Field samples are arguably the most important part of mine assessment and planning. Incorrect information will result in resource failures and mining plans. The reliability of your data is critical. MineSight Torque will offer the QA/QC module, a flexible, easy-to-use, built-in quality assurance and control tool designed to validate and determine the precision and accuracy of laboratory samples. To this end, it provides graphical and analysis functionality for analytical samples, standards, blanks and duplicates.
The QA/QC backstage allows you to create, edit, import the attributes, laboratories, analytical methods, measurement methods, blank samples and standards, as shown in Figure 1.
Once the project configuration is finalized, the user can manage all data with quality assurance and control in three different categories: samples, shipments and certificates. Each of these data types can be viewed separately allowing them to be managed in a simpler workflow (Figure 2).
Within QA/QC, there are three sets of graphs, analyzes and statistics for each sample type. Each chart type can be filtered by start and end date, attribute, lab, etc. Once the desired chart type and filters are selected, the data will appear in the browser together with the chart (Figure 3). In the following figures, statistics and specific analyzes of the data represented in the graph are shown.
The Blanks chart displays a dataset of blank samples arranged by date on the X axis and the resulting grade measured by the laboratory on the Y axis. This chart is useful for detecting the presence of contamination within the laboratory. As blank samples should have a zero content value, any content measured by the laboratory can be considered a contaminant. It is still possible to add a limit of detection (LOD) line at a user-defined value (Figure 4).
The Standards graph is similar to the Blanks graph, and displays the measured values of the standard samples. Field and laboratory standards can be imported and thus validated in order to establish the accuracy of the chosen laboratory's measurement practices and processes (Figure 5).
The Duplicates chart presents a set of original and duplicated value pairs in scatterplot form. Thus, it is possible to establish a baseline for the accuracy of the measurement processes of the chosen laboratory (Figure 6).
In this way, all new samples will go through the QA/QC validations at MSTorque and after being accepted, they will be imported into MSTorque to be used in the following processes.
Fast sample visualization and validation will allow you to better leverage your sampling expenses while increasing your productivity, saving time spent on spreadsheets and graphs by third-party software, avoiding the use of CTRL+C and CTRL+V that can generate some kind of erroneous correlation.
The new QA/QC module in MSTorque allows you to assess the quality of laboratory measurements for each method and for each attribute. For more detailed information about QA/QC at MSTorque, please contact our team via email client-relations@prominas.net.
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