The Application of Statistical Quality Control to Assess the Quality of Analytical Results in Mining & Exploration

Statistical quality control of analytical results in mining and exploration: the ideas behind the talk and the video.

First published on LinkedIn, 8 February 2021: read the original.

The quality control of analytical results (assays) in our industry presents numerous challenges. For example, geological variation can, and does, impact the assessment of precision. Control charts control lines are often based on subjective decisions, and more.

This article introduces a framework called Statistical Quality Control (SQC) and is presented as a video. The video lasts 16 minutes overall and is divided into two sections:

1. A PowerPoint slide show (automated) lasting 8.5 minutes and;
2. A screen recording of an application which incorporates all that is presented in the PowerPoint.

In the PowerPoint, I:

• Contrast the challenges our industry faces compared to manufacturing.
• Introduce and suggest ways SQC may be used to assess quality.
• Discuss the significance of geological variation and its impact when quality controlling precision.
• Discuss the relevance and application of SQC to assess quality in our industry and how it may be used to provide rules for acceptance/denial, rather than the subjective approach adopted by some.
• Introduce robust statistical methods to mitigate against the influence of outliers.

If you are involved with QAQC, I urge you to view the PowerPoint.

Watch the video on Vimeo (16 minutes). The app in its second half is version 1 of QC Analytical Results; the app has moved on since.

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First published on LinkedIn, 8 February 2021. More on this topic: Control charts.