Basic3QAQC (B3Q) Toolkit

Blanks & Standards — %Bias Analysis

The Blanks & Standards module imports CRM and blank data directly from your Database or spreadsheet exports. It computes percentage bias for each standard against certified values, flags outliers using Method Precision rejection criteria, and generates control charts that track laboratory performance over time.

Core Functionality

• ✓ Simultaneous Analysis: The system analyses all elements found in a data table at once.
• ✓ Bias Calculation: It specifically identifies the bias of a lab across different analyzed elements.
• ✓ CRM Comparison: It evaluates accuracy by comparing sample results against known CRM statistics. Certain samples, such as relative density, can be forced to run as a CRM if needed.
• ✓ The “Assist”: This feature provides high-level automated advice at the end of a run, warning users about issues like “Too many outliers” or “No blanks found”.

Reporting and Outputs

• ✓ Multiple Formats: Detailed reports for every element are generated in both JMP Journal and PDF formats.
• ✓ Summary Reports: A main journal provides a summary of all analyzed elements.
• ✓ Report Types: Users can choose between a Client Report (shorter and focused on interest points) or a more detailed Internal Report.
• ✓ Customizable Storage: All journals and tables are saved to a user-specified directory path.

Method Precision

Method Precision is defined as the best level of precision a laboratory can achieve using a specific analytical method. It is expressed as a confidence interval (usually at 99.7% or 3RSD) within which results are expected to fall for a specific grade, element, and method.

Core Concept and Influencing Factors

The precision of a lab is not static; it depends on several variables:

• ✓ Analytical and Instrumental Techniques: The specific equipment and methods used.
• ✓ Sample Characteristics: The element being analyzed, its grade, the matrix, and the particle size of the sample.
• ✓ Grade Range: A precision curve model is used to calculate precision across different grade ranges using paired data.

Key Applications

• ✓ Calculating Lab Precision: It establishes a confidence interval for specific conditions, meaning that if 100 identical samples are analysed, 99.7% should fall within this range.
• ✓ Supporting Paired Data Analysis: It calculates the intercept and slope for specific elements and labs, which are then used in Twin Stream or Paired Data Analysis.
• ✓ Updating Standard Deviations: It provides a way to calculate a more realistic Standard Deviation for a lab’s actual performance on a specific CRM, rather than relying solely on the certified SD which may be unrealistic for that lab.
• ✓ Comparing Laboratories: It allows for a direct comparison of performance; a lab that analyses samples within a smaller confidence interval is considered more accurate than its competitors.

Paired Data — Duplicate & Check Sample Analysis

Paired Data Analysis is designed to calculate the precision of laboratories across various elements by comparing two readings of the same sample.

Core Functionality

• ✓ Precision Calculation: The system focuses on precision, typically using data consisting of two readings for the same sample (e.g., Pt1 and Pt2).
• ✓ Outlier Detection: Data is checked for outliers using a specific Method Precision technique. If no existing specifications are found in the control tables, the system defaults to the KSigma outlier method.
• ✓ Simultaneous Processing: Like other tools in the series, it analyzes all elements found in a data table at the same time.
• ✓ The “Assist”: This feature provides high-level advice regarding probable problem issues identified during the analysis.

Data Types and Purposes

The application handles several types of paired data, each serving a different quality control purpose:

• ✓ Pulp-Replicate Data: Samples analysed twice at the same lab to determine Intra-lab Precision.
• ✓ Check Data: Samples sent to a secondary lab to determine Inter-lab precision.
• ✓ Blind Pulp Duplicates: Remainder of pulp re-submitted to the primary lab with a different ID to test long-term precision.
• ✓ Field Duplicates: Duplicate samples taken in the field to test the sampling technique.
• ✓ Coarse Duplicates: Samples split during the preparation stage (e.g., at the 3mm milling stage) to test sample preparation at the lab.

Reporting and Outputs

• ✓ Journal Formats: Reports are generated in both JMP Journal and PDF formats.
• ✓ Main Journal: Provides a high-level overview of the analysis process for each element and includes a copy of the “Assist” results. It also contains links to more detailed reports.
• ✓ Detailed Reports: For every element analyzed, a specific detailed report is created and stored in a directory specified by the user.

Connection to Method Precision

Paired Data analysis is closely linked to Method Precision. The Method Precision script is used to calculate the intercept and slope for a specific element and lab, which is then used to evaluate the paired data stream. This relationship helps monitor precision across different grade ranges.