Effect of sampling strategy on uncertainty and precision of flatness inspection studied by dynamic minimum deviation zone evaluation

Abstract

Evaluation of geometric deviations for the purpose of determining compliance with specified form tolerances requires the acquisition of numerous measured data points and extensive computation to accurately characterize the inspected part’s geometry. If there are not enough data points measured or when the measured points are not distributed properly on the measured surface a high level of uncertainty in characterizing the inspected part’s geometry can be expected. However, increasing the number of data point also significantly increases the computational time and also increases computational uncertainty by adding to instability of the optimization process required to find the minimum deviation zone. Selections of number and location of the measured date points need to be performed by understanding the significance of these two sources of uncertainties. This paper discussed the effect of sampling procedure on uncertainty and precision of flatness inspection.