The performance of tactile and optical surface sensors for nano and micro coordinate measuring machines (CMMs) is currently limited by the lack of precisely characterized micro spheres, since established strategies have mainly been developed for spheres in the range of millimetres or above. Although the characterization of a full sphere has already been demonstrated, the investigations in this contribution are limited to equator measurements.

We have, therefore, recently focused our research efforts towards a novel strategy for the characterization of spheres in the sub-millimetre range. It is based on a set of atomic force microscope (AFM) surface scans in conjunction with a stitching algorithm. To obtain an uncertainty statement, the uncertainty about the shape of the reference surface needs to be propagated via the shape of the AFM tip to the actual measurement object. However, the sampling process of an AFM is non-linear and the processing of AFM scans requires complex algorithms. We have, therefore, recently begun to model the characterization of micro spheres through simulations.

In this contribution, this model is extended by the influence of the tip and reference surface. The influence of the tip's shape and reference surface is investigated through virtual and real experiments. The shape of the tip is varied by using tips with mean radii of 200 nm and 2 µm while sampling the same ruby sphere with a mean radius of 150 µm. In general, the simulation results imply that an uncertainty of less then 10 nm is achievable. However, an experimental validation of the model is still pending. The experimental investigations were limited by the lack of a suitable cleaning strategy for micro parts, which demonstrates the need for further investigations in this area.