Statistical Inference on Part Geometry

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This research combines statistical theory with engineering technology to develop confidence levels for part inspections. The goal is to extend previous research on cylindricity to all solid geometric primitives. The research will employ maximum likelihood estimation of part geometric parameters, such as the radius of a sphere, to estimate the probability of geometry conforming to a specific model. These models will incorporate expected random and systematic deviations from nominal values and will be developed in the context of the manufacturing process. Once the measurements are complete, the theory developed will permit the statisically characterization of the impact of part geometry deviations. The research will enable the determination of several important values, among them is the number of sample points required to assure specified probabilities on type I and II errors. Individually inspected parts will be employed to draw inferences about the remainder of the parts in the production system. The relation between individual components and uninspected parts will be developed from the statistical theory of tolerance regions.