Metal Recovery Optimization & Diagnosis
Diagnose metal recovery losses and generate testable optimization protocols
What You Can Do
You can convert vague recovery underperformance into specific, testable hypotheses by mapping measured process data against theoretical stoichiometry. The skill guides you to isolate whether losses stem from chemical (incomplete reaction), operational (equipment malfunction), or characterization issues (ore property changes), then prioritizes loss mechanisms by impact potential and translates findings into controlled bench-scale or pilot test protocols.
Features
systematically differentiate between extraction losses (leaching, flotation, roasting) and product recovery losses (precipitation, filtration, smelting)
rank suspected loss mechanisms by potential impact and likelihood based on process data and ore characteristics
compare actual recovery against theoretical yields to pinpoint chemical or operational deviations
generate structured bench-scale and pilot-scale experiments with defined variables, controls, and success metrics
estimate the recovery percentage gain achievable from each loss mechanism remediation
document findings and recommendations for management approval of process modifications
contextualizes your process performance against literature data and comparable mill operations
structures root cause findings for quality and compliance reporting requirements
Example Output
Example 1: Low Flotation Recovery Diagnosis
- Problem: Cu recovery dropped 3% month-over-month
- Diagnosis Output: Flotation recovery 78% (target 88%). Leach efficiency unchanged at 94%. Root cause: flotation concentrate grade 22% Cu vs. baseline 25% Cu suggests altered froth stability or collector depletion.
- Hypothesis: Insufficient collector dosing due to ore hardness increase from new supplier
- Test Protocol: Increase collector by 15%, measure concentrate grade and recovery in 4-hour pilot flotation with new ore batch
Example 2: Smelter Product Loss Analysis
- Problem: Overall recovery 82% vs. 87% target
- Diagnosis Output: Leach recovery 96%, flotation recovery 88%, but smelting recovery only 79%. Loss calculated at 8% of final product weight.
- Hypothesis: Excessive slag carry-over or incomplete settling in reverberatory furnace
- Test Protocol: (1) Reduce temperature 50°C and measure slag viscosity, (2) extend settling time by 20 min, (3) sample slag composition before/after—target <3% Cu in slag vs. current 4.2%
What's Included
- SKILL.md instruction file with structured diagnostic framework:
- Process loss mapping template (extraction vs. recovery stage classification):
- Stoichiometric balance worksheet with mass-balance calculations:
- Hypothesis prioritization matrix (impact × likelihood × implementation effort):
- Test protocol template (bench-scale and pilot-scale experimental design):
- Root cause documentation checklist for compliance and management reporting:
Who It's For
- Process metallurgists troubleshooting mill recovery underperformance or new ore sources
- Operations managers justifying capital investment in process modifications or equipment upgrades
- Quality assurance and regulatory compliance specialists documenting root cause investigations
- Mining engineers designing pilot-scale experiments to validate optimization hypotheses
- Extractive metallurgy researchers benchmarking process efficiency against peer sites or literature
Best For
- Diagnosing unexpected drops in metal recovery (2–5% below baseline or target)
- Prioritizing among multiple suspected loss mechanisms when recovery data is incomplete
- Designing controlled experiments to isolate chemical, operational, or ore property causes
- Documenting technical justifications for process modifications or operational changes
- Troubleshooting performance changes when ore source, supplier, or seasonal conditions shift
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