Statistical Methods For Mineral Engineers May 2026

Conclusion: You cannot accurately sample coarse material with small masses. This explains why "scoop sampling" of conveyors is fundamentally flawed without proper mass reduction protocols (riffle splitters, rotary dividers). Once the mine feeds the plant, the mineral engineer shifts from geology to metallurgy. Here, Statistical Process Control (SPC) is the standard. The Moving Range Chart Most mineral processes have autocorrelation (tonnage now depends on tonnage 5 minutes ago). Traditional X-bar-R charts are less useful; Exponentially Weighted Moving Average (EWMA) charts are superior because they detect small, persistent shifts. Design of Experiments (DOE) Classical "one factor at a time" (OFAT) testing is statistically inefficient. Mineral engineers often face interactions (e.g., pH and collector dosage interact to affect recovery).

You are designing a sampling protocol for a leach feed. The grind size is $P_{80} = 75 \mu m$. You take a 200g pulp for analysis. The variance is acceptable. Now you need to sample crushed ore at $P_{80} = 10mm$ (10,000 $\mu m$). The particle size ratio is $10,000 / 75 = 133$. The mass required must increase by $133^3 \approx 2.35 \text{ million}$ times. $200g \times 2,350,000 = 470,000 kg$. Statistical Methods For Mineral Engineers

Statistically, we have redundant data. You have 3 assays (Feed, Con, Tail) and 2 flow rates (Feed, Tail). The system is over-determined . Modern metallurgical accounting uses minimization of weighted sum of squares to adjust measurements so they obey the conservation of mass (tonnage and metal). Here, Statistical Process Control (SPC) is the standard

In the world of mineral engineering, decisions have billion-dollar consequences. A mill that operates at 85% recovery instead of 90% can render a deposit uneconomical. A misinterpreted assay grid can lead to the development of a barren hill. Unlike chemical engineering (which deals with pure reactants) or mechanical engineering (which deals with deterministic tolerances), mineral engineering must contend with heterogeneity . Design of Experiments (DOE) Classical "one factor at