amount of material can be produced using fewer plant operating hours.

One of the main factors affecting primary crusher throughput is fragmentation. This metric is commonly judged by the eye, though, as quantitative measurement has traditionally been expensive and time consuming.

Still, it is now possible for drones to measure muckpile fragmentation using AI that is trained to detect rock edges. Other AI models can then correlate this with drill and blast parameters to accurately predict how a specific design change will impact fragmentation results.

All of this means drone data can be used as a key input to optimize drill and blast designs to reduce total cost per ton.

Fuel consumption and tire wear

Fuel and tires are two of the largest cost categories for pits. Moving the same amount of material while buying less fuel and fewer tires offers a significant total cost savings for every site.

Drone data can help achieve this by monitoring road quality and correlating this with driver performance.

Once drone images are processed into a 3D photo model, AI algorithms can be trained to detect the haul roads and automatically assess metrics such as grade, camber and smoothness to highlight any areas that need attention.

Drill and blast costs

Blasting represents another major cost for quarries, but costs can be difficult to control because operations are often outsourced.

This leads to a lack of transparency into drilling and blasting quality and efficiency. In these situations, it is common for sites to focus purely on price negotiation with contractors when trying to reduce cost.

AI can again be implemented to analyze drone data and provide greater visibility into blasting operations. Hole locations can automatically be detected and assessed to measure collar deviation. Boretrack data can be combined with 3D drone models to assess drilling performance and inform safer loading decisions. These 3D models can then be used to calculate actual volumes and powder factors for each hole and for the entire shot.

This information empowers quarry managers to take control of drilling and blasting costs by working with operators and contractors to improve quality and efficiency rather than just negotiating price.

Drones have proven their worth as an efficient survey tool, but their full potential can only be unlocked by addressing the major value drivers on site. AI is now enabling many of these use cases and shifting drone data from “nice to have” to a key component of site profitability.

Brad Gyngell is COO of Strayos.