Leaching Circuit Optimizer
Diagnose leaching failures and optimize extraction parameters using metallurgical data analysis
What You Can Do
You can rapidly diagnose leaching circuit problems by submitting operational data, mineralogical assays, and performance metrics to Claude, which analyzes root causes, models parameter optimization scenarios, and evaluates alternative solvent systems or circuit configurations. Rather than relying on expensive trial-and-error testing, you'll receive data-driven recommendations for temperature, pH, residence time, pulp density, and solvent alternatives tailored to your ore mineralogy and equipment constraints.
Features
analyzes operational data to identify why recovery dropped, linking failures to specific variables (temperature creep, pH drift, mineralogy changes, equipment degradation)
evaluates how changes to residence time, pulp density, temperature, and solvent concentration impact extraction efficiency
compares performance, cost, and safety trade-offs between leaching chemistries (cyanide vs. thiourea, sulfuric vs. chloride)
suggests equipment modifications, flow-sheet changes, or staged leaching configurations for different ore types
identifies scaling issues between lab bench tests and production circuits based on kinetic and hydrodynamic principles
compares actual performance against design specifications to flag mechanical problems or maintenance needs
structures failure analysis, recommendations, and risk assessment for engineering and management stakeholders
Example Output
Example 1: Cyanide Leaching Recovery Drop
Input: Gold recovery dropped from 92% to 78% over 3 weeks; pH rose from 11.2 to 12.1; dissolved oxygen steady at 8 mg/L; ore type unchanged.
Output:
- Root Cause: Elevated pH inhibits cyanidation kinetics; likely caused by increased carbonate in ore feed or insufficient acid dosing.
- Immediate Actions: Reduce pH to 10.8–11.0 using sulfuric acid; verify ore sourcing; check acid injection pump calibration.
- Recovery Forecast: 90–91% recovery within 48 hours post-correction.
Example 2: Sulfuric Acid Leaching Circuit Design
Input: Designing new circuit for laterite ore; lab data shows 85% extraction at 80°C, 2 hours residence time; current equipment sized for 100 t/h.
Output:
- Recommended Configuration: Staged leaching (2 × 10 m³ reactors in series); temperature control via jacket heating; air agitation at 0.5 m³/min.
- Parameter Set: 85°C, pH 0.5–1.0, 120 minutes residence time (add 20% safety margin over lab conditions for scale-up variability).
- Equipment Gaps: Require pH monitoring loop and acid addition system; estimate 15% efficiency loss vs. lab due to temperature gradients—compensate with extended residence time.
What's Included
- SKILL.md: Full leaching diagnosis framework, troubleshooting workflow, and metallurgical reference data
- Operational Data Template: Structured checklist for capturing circuit configuration, feed assays, process parameters, and performance metrics
- Root Cause Decision Tree: Diagnostic flowchart linking symptoms (recovery drop, viscosity issues, foaming) to most likely root causes
- Parameter Optimization Worksheet: Blank template for modeling scenarios (temperature, residence time, solvent concentration) and predicted outcomes
- Solvent Comparison Matrix: Side-by-side performance, cost, and safety evaluation framework for common leaching chemistries
Who It's For
- Minerals processing engineers troubleshooting production leaching circuits
- Metallurgists designing new leaching systems for different ore deposits
- Operations supervisors diagnosing unexpected recovery losses or equipment underperformance
- Consulting engineers evaluating solvent alternatives or circuit retrofits
- Mining technical teams preparing failure analysis and improvement proposals for stakeholder review
Best For
- Diagnosing sudden or gradual recovery drops in cyanide, sulfuric acid, or chloride leaching
- Optimizing process parameters (temperature, pH, residence time, pulp density) before pilot testing
- Evaluating solvent substitution or circuit redesign scenarios using operational data
- Troubleshooting scale-up problems between laboratory and production circuits
- Preparing technical reports with root-cause analysis and engineering recommendations
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