Rio Tinto – RAILVU – Optimization of the Rail Network Iron Ore Throughput with AI
The Challenge
The Labrador Trough is a significant basin with rich deposits of high-grade iron ore. The mining operations in the region are serviced by two independent railways, including the Quebec North Shore and Labrador Railway (QNS&L), Rio Tinto IOC’s wholly-owned 418 km railway.
To unlock additional capacity and optimize the operations of the QNS&L railway, which serves four iron ore producers in the region, the ‘RailVu’ project aims to introduce AI-powered tools to refine daily train scheduling and enable real-time traffic management.
The challenge
The Labrador Trough is a significant basin with rich deposits of high-grade iron ore. The mining operations in the region are serviced by two independent railways, including the Quebec North Shore and Labrador Railway (QNS&L), Rio Tinto IOC’s wholly-owned 418 km railway.
To unlock additional capacity and optimize the operations of the QNS&L railway, which serves four iron ore producers in the region, the ‘RailVu’ project aims to introduce AI-powered tools to refine daily train scheduling and enable real-time traffic management.
Investment
$
1.7
M
Scale AI investment
$
4.4
M
Total investment
Partners
