Quasi-Monte Carlo Simulation Methods for Measurement Uncertainty
Modern dimensional metrology, which deals with the art and science of measuring manufactured parts in industry, is one current source of important problems involving geometric computations. For this reason, evaluating the performance of software and hardware for the Coordinate Measuring Machine (CMM) system is invaluable, both for making decisions about the possible purchase of a CMM system and for assessing its use in the inspection of manufactured parts. This performance evaluation can be based on a model in which the sources of uncertainty for such a system are identified and described, and their combined effect on the overall measurement result is estimated. This paper constructs a simple, new mathematical model for measurement uncertainty and uses quasi-Monte Carlo methods to simulate the relationship between the measurement result and the sources of error in order to predict the measurement uncertainty. This approach also is applied to the testing of algorithms of a CMM software system.
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