B3Q QAQC Toolkit
From sample to certainty — automated QAQC for analytical laboratories.
Most laboratories track QAQC in spreadsheets — error-prone, inconsistent between analysts, and impossible to audit. B3Q replaces manual workflows with reproducible, statistically rigorous analysis that meets international best practices.
Three Specialised Modules
Blanks & Standards
%Bias Analysis & CRM Monitoring
Automates CRM monitoring from raw data to auditable report. Generates Shewhart control charts, calculates %Bias, detects outliers statistically, and builds a cumulative history of laboratory accuracy.
For: Lab managers, quality managers, resource estimators
More ↓Method Precision
Slope & Intercept Calculation
Calculates lab-specific precision from your own replicate data using robust regression. Replaces generic textbook values with measured performance, enabling meaningful control limits and uncertainty estimates.
For: Lab managers, accreditation auditors, resource estimators
More ↓Paired Data
Duplicate & Check Sample Analysis
Evaluates field duplicates, pulp duplicates, and umpire check samples with scatter plots, QQ-plots, difference plots, and precision statistics. Distinguishes geological variability from analytical error.
For: Resource estimators, exploration geologists, Competent Persons
More ↓
Blanks & Standards — %Bias Analysis
The problem: Every certified laboratory analyses CRMs and blanks alongside production samples, but most track results in fragmented spreadsheets. Formulas break, outliers get deleted without documentation, and assembling performance evidence for auditors takes hours.
B3Q automates the entire CRM monitoring workflow in a single, guided process. Import your data from Excel, CSV, JMP, or directly from your LIMS database. B3Q loads lab-specific specifications from Control Tables — certified values, recommended standard deviations, and detection limits — then calculates percentage bias for every CRM measurement. Blanks are evaluated separately against a detection limit multiplier to flag contamination automatically.
Shewhart-style control charts are generated per standard per laboratory, complete with warning and action limits. Statistical outliers are identified, separated into a documented "rejected" table, and the analysis re-runs on the cleaned dataset with before-and-after statistics. A summary tabulation shows pass/fail status per standard, ready for your QAQC report.
Results are automatically appended to a cumulative history table. Over time this builds %Bias-over-time trending, CRM heatmaps, and filterable tabulations — auditable evidence that grows with every analysis run.
Deliverables
- Branded PDF report with all charts, tables, and parameters
- Control charts per CRM per lab, ready for audit presentation
- Summary tabulation of pass/fail status per standard
- Documented outlier exclusions with before/after statistics
- Cumulative history table with %Bias trending over time
Method Precision — Slope & Intercept Calculation
The problem: When a laboratory reports 5.2 g/t, how precise is that number? Most labs use generic textbook values that don't reflect actual performance — or don't measure precision at all. Without lab-specific method precision, you cannot set meaningful control limits or assess analytical uncertainty in resource models.
B3Q calculates lab-specific and method-specific precision using replicate measurements from your routine production data. Import your duplicate assays, then B3Q cleans the data, groups by standard, and calculates the mean and root-mean-square standard deviation for each group.
The Jackknife multivariate outlier detection method identifies replicate pairs with unusually high or low variability relative to their grade. A bivariate regression of √(RMS sd) against Mean produces the precision slope — a single number that characterises how your lab performs across the full grade range. An interactive report lets you compare new vs existing precision curves and accept or reject the updated value.
Deliverables
- Lab-specific precision slope and intercept values
- Jackknife outlier analysis with documented exclusion criteria
- Interactive regression chart (√RMS sd vs Mean)
- Side-by-side comparison of new vs existing precision curves
- Summary table with full audit trail
- Branded PDF report of the complete analysis
Paired Data Analysis
The problem: Paired results — field duplicates, pulp duplicates, check samples — come back in spreadsheets. Manual comparison is subjective, with no statistical basis for concluding results are "acceptable" and no way to separate geological variability from analytical error.
B3Q provides a complete, multi-step workflow for evaluating paired assay data with statistical rigour. Import and match pairs, then generate scatter plots with 45° reference lines for instant visual assessment. Data is cleaned with every exclusion documented — records below detection limits, missing values, and exact duplicates are counted and removed transparently.
Choose from multiple outlier detection methods: the kSigma Interactive method with real-time visual feedback as you adjust the threshold, or the Method Precision method that defines grade-dependent acceptance limits using the slope from Module 2. After outlier removal, B3Q generates difference plots, distribution histograms, QQ plots (before and after), and precision plots with 10%/20% precision lines overlaid.
A comprehensive summary tabulation — total records, exclusions, outlier method, percentage outliers, final precision metrics — goes directly into a Competent Person's report or QAQC appendix.
Deliverables
- XY scatter plots with 45° reference line (before and after cleaning)
- Interactive outlier detection with adjustable thresholds
- Difference plots (absolute and relative) showing bias patterns
- QQ plots and distribution histograms
- Precision plot with 10%/20% lines and method precision curve
- Overall summary tabulation ready for inclusion in reports
- Cumulative precision history table
Why B3Q Over Spreadsheets?
| Capability | Spreadsheets | B3Q Toolkit |
|---|---|---|
| Reproducibility | Formulas break, get overwritten, vary between analysts | Same calculation every time, every analyst |
| Audit trail | Who changed what? Unknown | Full history with timestamps |
| Speed | Hours per element suite | Minutes for entire suite |
| Outlier handling | Subjective deletion | Statistical methods with documentation |
| Historical trending | Manual chart updates | Automatic accumulation and plotting |
| Multi-lab comparison | Build from scratch each time | Built-in MultiWay analysis |
| Control charts | Manual setup in Excel | Generated automatically with limits |
Trusted by Certified Laboratories
Used by analytical labs and multinational mining companies across Southern Africa since 2006. Built on the proven SAS JMP statistical engine.
Supports compliance with ISO 17025, JORC, SAMREC, and NI 43-101 reporting requirements.
Training Programme (3-Day Course)
A comprehensive course that builds understanding from data fundamentals through to full B3Q Toolkit proficiency. Participants work with their own laboratory data on Day 3.
| Day | Topic | What You Learn |
|---|---|---|
| Day 1 | Data Exploration with JMP | Navigate JMP, manage and clean data, explore distributions and visualisations, assess data quality before analysis |
| Day 2 | Measurement System Analysis | Statistical foundations of precision and accuracy, understanding variation, gauge studies, what the numbers mean and why they matter |
| Day 3 | B3Q Toolkit Hands-On | Full walkthrough of all three modules using your own lab data, Control Table setup, interpreting reports, capturing results to history |
Includes comprehensive user documentation per module and one day of free training with purchase.
Best Practices Overview
Frequently Asked Questions
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Do I need JMP to use B3Q?
Yes. B3Q is built as a set of JMP add-ins that run on the SAS JMP statistical platform. You need a current JMP licence installed on your desktop. No server infrastructure or cloud services are required — B3Q runs entirely on your local machine.
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What data formats are supported?
B3Q imports data from Excel (.xlsx/.xls), CSV, and JMP data tables. It can also connect directly to your LIMS database via ODBC, eliminating manual data export/import cycles.
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Can B3Q connect to my LIMS?
Yes. B3Q supports direct database integration via ODBC. This allows you to pull lab data directly from your LIMS into the software, eliminating manual data handling and reducing transcription errors.
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How long does setup take?
Installation is straightforward — download the add-ins and install them in JMP. Initial setup involves configuring your Control Tables with your laboratory's certified reference values, specifications, and element mappings. Octoplus provides installation support and training to get you operational quickly.
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Does B3Q support ISO 17025 compliance?
B3Q generates the documented evidence that ISO 17025 auditors require: full audit trails, documented outlier criteria, before-and-after statistics, cumulative performance history, and branded reports with all parameters recorded. The toolkit supports — but does not replace — your laboratory's quality management system.
Get Started with B3Q
Whether you need automated QAQC analysis, expert consulting, or hands-on training, we can help your laboratory achieve consistent, auditable results.
Octoplus Information Solutions (Pty) Ltd
PO Box 2564, Brooklyn Square, 0075, Pretoria, South Africa
+27 12 346 4823 |
www.octoplus.co.za