Assay Sampling Protocols for Industrial Metal Scrap Valuation
Assay sampling protocols establish true dry weight and payable metal content, directly governing settlement values, working capital allocations, and lender borrowing base limits.
Fundamental Sampling Error
Meaning
Inherent statistical variance represents the minimum unavoidable sampling error caused by the physical differences between individual particles in a bulk batch. Managing the fundamental sampling error is essential for securing representative samples from gold and base metal shipments. This error can never be eliminated completely but can be minimised by reducing the particle size before splitting.
Gy Theory
Pierre Gy established the mathematical equations that describe this sampling variance. The equation links the error directly to the mass of the sample and the size of the largest particles. This formula shows that as the particle size increases, the potential for error grows exponentially.
Analysts use this model to determine the correct mass required for a reliable assay.
Error Mitigation
Reducing the particle size by crushing and grinding is the primary way to control this variance. When the rock is milled to a fine powder, the minerals are distributed more evenly. This allows a smaller sub-sample to represent the entire lot with high accuracy.
Mineral Heterogeneity
Ores with highly concentrated minerals, such as gold vein material, suffer from high variance. A single large gold grain in a small sample can cause an artificially high assay value, while its absence causes a false negative. This nugget effect is a direct result of the physical differences between the gold grains and the waste rock.
Controlling this variance requires fine milling. If the grinding is insufficient, the analytical results will fluctuate wildly between duplicate runs.