Anticipate how changing feed will impact throughput, recovery, and costs.
MillMax optimizes plant performance by translating changing feed conditions into clear operating targets
so control rooms stay stable while economics improve.
Keep the circuit closer to its best operating window without destabilizing control.
Improve economic performance while existing APC/MPC maintains stability.
What’s Broken Today?
Plants react to feed changes after performance drifts, not before
Many critical variables (e.g., true grind state, effective hardness, mineral response) are difficult or impossible to measure directly.
Optimization decisions rely heavily on operator intuition and experience, making results inconsistent across shifts.
How MillMax Works
From raw data to actionable stockpile truth
1. Inputs
Required Data Sources
- Plant historian data (throughput, power, recovery, reagent usage, key control tags)
- Feed characterization from upstream (e.g., DynaMax / OreMax outputs or equivalent)
- Circuit configuration and operating limits (constraints, setpoint ranges)
Optional data sources (nice to have):
- Laboratory results (assays, grind size, mineralogy, recovery tests)
- Equipment availability and maintenance signals
- Cost sensitivities (energy, reagents, penalties)
2. Outputs
What Users Receive:
- Feed-aware operating targets (throughput, grind, reagent strategy, recovery trade-offs)
- Soft sensor estimates for variables that are difficult to measure directly
- Clear recommendations explaining what to change, why, and what to expect
- Continuously or at a configurable cadence, updating as feed conditions and plant response change
The Deployment Workflow
Ingest live plant data and feed characteristics
from upstream systems.
Estimate unmeasured process states
using soft sensors and validated models.
Predict plant response
to changing feed and operating conditions.
Evaluate economic trade-offs
(throughput vs recovery vs reagent/energy cost).
Recommend optimal operating targets
within safe and defined constraints.
Present explainable guidance
to operators or send setpoints to the DCS/SCADA.
Learn from outcomes
as the plant responds, refining recommendations over time.
Top KPIs Impacted
Recovery improvement:
typically 0.5–5% depending on circuit and variability
Throughput stability:
reduced oscillations and fewer corrective interventions.
Reagent efficiency:
up to 30% savings demonstrated in pilots.
Energy efficiency:
improved kWh/t through better operating-point selection.
Case Story
A gold operation experienced frequent recovery swings due to feed variability. MillMax used feed-aware soft sensors and economic optimization to recommend adjusted operating targets, resulting in a 1.6% recovery uplift while maintaining stable control. (Pilot outcome).Ready to turn feed variability into predictable performance?
Book a walkthrough to learn how MillMax converts real-time feed signals into stable circuit performance and better throughput and recovery.
45 Minute Discovery Session
understand circuit objectives, variability drivers, and current control strategy
Opportunity Assessment
review available plant and feed data to size upside
Tailored Walkthrough
show MillMax recommendations in the context of your circuit and constraints
Primary Users
Metallurgists, Control Room Operators, Processing Manager, Plant Manager, Technical Services Manager