Abstract
Abstract Inspection is commonly used to scrutinize the quality of manufactured products against established standards and specifications. However, the quality and reliability of many inspection processes are contaminated by various uncertainties. One of the prominent sources for measurement uncertainties is due to the imperfection of a measuring device and the confounded effect of its imperfection with geometric characteristics of a measured feature. To ensure the quality and reliability of any inspection process, measurement uncertainties need to be addressed for all data acquisition activities. A method is also needed to identify and decouple the effect of confounded uncertainties. If this can be done, then the collected data can be properly adjusted and a more meaningful analysis result can be drawn. In this paper, the issue of uncertainty identification for machine calibration and dimension measurement using artifacts with spherical feature is discussed. Analytical models are derived to first assess and then decouple the confounded effect of both types of uncertainties. Finally, case studies are used to illustrate the general application and the effectiveness of the derived models in assessing and decoupling the confounded effect, and thus, reducing the measurement uncertainties.
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