Proposed Validation Method for the Uncertainty Estimation of CMM Straightness Measurement Using PSO Algorithm and SMC Technique

Straightness uncertainty in dimensional metrology is an important parameter in precision engineering. Optimization in straightness measurement using soft algorithm techniques is widely encountered solution in coordinate metrology. In this work, we report on the uncertainty in the CMM measurement of straightness feature for a slab surface. Straightness points have been measured precisely in 3D using CMM at NIS. The straightness has been analyzed using a Particle Swarm Optimization (PSO) algorithm. The probability density distribution of the measured spatial straightness was developed using a Sequential Monte Carlo (SMC) technique; forming probability density histogram with 95% confidence level representing an uncertainty in the straightness measurement. Comparison with relevant reports showed and approved that our results are more accurate since we used a computationally efficient modified SMC technique and PSO algorithm. This work confirms that the developed strategic methodology can achieve validation method successfully for straightness uncertainty. Moreover, uncertainty in straightness measurement has been estimated and found to be suitable of the proposed validation method for CMM dimensional metrology.