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    ABB–Point Laz mine hoist inspection JV: integrated monitoring insights for engineers

    May 27, 2026|

    Reviewed by Tom Sullivan

    ABB–Point Laz mine hoist inspection JV: integrated monitoring insights for engineers

    First reported on International Mining – News

    30 Second Briefing

    ABB has formed a strategic partnership with Point Laz to integrate the Lazaruss™ mine shaft monitoring system into ABB’s mine hoist portfolio, targeting safer and more reliable hoist inspection in deep underground shafts. The collaboration focuses on an integrated service offering that combines continuous shaft condition monitoring with hoist control and maintenance planning, moving inspections away from purely manual, periodic checks. For engineers, this signals growing scope to link hoist performance data with real-time shaft integrity information for earlier detection of lining, guide and conveyance issues.

    Technical Brief

    • System architecture supports remote diagnostics, reducing exposure hours for personnel in inspection conveyances.
    • Event logs and condition trends can be tied directly into planned maintenance work orders for shaft infrastructure.
    • For safety management, the approach shifts compliance evidence from periodic reports to time-stamped, sensor-based records.
    • Similar integrated hoist–shaft monitoring could inform future standards for shaft inspection intervals and acceptance criteria.

    Our Take

    ABB already features prominently in our Mining coverage through power and drive packages for projects like Harmony Gold’s Eva copper mine, so a JV with Point Laz on hoist inspection suggests it is trying to lock in more of the life-of-mine services envelope around its installed equipment base.

    The tie-up also aligns with ABB’s recent push to embed digital and AI tools (as seen in its ABB Ability Energy Management integrations), implying that hoist inspection under this JV may evolve quickly towards data-rich, condition-based regimes rather than periodic manual checks.

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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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