Quality control on assays: addressing some issues / Контроль качества анализов: решение некоторых проблем

After several decades of research, papers, conferences and undoubtedly many millions of analyses of rock and soil samples globally, we know that the success of mining projects is largely dependent on the quality of the data on which they are modelled. The importance of proper sampling, data management, quality assurance and quality control have all been extensively addressed in the literature. However, as global standards change and mining companies have to be more and more innovative to extract value out of marginal projects, it is interesting to note that basic quality control concepts are still poorly understood, misapplied and lead to constant confusion in the exploration and mining sectors.

One such issue is how to interpret the quality of the data generated by the laboratories. Most geologists are familiar with control charts but not many realise that the most common approach for their use is disputed. It doesn’t help that certified reference material providers provide conflicting advice on how to use their material and that most sampling and QA/QC courses, as well as information in the AusIMM latest Monograph on best practices are limited in their full explanation of the proper process.

Demonstrating and quantifying bias, accuracy and precision, and defining when standards really fail are critical to monitor quality and to communicate any issues between the various parties.

At the core of this lies a fundamental lack of understanding of the principles of quality control, sampling and basic statistics in the mining industry.