Measurement Uncertainty and Laboratory Comparison: Essential Concepts for Quality Professionals

What is Measurement Uncertainty?

Measurement Uncertainty is a quantitative description of the reliability of a measurement result. Simply put: every measurement has an error, and uncertainty tells you "within what range the result might vary."

Key Points:

• Uncertainty ≠ Error. Error is the difference between the measured value and the true value (always unknown), while uncertainty is the range within which the measured value is likely to fall (can be estimated).
• Sources of uncertainty: instrument accuracy (the main contributor), environmental temperature and humidity, operator technique, sample homogeneity, etc.
• Representation: for example, "length = 25.4 mm ± 0.1 mm (k=2)", where ±0.1 is the expanded uncertainty, and k=2 indicates a confidence level of approximately 95%.

Why Do Quality Professionals Need to Understand Uncertainty?

1. Determining Conformance/Nonconformance: When a measurement value is close to the specification limit, uncertainty determines whether your decision is "justified." For instance, a measurement of 25.4 mm with a tolerance of 25.0～25.5 mm and an uncertainty of 0.1 mm—strictly speaking, a measurement of 25.45 mm cannot be directly judged as conforming.
2. Extension of MSA: Gauge Repeatability and Reproducibility (GR&R) is closely related to uncertainty. A good uncertainty assessment is often based on MSA data.
3. Requirement for Laboratory Accreditation: ISO/IEC 17025 explicitly requires laboratories to have the capability to evaluate and report measurement uncertainty.

What is Laboratory Comparison?

Laboratory Comparison (Interlaboratory Comparison) involves distributing the same test sample to multiple laboratories and comparing the consistency of their results. The purpose is straightforward: to see how your laboratory's test results compare to those of your peers.

Common Forms:

• Proficiency Testing (PT): Organized by authoritative institutions, with fixed frequencies (usually 1-2 times per year), and formal scoring (z-value). z-value ≤ 2 is passing, 2 < z ≤ 3 is a warning, and z > 3 is failing.
• Informal Laboratory Comparison: Organized independently between laboratories, not bound by accreditation bodies, but still valuable for reference.

Basic Steps of Comparison:

1. Select a stable comparison sample (must be uniform and stable, capable of supporting the entire comparison period).
2. Each laboratory independently tests under specified conditions.
3. Aggregate data → calculate the assigned value (usually using a robust mean or median).
4. Calculate the z-value or En-value for each laboratory.
5. Analyze deviations and implement corrective actions.

The Relationship Between Uncertainty and Comparison

The two concepts complement each other:

Practical Experience in the Workplace: If a laboratory's evaluated uncertainty is significantly smaller than the deviation between the comparison result and the assigned value, it suggests that the uncertainty assessment is overly optimistic and needs to be re-evaluated. Conversely, if the deviation is much smaller than the evaluated uncertainty, it indicates that the assessment is overly conservative and not sufficiently precise.

Quick Tips for Quality Professionals

• No Need to Calculate Uncertainty Yourself—These tasks are performed by metrology calibration personnel or laboratory engineers. The quality professional's role is to understand the reports and the impact on decision-making.
• Watch for "Abnormal" Results in Comparisons: Laboratories with z-values ≥ 3 must initiate corrective actions, and tracking the progress of these actions is the responsibility of the quality department.
• Incorporate Uncertainty into Conformance Criteria: It is recommended to specify "acceptance criteria considering uncertainty" in inspection specifications to avoid disputes.

Summary

Measurement Uncertainty and Laboratory Comparison are the two cornerstones of the ISO/IEC 17025 system. Uncertainty tells you how reliable the results are, while comparison tells you how far your laboratory is from the standard. As a quality professional, you don't need to delve into the calculations, but you should: understand uncertainty reports, monitor comparison results, and incorporate uncertainty into inspection decision-making processes.

Knowledge Number: 11.2.2

Version: v20260522

Accompanying Training Materials: Integrated Practical Training on Metrology Calibration, Gauge Management, and MSA (Complete PPT) —— Integrates calibration traceability, MSA five properties and GR&R, key points of uncertainty, and digital pathways, suitable for 3-4 hours of internal training.

Accompanying Tool Templates: Tool Kit for Metrology Calibration, Gauge Management, and MSA (Excel Templates) —— Includes ledger, calibration plan, nonconformance impact assessment, interim verification, GR&R data collection, and color-coded inspection points. Click to Download Excel Tool Kit

Author: Quality Excellence Think Tank