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    Mining’s north star of remote autonomy: integration lessons for brownfield mines

    August 4, 2026|

    Reviewed by Tom Sullivan

    Mining’s north star of remote autonomy: integration lessons for brownfield mines

    First reported on International Mining – News

    30 Second Briefing

    Mining’s push for remote autonomy is shifting from isolated pilots to integrated systems where ABB’s Ability™ platform links hoists, grinding mills and conveyors with fleet management and plant control. Vedrana Spudic, Head of Technology, Mining & Materials at ABB Process Industries, describes mines trialling tele-remote LHDs, semi-autonomous haul trucks and drone-based stockpile surveys, all supervised from offsite operation centres hundreds of kilometres away. The key constraint is legacy brownfield infrastructure—narrow haul roads, variable comms bandwidth and mixed-vintage drive systems—which forces staged upgrades to power, networking and control architectures.

    Technical Brief

    • For other mines, a key lesson is designing early for interoperability between plant control and fleet management.

    Our Take

    With 110 keyword-matched pieces on critical minerals in our database, ABB Process Industries’ focus on remote autonomy sits squarely in a stream of coverage where operators are looking beyond discovery to how they will safely run dispersed, harder-to-staff assets.

    Recent items on Queensland’s four-year critical minerals plan suggest that jurisdictions actively courting critical minerals investment will be receptive to remote and autonomous operating models, which could make ABB-style control architectures a differentiator in project approvals and funding pitches.

    International Mining’s role in both this piece and the World Mining Congress 2026 coverage signals that remote autonomy for critical minerals assets is moving from vendor marketing into the mainstream conference agenda, where it will shape how CEOs think about workforce, ESG reporting and long-term asset design.

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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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