The construction of random-fuzzy variables from the available relevant metrological information

Approaches other than the probabilistic approach recommended by the guide to the expression of uncertainty in measurement (GUM) have been proposed during the recent past for uncertainty expression and estimation. The approach based on random-fuzzy variables (RFVs) appears to be the most promising approach since it is based on the theory of evidence, which encompasses probability theory as a particular case. The correctness of the final uncertainty estimation quite directly depends on the way the RFVs are built, which depends on the available relevant metrological information. After briefly recalling the fundamentals of the RFV approach, this paper discusses how the available relevant information should be exploited to attain correct results.