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    Sandvik xCell Vision: automated rock bolt QA/QC explained for ground engineers

    November 9, 2026|

    Reviewed by Tom Sullivan

    First reported on International Mining – News

    30 Second Briefing

    Sandvik has launched xCell Vision, a cloud-based AI and LiDAR-driven system that automatically identifies and classifies installed rock bolts in underground mines and tunnels. The software extracts bolt count, spacing, orientation and tail length directly from 3D scan data, replacing manual tape and visual checks for ground support QA/QC. For geotechnical engineers, this enables faster compliance checks against support patterns, more consistent documentation of installation quality, and earlier detection of under-supported areas.

    Technical Brief

    • Automated bolt recognition reduces reliance on manual tape measurements in unsupported or partially supported headings.
    • Consistent digital records of each scan create an auditable trail for ground support safety compliance.
    • Remote access to processed datasets allows geotechnical engineers to review support conditions away from high-risk zones.
    • Standardised, algorithm-based classification of bolts reduces human variability in support inspections and sign-off.
    • Integration of AI with LiDAR aligns with regulator pressure for objective evidence of installed support patterns.
    • Similar workflows could extend to mesh, shotcrete and cable bolt QA/QC, tightening overall ground control assurance.

    Our Take

    In our software category, Sandvik is one of the few OEMs that also appears frequently in safety-tagged hardware pieces, such as the recent certified lifting solutions for raise boring maintenance, signalling a deliberate strategy to bundle digital and physical risk controls around critical underground tasks.

    The joint collaboration statement with Eldorado Gold and the large underground fleet order from Northern Star Resources suggest that Sandvik’s major gold clients are already invested in its digital-ready equipment, which should ease deployment of automated rock bolt analysis across multiple mines once proven.

    Across the 40 Software stories in our database, Sandvik stands out for pairing analytics tools with training and skills initiatives like its global postgraduate mining engineering programme, which likely helps drive adoption of more advanced inspection systems such as xCell Vision at site level.

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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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