7. Conclusions

Measurement uncertainty and metrological traceability are interdependent concepts. The evaluation of uncertainties of measurement results is essential to ensure that they are reliable and comparable. Moreover, the process that involves the modeling of measurement systems and evaluation of their uncertainties is of great importance for the metrologist as it constitutes a tool for the management of the measurement laboratory, since it can indicate exactly where to invest to get better, more qualified results.

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The GUM and the application of the LPU continue to be the most used and widespread methodology for bottom-up uncertainty evaluation in metrology. It is adopted worldwide and provides a strong base for comparability of measurement results between laboratories. On the other hand, a new version for the GUM is currently under revision. This version should be aligned with its supplements in a more harmonized way, incorporating concepts from Bayesian statistics and resolving some inconsistencies. As a consequence, if the mentioned distribution-free coverage intervals are maintained, results for the expanded uncertainty will be greatly overestimated compared to the current version of the GUM.

In this way, the best alternative for a more realistic and lean uncertainty assessment would be through a numerical simulation using the Monte Carlo method, which should lead to a smaller and more reliable uncertainty result.
