ABB’s Automation Extended: staged DCS upgrades for brownfield mines explained
Reviewed by Tom Sullivan

First reported on International Mining – News
30 Second Briefing
ABB has launched its Automation Extended programme as a strategic evolution of its distributed control systems, aiming to let mines introduce new automation capabilities progressively while preserving existing DCS investments and control logic. The approach is pitched at brownfield process plants with ABB’s large installed DCS base, where operators want to add advanced process control, data integration and remote operations without major shutdowns or rip-and-replace projects. For mining engineers, this signals a stronger focus on staged upgrades of concentrators, smelters and material handling systems rather than full control system overhauls.
Technical Brief
- Automation Extended is framed as an evolution of ABB’s existing DCS architecture, not a replacement platform.
- Programme scope centres on integrating “future automation capabilities” into current control layers while retaining validated control logic.
- Data integration is a core element, signalling closer coupling of DCS with higher-level information and optimisation systems.
Our Take
ABB’s Automation Extended sits alongside its recent work on Boliden’s Aitik tailings facility and Vulcan Energy’s Lionheart project, signalling that ABB is standardising an integrated electrification–automation stack that can be ported across both conventional and emerging critical-materials operations.
The long-running ABB–Fenner Conveyors collaboration in Australian mines suggests Automation Extended will likely be engineered to plug into existing ABB drive, hoist and conveyor ecosystems rather than replace them, which matters for brownfield upgrade strategies.
Within our 858 Mining stories, ABB appears frequently as a systems integrator rather than a point-solution vendor, so Automation Extended is likely to be positioned as a coordination layer that helps miners stitch together disparate ABB and non-ABB products into a more coherent control environment.
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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