Improving Quality Assurance and Quality Control Practices - Basic Methodology Using Worked Examples

The need for quality assurance and quality control (QA/QC) in the sampling and assaying of minerals is fundamental to the reliability and confidence of a mineral resource estimate, reserve estimate and possibly profitability of a mine. In spite of this, QA/QC practices in the mining industry are commonly applied poorly, or misunderstood. As New Leaders, we should aim to correct the poor practices and become fully informed on appropriate procedures. This paper uses worked examples that show the usefulness and importance of best practice QA/QC procedures. Fundamentals of reviewing the performance of the laboratory by examining the results of client inserted standard reference material (standards), blank material and duplicate samples are discussed. To do this, three examples from Australian data sets have been used. For each example, simple and efficient plotting techniques are suggested with subsequent evaluations of each plot. The first case study compares the results of internal standards from a laboratory with blind standards (where the expected value is unknown to the laboratory) submitted by the client. It was demonstrated over time that the laboratory was unintentionally analysing the internal standards in a different manner to the remainder of the sample batch. In this example, not understanding the cause of a high negative laboratory bias could have led to poor understanding of the deposit's grade and in the extreme a proposed mining operation may have reached operational stage with a subeconomic grade. The second case study discusses the quality of blank material submitted by a mining operation to monitor cross-contamination within the laboratory. The blank material contained background levels of the element under investigation. This created uncertainty in the assay results, which could have led to the need for additional assays and drilling programs. Finally, the third case study demonstrates the use of the relative paired differences (RPD) technique to cross-validate the results from duplicates and repeat analyses from two laboratories. The three examples given show either laboratory or operational error. If left undetected, each example could have had serious implications for the mineral resource estimate and ultimately, the mining operation. These examples are not isolated occurrences; poor QA/QC practices are an industry wide problem exacerbated by rapid staff turnover and increased contractor positions on-site. New Leaders must be equipped with a thorough grounding in QA/QC best practices to improve its application and confidence in the results of sample analysis.