Real-Time Flotation Grade-Recovery Optimization
Uses online flotation sensing such as LIBS chemistry, froth imaging, and pulp measurements with automated or model predictive control to adjust operating conditions and reagents as ore variability changes. The workflow optimizes concentrate grade versus recovery, helps meet product specifications such as lithium and iron limits, improves gold or mineral recovery, and supports downstream stability and reagent efficiency.
Business Blueprint
GROUNDEDReal-time flotation optimization keeps mineral recovery, concentrate grade, and circuit stability on target as ore and operating conditions change.
The Problem
Flotation circuits are hard to keep at the right grade-recovery balance when disturbances and ore variability change the process; poor flotation can reduce recovery, lower product grade, increase reagent cost, and make the circuit harder to operate.
Plant operations teams
High variability and poor flotation operation make the circuit more difficult to control and operate day to day.
Metallurgical and process-control teams
They need multi-variable control that can meet recovery and grade requirements while staying within plant constraints.
Flotation operators
Without circuit-level control, operator attention is pulled toward local, per-cell adjustments rather than global circuit-wide optimization.
Cost of Inaction
Reduced recovery efficiency, low grade quality product, high input disturbances, increased use/cost of reagents, and high variability within the process.
Process Fit
Back-office process automationAs-Is
Operators and metallurgical teams manage flotation through existing regulatory controls, local adjustments, instrumentation, and control-room dashboards while feed, water balance, and other disturbances affect mass pull, grade, and recovery.
To-Be
Online process observations, virtual analyzers, and plant instrumentation feed an advanced control layer that updates setpoints continuously, coordinates mass pull, air, froth depth, and related controls, and gives operators circuit-wide oversight through SCADA while respecting plant constraints.
Human Checkpoints
- Technical and economic feasibility assessment before commissioning — Process-control and metallurgy leads
- Design, implementation, validation, and handover to site team — Operations, process-control, and metallurgical teams
- Control-room monitoring and intervention through SCADA dashboards — Flotation operators
Systems Touched
Business Cycle
Upstream
- Reliable process observations, virtual online analyzers, and instrumentation feeds are needed so the control layer can update actions from current circuit conditions.
- The circuit needs agreed plant constraints and recovery/grade requirements before automated setpoint changes are allowed.
- Upstream flow-rate and water-balance disturbances must be understood because they affect the mass-pull capacity of the flotation circuit.
Downstream
- Improves downstream flowsheet stability when flotation control performs well.
- Moves operator attention from local cell-by-cell adjustments to global circuit-wide adjustments under different operating conditions.
- Supports recovery and grade requirements while keeping the flotation circuit within plant process constraints.
Value Evidence
- Recovery performanceIMPROVED
- Downstream flowsheet stabilityIMPROVED
- Flotation circuit stabilisationIMPROVED
- Operator focus on circuit-wide controlIMPROVED
Adoption Journey
LEVEL 1 — QUICK WIN
Gate: Prove value on one flotation circuit using feasibility assessment, control-interface prototyping, and available circuit data.
Outcome: A credible business case, agreed controllable variables, and operator-visible prototype before changing live control.
LEVEL 2 — STANDARD
Gate: Prove commissioned control can operate within plant constraints with operator oversight.
Outcome: A production control layer that stabilizes flotation and updates setpoints while operators monitor through existing control-room systems.
LEVEL 3 — ADVANCED
Gate: Prove the approach holds grade-recovery performance across changing operating conditions and creates downstream stability.
Outcome: Circuit-wide optimization replaces local firefighting and supports a more stable downstream flowsheet.
Detailed per-level builds in the solution spectrum below
Risk & Governance
New control technology can strain site adoption, especially when resources or access are limited.
Posture: Use staged design, implementation, validation, and transition to the site team for ongoing operation.
Automated grade-recovery expansion is not complete without the needed froth and pulp sensing capability.
Posture: Treat froth and pulp sensor installation, plus further exploitation of the dynamic flotation simulation, as prerequisites for expansion.
The controller must not chase recovery or grade targets outside safe plant operating limits.
Posture: Keep plant process constraints as hard guardrails for automated control actions.
Control-room trust depends on clean integration with plant instrumentation and operator displays.
Posture: Integrate through OPC and expose the operator interface through SCADA dashboards.
Operating Intelligence
How it works
AI runs the operating engine in real time.
Humans govern policy and overrides.
Measured outcomes feed the optimization loop.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Sense
Step 2
Optimize
Step 3
Coordinate
Step 4
Govern
Step 5
Execute
Step 6
Measure
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI senses, optimizes, and coordinates in real time. Humans set policy and override when needed. Measurements close the loop.
The Loop
6 steps
Sense
Take in live demand, capacity, and constraint signals.
Optimize
Continuously compute the best next allocation or action.
Coordinate
Push those actions into systems, channels, or teams.
Govern
Humans set policies, objectives, and overrides.
Authority gates · 1
The system may not change grade-recovery priorities, impurity limits, or downstream capacity constraints without approval from the metallurgist or operations leadership. [S2][S3]
Why this step is human
Policy decisions affect the entire operating envelope and require organizational authority to change.
Execute
Run the approved operating loop continuously.
Measure
Measured outcomes feed back into the optimization loop.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in Real-Time Flotation Grade-Recovery Optimization implementations:
Key Players
Companies actively working on Real-Time Flotation Grade-Recovery Optimization solutions:
Real-World Use Cases
Model predictive control for Lihir flotation circuit gold recovery optimization
Software continuously checks the flotation process, predicts recovery and grade outcomes, and adjusts several operating settings so more gold sticks to bubbles and is recovered from the slurry.
Proposed automated grade-recovery control with froth and pulp sensing
Future sensors would watch the froth and pulp, and the control system would automatically adjust the circuit to balance copper grade and recovery.
LIBS-based real-time flotation chemistry optimization for spodumene concentrate
A laser analyzer looks at the lithium slurry while it is flowing and quickly tells operators what elements are in the concentrate, so they can adjust flotation before product quality drifts.