A new optimized uncertainty evaluation applied to the Monte-Carlo simulation in platinum resistance thermometer calibration

The basic steps for evaluating the measurement uncertainty according to ISO approach, propagation of uncertainties and Monte-Carlo simulation are investigated. These methods during a case study in a temperature secondary laboratory for uncertainty assessment of a platinum resistance thermometer calibration are illustrated. For considering some sources of variability in the measurement which may not be appropriately treated and the computational efficiency in simulation model, a simulation optimization and a Genetic algorithm are proposed to establish lower and upper bounds as limit standards for simulation results.