A Guide to Measurement Uncertainty and Traceability

Measurement Uncertainty and Traceability illustration image

What Is Measurement Traceability?

Measurement traceability is the ability to trace individual measurement results to national or international standards. According to the International Vocabulary of Metrology (VIM), traceability is:

“The property of a measurement result whereby the result can be related to a reference through a documented, unbroken chain of calibrations, each contributing to the measurement uncertainty.”

Establishing traceability ensures that measurements performed in one laboratory, facility, or country can be compared confidently to those taken elsewhere. It is the backbone of consistent quality and standardization across global operations.

Why Is Traceability Important?

Establishing traceable measurements supports a range of operational and regulatory objectives:

Compliance with industry standards and regulations such as ISO/IEC 17025, ISO 9001, GxP and FDA requirements

Confidence in measurement data used for decision-making and reporting

Consistency in quality control across multiple sites or over time

Legal and technical defensibility of measurement results

The Role of Calibration

Calibration is essential for establishing measurement traceability. It is a comparison of an instrument's output with a known reference under controlled and stable conditions. The purpose is to determine how much the instrument deviates from the reference value – without making any adjustments during the process.

Rather than altering the instrument, calibration quantifies its measurement error. This information enables users to assess performance, apply necessary corrections, and determine whether the instrument operates within acceptable tolerances.

Defining Measurement Uncertainty

Measurement uncertainty refers to the quantified doubt that exists about the result of any measurement. It provides a range within which the ‘true value’ is expected to lie, along with a confidence level indicating how certain we are of that range.

For example:

A reading of 24.45^oC ± 0.2^oC at 95% confidence means that the true value is expected to lie between 24.25 and 24.65 ^oC, with a 95% level of confidence.

It is important to distinguish uncertainty from other commonly misunderstood terms:

Error is the known deviation between the measured value and the reference.

Uncertainty is the estimate of doubt surrounding that measurement.

Accuracy and precision are qualitative or misused terms and should be replaced with quantitative descriptors such as uncertainty and specification.

Why Is Measurement Uncertainty So Critical?

Understanding and managing measurement uncertainty is essential for:

Ensuring product quality and safety – especially in industries with tight tolerances

Assessing risk– particularly when measurements are used to make critical decisions

Setting realistic process limits – uncertainty expands the range of possible values, affecting compliance with defined tolerances

Take the example of a pharmaceutical cleanroom environment where humidity must be controlled between 40% and 60%rh. If a sensor reads 50%rh with an uncertainty of ±5%, the actual humidity could be anywhere from 45% to 55%. If the uncertainty increases to ±10%, the range becomes 40% to 60% – potentially bordering on non-compliance.

How Is Measurement Uncertainty Calculated?

Measurement uncertainty is determined by evaluating all known contributors to error in a system. These can include:

Instrument resolution and stability

Reference standard uncertainty

Environmental influences (e.g. thermal gradients)

Repeatability and reproducibility

Operator technique

Drift over time

Each contributor is quantified – using either Type A evaluations (statistical methods) or Type B evaluations (non-statistical estimates) – and expressed in terms of a standard uncertainty. These are then combined using the root sum square method:

U = k × √(u₁² + u₂² + u₃² + ...)

Where:

U is the expanded uncertainty

u values represent standard uncertainties from different sources

k is the coverage factor (typically k = 2 for 95% confidence)

Practical Considerations

To ensure robust uncertainty estimation and traceability:

Calibrate at operating conditions whenever feasible

Follow standardized procedures and ensure proper documentation

Use properly trained personnel and maintain equipment as per manufacturer guidance

Understand the difference between calibration and adjustment

Avoid overreliance on manufacturer specifications – they may not reflect real-world performance

Final Thoughts

Measurement uncertainty and traceability are not abstract concepts – they are practical tools for ensuring confidence, compliance, and consistency in all aspects of measurement. Organizations that invest in understanding and managing these elements are better equipped to make informed decisions, reduce risk, and maintain quality in even the most demanding environments.

To find out more, contact our team of calibration experts today.