ABSTRACT
In precision engineering, the demands for close tolerances and accurate dimensions on workpieces are challenging to manufacture but critical for reliable function when assembled into a mechanical system. These dimensions have to be confirmed by measurement, and such measurements always include disturbances that cause the measurement results to deviate. Typically, the resulting deviations are small, but they can be large enough to prevent a proper decision about a workpiece being taken. Therefore, 414an appropriately rigorous estimation of measurement uncertainty is essential in the production process. This chapter is about measurement uncertainty and follows the most recent Guide to the Expression of Uncertainty in Measurement, commonly called the GUM. From elementary single variable statistics through uncertainty propagation, the chapter shows the reader how to estimate uncertainty in the result of a measurement process. The concept of propagation of uncertainty distributions and Monte Carlo methods of uncertainty estimation are also presented.
