Application of GUM Supplement 2 to uncertainty estimation of five-axis CNC machines geometric error parameters identification using the SAMBA method

摘要

This paper investigates the uncertainty estimation of the machine tool identified geometric errors parameters. The analysed quantities are obtained through the simulation of the scale enriched reconfigurable uncalibrated master balls artefact (SAMBA) calibration process. The uncertainties are estimated using two approaches described in the GUM Supplement 2: the generalized uncertainty framework (GUF) and adaptive Monte Carlo method (MCM). The associated coverage factors are calculated. The results obtained by both approaches are compared and examples of estimated probability density plots are presented. The results show that in case of investigated (iterative) measurement the GUF cannot be validated with MCM. However, the latter method gives an opportunity to calculate uncertainty of identified errors.