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    REMA TIP TOP MCube CAM: conveyor belt inspection insights for mine engineers

    December 11, 2025|

    Reviewed by Tom Sullivan

    First reported on International Mining – News

    30 Second Briefing

    REMA TIP TOP has launched MCube CAM, a smartphone-based system that uses AI-supported video analysis to inspect conveyor belt top covers, automating a task traditionally done by manual visual checks. The tool records belt surface condition in real time and feeds data into the company’s MCube monitoring ecosystem, enabling faster detection of damage, wear and splice issues. For mine operators, this points to more consistent inspection intervals, reduced downtime from unexpected belt failures, and better documentation of belt condition for maintenance planning.

    Technical Brief

    • Automated anomaly flagging supports risk-based maintenance scheduling and targeted shutdown planning for high-risk segments.
    • Consistent digital records strengthen compliance with site conveyor safety procedures and OEM maintenance recommendations.
    • Similar smartphone-based inspection workflows could be extended to chutes, transfer points and stockyard conveyors.

    Our Take

    Within the 562 tag-matched pieces on Projects, Product and Safety, REMA TIP TOP appears mainly in the context of wear protection and service contracts, so a dedicated item on MCube CAM signals the company is pushing harder into digital tooling rather than just consumables.

    Our Mining category coverage shows that most safety-tagged product stories focus on collision avoidance and underground monitoring; a conveyor inspection tool like MCube CAM targets a more mundane but high-frequency risk area where incremental gains can materially cut downtime and belt failure incidents.

    For operators, a vendor-driven inspection platform from REMA TIP TOP could subtly shift procurement towards bundled service-and-technology contracts for conveyors, as opposed to the traditional model of buying belt components and managing inspection in-house.

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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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