Measurement Error Reduction in Automated Inspection of Free-Form Surfaces Defined by Cubic B-Spline

Abstract

Historically, inspection data were used to determine whether or not a manufactured part met specifications. If the part did not meet specifications, it was reworked or scrapped. Now, inspection devices like coordinate measuring machines (CMMs) can provide data about how far a part is in or out of tolerance. The data are now being used to make manual adjustments to machining offsets and process parameters. However, the quality and reliability of many inspection processes are contaminated by various measurement errors. One of the prominent sources for measurement errors is due to the imperfection of a measuring device and the compound effect of its imperfection with geometric characteristics of a measured feature.To ensure the quality and reliability of any inspection process, measurement errors need to be identified and reduced by minimizing the effect of the compound errors. If this can be done, the quality of collected data can be enhanced and a more meaningful analysis result can then be drawn. In this paper, the issues of measurement error identification and reduction for machine calibration and dimension measurement, when dealing with uniform bicubic B-spline surface features are discussed. Analytical models are derived to first assess and then decouple the compound effect of both types of errors. Finally, case studies are used to illustrate the application and the effectiveness of the derived models in assessing and decoupling the compound effect and thus reducing the measurement errors.