D¨¦senfant, M. and Priel, M.
2006 Measurement, 39(9): 841-848
Measurement uncertainty evaluation; Interlaboratory comparisons; Repeatability and reproducibility studies; Proficiency testing; Method validation
D¨¦senfant, M. and Priel, M., (2006), "Road map for measurement uncertainty evaluation", Measurement, 39(9): 841-848.
Abstract:
Various methods and tools are now available to evaluate measurement uncertainty. These new methods comply with the concepts and recommendations of the Guide to the expression of uncertainty in measurement (GUM). In this paper, the authors introduce several alternatives for laboratories, notably those based on intra-laboratory and interlaboratory approaches.
The intra-laboratory approaches will include the "modelling approach" (application of the procedure described in Chapter 8 of the GUM) and the "single-laboratory validation approach".
The interlaboratory approaches, based on collaborative studies, are the "interlaboratory validation approach" and the "proficiency testing approach". The former uses the statistical methods described in ISO 5725 Accuracy (trueness and precision) of measurement methods and results, and the recent ISO Technical Specification 21748 Guidance for the use of repeatability, reproducibility and trueness estimates in uncertainty estimation. The second approach will certainly play an important role in the near future. Several testing laboratories are involved in proficiency testing scheme and are interested in the possibility of using the results of these exercises and the data accumulated over time to evaluate their uncertainty. The most important application area of these approaches certainly concerns medical laboratories. Recently, medical laboratories have been encouraged to evaluate their uncertainty of analysis, either by regulation or on a voluntary basis in the accreditation process.
In this paper, the authors present the four methods, their coherence, and their common requirements: a clear definition of the measurand and a technical analysis of the measuring process to identify most of the uncertainty factors.
