AspenTech on targeted AI in mining: practical deployment lessons for engineers
Reviewed by Tom Sullivan
First reported on International Mining – News
30 Second Briefing
Targeted AI deployments in mining are shifting from broad “digital transformation” to tightly scoped, outcome-driven use cases, with Emerson’s Aspen Technology business reporting faster ROI where operators focus on short-term, measurable wins. Ed Bardo, Senior Principal Solution Consultant for Metals & Mining at AspenTech, cites examples such as AI-powered optimisation of specific unit operations and asset health monitoring rather than site-wide rollouts. For engineers, the message is to ring‑fence problems with clear KPIs, deploy modular AI tools, and scale only once value is proven.
Technical Brief
- AspenTech’s mining deployments concentrate AI on individual unit operations such as grinding, flotation and thickening.
- Asset health models are trained on site-specific historian data rather than generic OEM datasets.
- Ed Bardo notes operators often start with soft sensors to infer unmeasured variables in real time.
- Supervisory control layers use AI outputs as advisory setpoints, leaving base-loop PID logic unchanged.
- Many sites run AI models in “shadow mode” to validate predictions before closing control loops.
- Data quality work typically precedes modelling, including tag rationalisation, bad-value filtering and time-alignment of signals.
- Integration is usually via existing DCS or SCADA interfaces, avoiding major changes to field instrumentation.
- Lessons are feeding into modular templates for common mining flowsheets, shortening configuration on subsequent sites.
Our Take
International Mining also features prominently in coverage of IMARC and the World Mining Congress 2026, signalling that Aspen Technology’s AI messaging is likely being positioned for the same senior decision-maker audience shaping digital roadmaps for major miners.
The IMARC-related pieces in our coverage emphasise AI for critical minerals supply chains, suggesting Emerson’s Aspen Technology may find strongest traction where operators need to squeeze more throughput and predictability from existing assets rather than greenfield builds.
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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