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    Jameson Cell and AI-driven APC: circuit design and retrofit notes for plant engineers

    July 16, 2026|

    Reviewed by Tom Sullivan

    First reported on International Mining – News

    30 Second Briefing

    Glencore Technology is promoting the Jameson Cell as a key enabler for AI-driven advanced process control (APC), arguing that flotation circuit hardware must be reconfigured, not just overlaid with new software. The company points to the cell’s short residence time, small footprint and consistent froth conditions as features that generate cleaner, higher-frequency data streams for machine-learning control platforms. For plant designers and metallurgists, this shifts APC discussions towards circuit layout, sensor placement and retrofit strategies around Jameson Cells to stabilise and optimise flotation performance.

    Technical Brief

    • For other flotation circuits, similar decoupling of contacting and separation zones could ease APC deployment.

    Our Take

    Across recent coverage, Glencore Technology has been repositioning the Jameson Cell from niche cleaner/scavenger roles into primary rougher duties, which gives AI-driven advanced process control (APC) systems a larger lever on overall plant recovery and energy intensity than if they were only trimming at the margins.

    The Mogalakwena North and Fruta del Norte deployments in our database show the Jameson Cell already operating in low mass pull and high-recovery strategies; layering AI/APC on top of these tighter operating windows is likely to demand higher-frequency, more reliable instrumentation and data reconciliation than many brownfield concentrators currently run.

    With 2415 tag-matched ‘Projects’/‘Product’ pieces in our database, Glencore Technology’s push to link the Jameson Cell to AI and artificial intelligence themes stands out as one of the relatively few equipment stories explicitly framing flotation hardware as a digital-control platform rather than just a metallurgical upgrade.

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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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