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    Sandvik–Northern Star underground fleet deal: automation takeaways for mine engineers

    December 15, 2025|

    Reviewed by Joe Ashwell

    First reported on International Mining – News

    30 Second Briefing

    Northern Star Resources has ordered Sandvik Toro® TH663i underground trucks and Toro® LH621i and LH517i intelligent loaders for its Western Australian gold operations, with the fleet order booked in Q4 2025. Deliveries will start in Q1 2026 and run through 2027, supporting high‑tonnage, automated loading and haulage in deep underground stopes. The i-series machines are configured for Sandvik’s AutoMine® and OptiMine® platforms, signalling further roll-out of tele-remote and data-driven fleet management in Australian hard-rock mines.

    Technical Brief

    • Sandvik’s intelligent loaders include onboard diagnostics and condition monitoring, supporting predictive maintenance in deep-level operations.

    Our Take

    Sandvik’s new C$85 million Sudbury facility, highlighted in our December 2025 coverage, signals that the supplier is scaling manufacturing and support capacity just as it secures larger underground fleet orders from operators like Northern Star in Australia, which should improve parts availability and rebuild turnaround for those fleets.

    Across the 309 Mining stories in our database, Sandvik appears frequently in automation and digitalisation contexts, so a multi-year underground fleet investment by a major Australian gold producer suggests Northern Star is likely positioning its Western Australian operations for higher automation and data-driven maintenance rather than a simple like-for-like equipment refresh.

    With deliveries starting in Q1 2026, the timing aligns with Sandvik’s push into non-coal mechanical cutting and hard-rock systems noted in our December 2025 piece on its 430-unit active fleet, indicating that Northern Star could benefit from the same design and component standardisation that Sandvik is rolling out across its broader hard-rock portfolio.

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    Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.

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