Comparison of the GUM and Monte Carlo methods on the flatness uncertainty estimation in coordinate measuring machine

Abstract

In engineering industry, control of manufactured parts is usually done on a coordinate measuring machine (CMM), a sensor mounted at the end of the machine probes a set of points on the surface to be inspected. Data processing is performed subsequently using software, and the result of this measurement process either validates or not the conformity of the part. Measurement uncertainty is a crucial parameter for making the right decisions, and not taking into account this parameter can, therefore, sometimes lead to aberrant decisions. The determination of the uncertainty measurement on CMM is a complex task for the variety of influencing factors. Through this study, we aim to check if the uncertainty propagation model developed according to the guide to the expression of uncertainty in measurement (GUM) approach is valid, we present here a comparison of the GUM and Monte Carlo methods. This comparison is made to estimate a flatness deviation of a surface belonging to an industrial part and the uncertainty associated to the measurement result.