What are the most significant sources of uncertainty in laboratory measurements

Short answer: The most significant sources of uncertainty vary with each type of test, measurement, and measurement system. However, some of the most common sources of uncertainty that significantly affect measurement results include:

• Repeatability,
• Reproducibility,
• Resolution,
• Drift or Stability,
• Bias,
• Reference Standard Uncertainty,
• Environmental Contributors, and
• Method-specific Contributors.

Every test and measurement is different. Likewise, the most significant contributors will not be the same.

Some tests and measurements will be heavily influenced by repeatability and reproducibility. Some will be significantly affected by drift or bias while others are significantly impacted by instrument resolution or environmental factors.

The only way to know which sources are the most significant is to evaluate measurement uncertainty and calculate the percentage of the total variance (i.e. Factor Analysis) each source of uncertainty has on the combined standard measurement uncertainty.

Examples

Example 1: Drift, Bias, and Reference Standard Uncertainty

Stable, repeatable, and reproducible measurements are likely influenced by drift, bias, calibration uncertainties.

For example, some precision multimeters have high resolution and the capability to repeat measurement results with low variability. In this scenario, factors like drift, bias, or reference standard uncertainty will be the most significant source of uncertainty.

Example 2: Repeatability and Reproducibility

Unstable, less repeatable measurements are likely influenced by Type A uncertainties, such as repeatability and reproducibility.

For example, pipetting is a skill. Typically, there is a degree of variability in reproducible results between different operators. Therefore, repeatability and reproducibility are usually significant sources of uncertainty.

Another example is calibrating a torque wrench. Obtaining repeatable measurements is a skill, and the variability in reproducible results between operators is likely. Therefore, repeatability and reproducibility are usually significant sources of uncertainty.

Example 3: Environmental Contributors

Measurements that are sensitive to environmental conditions will likely have environmental factors such as temperature, pressure, etc as the most significant sources of uncertainty. For example, a CMM is capable of producing accurate and repeatable results. However, environmental factors such as temperature can affect its performance making it a significant  source of uncertainty.

Another example is volumetric flow. No matter how accurate or repeatable the device is, results can be significantly impacted by environmental factors such as temperature and pressure. In my experience, the reference temperature has been the biggest factor when evaluating interlaboratory comparison results. When the reference temperature is unknown or different and the results are not standardized to normal temperature and pressure (NTP), the effects on measurement uncertainty are very significant.

Example 4: Resolution

Equipment that lacks enough resolution to see variability in results will result in resolution being the largest contributor to uncertainty.

For example, the measurement uncertainty of a low resolution, dial caliper measuring a gauge block will have its resolution as the most significant contributor. Typically, the uncertainties related to the gauge block, the measurement process, and environmental conditions will be significantly less than the resolution of the caliper. Therefore, the uncertainty will be dominated by the resolution. Even the estimate of measurement repeatability will be limited by the resolution if all the repeated results are the same (i.e. no variation). See JCGM 100:2008, section F.2.1.1 for guidance to estimate repeatability in this scenario.