Extractive Process Optimizer
Diagnose extraction failures and model metallurgical process parameter scenarios
What You Can Do
You can rapidly diagnose low recovery rates by cross-referencing ore composition, process parameters, and output metrics to identify root causes. Model extraction scenarios by varying temperature, pH, residence time, and pulp density to predict yield impacts before costly pilot tests. Structure comprehensive troubleshooting reports with hypothesis chains, test sequences, and expected outcomes to guide lab validation or plant trials.
Features
cross-reference ore assay, circuit parameters, and yield data to pinpoint failure drivers
predict recovery rate changes from variations in temperature, pH, time, pulp density, and reagent dosing
document hypothesis chains, test sequences, and corrective actions with expected outcomes
separate signal from noise in inconsistent operational data to identify true performance trends
compare your process performance against published values and similar operations to validate findings
diagnose interactions across leaching, roasting, and flotation stages to trace cascading failures
structure failure investigations with evidence chains and corrective action validation plans
Example Output
Example 1: Copper Recovery Diagnosis
Input: Copper recovery dropped from 85% to 78% over two weeks. Ore grade stable at 1.2% Cu. Leach temperature 65°C, pH 2.1, residence time 4 hours.
Output:
- Hypothesis 1: Pulp density increase (45% to 48%) reducing acid contact — predicted impact: 2-3% recovery loss ✓
- Hypothesis 2: Reagent degradation (sulfuric acid age 6 weeks) — test: pH profile across circuit
- Hypothesis 3: Ore mineralogy shift — test: liberation curve on latest ore samples
- Recommended test sequence: Check pulp density first (15 min), then acid titration (30 min), then liberation if needed
Example 2: Temperature Optimization Scenario Input: Considering increasing leach temperature from 65°C to 75°C. Current recovery 82%. Energy cost increase acceptable.
Output: Scenario modeling:
- +10°C increase: predicted recovery gain 3-5% (literature: 0.3-0.5% per degree for copper sulfate)
- Acid consumption may increase 8-12% — validate with stoichiometric model
- Residence time potentially reducible by 20 min → energy offset analysis
- Risk: Scale formation above 75°C — recommend intermediate test at 70°C first
- Recommendation: Pilot test at 70°C (lower risk) before 75°C commitment
What's Included
- SKILL.md instruction file: core methodology for extraction diagnosis and scenario modeling
- Troubleshooting workflow template: hypothesis-test sequence-outcome structure with fillable fields
- Parameter sensitivity checklist: quick reference for temperature, pH, time, density, and reagent impacts on leaching/roasting/flotation
- Recovery failure diagnostic tree: decision logic for narrowing down root causes from ore, circuit, or operational sources
- Scenario modeling worksheet: structured format for documenting parameter variations and predicted outcomes before testing
Who It's For
- Extractive metallurgists — diagnosing recovery failures and optimizing leaching, roasting, and flotation circuits
- Process engineers — modeling parameter changes and planning pilot-scale tests
- Plant operations teams — troubleshooting unexpected yield drops and validating process adjustments
- Ore processing technicians — structuring root-cause investigations and documenting corrective actions
- Metallurgical consultants — benchmarking client operations and recommending optimization strategies
Best For
- Diagnosing low or declining recovery rates in copper, gold, nickel, or other metal extraction
- Modeling the impact of temperature, pH, residence time, and pulp density changes on extraction yield
- Structuring systematic troubleshooting workflows with hypothesis prioritization and test sequences
- Interpreting noisy operational data to separate true performance trends from normal variability
- Benchmarking your extraction process against literature values and similar operations
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