Robust Estimation of Optimal Sample Size for CMM Measurements with Statistical Tolerance Limits

Abstract

The paper proposes the kernel probability density function approach to estimate the distribution of measurements on a part which is measured in a coordinate measuring machine (CMM). The study is based on the experimental data derived from internal cylinder measurements. The distribution free model suggested by Wilks was used as a reference for the selection of the sample size. Three cross sections of a cylinder were measured regarding to this reference. The work defines the minimum required sample size for obtaining at least 0.95 proportion of radius variation for particular studied cylindrical part with 95% confidence level.