«We’re not ready for this yet. We only have 30 trucks»
This is one of the weakest objections in mining tech.
AI-based truck balancing does not start at 100 trucks. It does not even start at 50. In practice, once you have around 20-25 trucks working across multiple excavators, the system is already too dynamic for manual allocation to compete with an algorithm recalculating every few seconds.
Let’s be precise. Fleet size affects the size of the prize. It does not determine whether the problem exists.
A 30-truck mine may generate less absolute upside than a 150-truck one. Obviously. But the underlying losses are usually the same: truck-shovel imbalance, hidden shift-change losses, badly timed refuelling, queueing, idle equipment, unstable haulage flow.
The difference is that smaller operations usually feel those losses more sharply. Large mines often have buffer. They can survive inefficiency. Smaller ones often cannot. When your fleet is small, every lost trip matters more, not less.
So “we’re too small for AI” usually means something else: “We’re too small to buy an overpriced, heavy, consultant-fed famous system.”
Fair enough. But that has nothing to do with whether AI balancing is relevant. It has everything to do with the kind of solution being offered.
We have seen smaller sites improve fast, because the operational losses were already there. The mine was not too small for AI.
It was just running below its potential.
Read more — in our LinkedIn www.linkedin.com/company/oesventures/
This is one of the weakest objections in mining tech.
AI-based truck balancing does not start at 100 trucks. It does not even start at 50. In practice, once you have around 20-25 trucks working across multiple excavators, the system is already too dynamic for manual allocation to compete with an algorithm recalculating every few seconds.
Let’s be precise. Fleet size affects the size of the prize. It does not determine whether the problem exists.
A 30-truck mine may generate less absolute upside than a 150-truck one. Obviously. But the underlying losses are usually the same: truck-shovel imbalance, hidden shift-change losses, badly timed refuelling, queueing, idle equipment, unstable haulage flow.
The difference is that smaller operations usually feel those losses more sharply. Large mines often have buffer. They can survive inefficiency. Smaller ones often cannot. When your fleet is small, every lost trip matters more, not less.
So “we’re too small for AI” usually means something else: “We’re too small to buy an overpriced, heavy, consultant-fed famous system.”
Fair enough. But that has nothing to do with whether AI balancing is relevant. It has everything to do with the kind of solution being offered.
We have seen smaller sites improve fast, because the operational losses were already there. The mine was not too small for AI.
It was just running below its potential.
Read more — in our LinkedIn www.linkedin.com/company/oesventures/