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    Hexagon–UMEC collision avoidance JV: design and testing insights for mine engineers

    December 17, 2025|

    Reviewed by Joe Ashwell

    Hexagon–UMEC collision avoidance JV: design and testing insights for mine engineers

    First reported on International Mining – News

    30 Second Briefing

    Hexagon’s Mining division has secured access to Montana Technological University’s Underground Mine Education Center (UMEC), including its full-scale training drifts and specialised underground equipment, to develop next-generation collision avoidance and operator safety systems. The agreement gives Hexagon a controlled but realistic testbed for validating sensor coverage, communications performance and human–machine interface design in complex underground geometries rather than relying solely on lab or surface trials. Engineers can expect faster iteration of proximity detection algorithms and simulation models tailored to narrow headings, mixed fleets and variable ground conditions.

    Technical Brief

    • Similar university–vendor arrangements could formalise proving grounds for other underground safety and automation systems.

    Our Take

    Within the 730 tag-matched pieces on Projects, Safety and Product, underground collision avoidance is one of the less frequently covered safety themes, suggesting Hexagon’s Mining division is moving into a relatively under-served niche compared with surface fleet management and fatigue monitoring.

    Using Montana Tech’s Underground Mine Education Center (UMEC) as a JV testbed gives Hexagon a controlled but realistic environment to validate sensor performance and algorithm reliability before deployment in high-risk production headings, which can materially shorten certification and client trial timelines.

    For OEMs and contractors following our Mining safety coverage, this JV model with an academic underground facility like UMEC signals a practical route to de-risking next-gen digital safety products without tying up production time at operating mines.

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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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