The new accreditation standard ISO/IEC 17025: 1999 requires laboratories to estimate the uncertainty of measurement.

“I used to be uncertain – now I’m not so sure”

Uncertainty does not inspire confidence, but from an analytical laboratory perspective, uncertainty defines the range of the values that could reasonably be attributed to an analytical result. Uncertainty arises as a result of random effects, such as short-term fluctuations in temperature, relative humidity and power source variations or a result of systematic effects, such as instrumental drift between calibrations. When laboratories report uncertainty it gives a quantitative indication of the quality of the analytical results, and it allows the user of the result to:

• Assess its reliability.
• Assess the confidence that can be placed on a result, when comparing it with a limiting value defined in a specification or regulation.
• Compare analytical results e.g., from different laboratories.
• Assess the “fitness for purpose” of the result.

The complexity involved in estimation of uncertainty of measurement in the case of testing varies considerably from one test field to another and also within one field itself. A less metrologically rigorous process than that which can be followed for calibration can also often be used. Clause 5.4.6.2 of ISO/IEC 17025 allows for these factors. The degree of rigor needed in an estimation of uncertainty of measurement depends on factors such as:

• Requirement of the test method.
• Requirement of the client.
• There are narrow limits on which decisions conformance to a specification are based.

If the test method is well recognized (ASTM, ISO) and specifies limits to the values of the major sources of uncertainty of measurement, and specifies the form of presentation of calculated results, the laboratory is considered to have satisfied this clause by following the test method and reporting instructions. Clause 5.4.6.3 states that uncertainty components/budgets are a combination of many factors that may include, but are not limited to:

• Sampling – where in-house or field sampling form part of the specified procedure, effects such as random variations between different samples and any potential for bias in the sampling procedure.
• Storage conditions – where test sample is stored prior to analysis, the storage conditions may affect the analytical result.
• Properties and condition of item being tested.
• Equipment used – limits of accuracy of instruments used in the measurement process i.e., analytical balance.
• Analytical method used – assumed stoichiometry, reagent purity, instrument settings, blank correction.
• Reference standards.
• Reference materials.
• Environmental conditions.
• Calibration.
• Operator effects.
• Known physical characteristics of components such as, coefficient of thermal expansion. These often can be looked up in engineering and scientific handbooks.
• Data processing.

Estimates of other components can only be based on experience or other information, and are called Type B evaluation. Values belonging in this category may be derived from:

• Previous measurement data.
• Experience with or general knowledge of the behaviour and properties of relevant materials and instruments.
• Manufacturer’s specifications.
• Data provided in calibration and other certificates.
• Uncertainties assigned to reference data taken from handbooks.

The measurement uncertainty for a given calibration is the combination of all the type A and type B components of the uncertainty budget.