Coordinate measuring machine (CMM) plays a more and more important role in the flatness evaluation. The pre-processing for eliminating error data is an important process to improve the quality of flatness evaluation. So, flatness uncertainty estimation becomes a key problem. To solve the problem, a flatness uncertainty estimation method based on data elimination is presented. Firstly, a method for excluding the error data based on statistical theory is expatiated with the consideration of probability theory and mathematical statistics. Secondly, details of calculating flatness uncertainty based on least-square method are analyzed. Then the measured 3-dimensional data are processed so as to put the excluding method into use. So the error data can be deleted and the flatness uncertainty can be decreased and can achieve a good evaluation quality. Finally, an example is given and the result shows that the method proposed in this paper is feasible.

The new-generation standards of Geometrical Product Specifications (GPS) take the measurement and verification of manufactured parts according to the duality principle. The Specification Surface Model (SSM) is a simulation model of the actual manufactured part which plays a decisive role in the process of duality verification. The existing methods, however, have not been found to carry out much related research on the generation of SSM. This paper presents a method to generate the SSM for the characteristic of planar feature with flatness under the standards of GPS. The mathematical model of the flatness tolerance is firstly established. Secondly, in order to get the simulation points to simulate the actual characteristics of the manufactured parts, both of the functional requirements of the parts and the influences of the manufacturing process are considered. And then the simulation points under the normal distribution are generated within their tolerance zone by computer. By using the approximation method of the least-squares SSM is then obtained. Finally, an example is used to illustrate the proposed method.