CMM Measurement Uncertainty Reduction via Sampling Strategy Optimization

Uncertainty is a key concept in any environment which involves measurements to ensure process quality: a trade-off has to be found between measurement costs, which increase as uncertainty lowers, and costs related to measurement errors. In mechanics, geometrical conformance is a common requirement. Two similar standards series deal with the problem of uncertainty in geometrical error estimate: ASME B89.7.3 and ISO 14253. Geometrical inspection is often performed by means of a “Coordinate Measuring Machine” (CMM). For a CMM, a trade off between measurement and errors costs may be found by optimizing the sampling strategy. In this work a cost function will be proposed as support for finding a trade-off between measurement uncertainty and costs. This function may be optimized by means of an heuristic algorithm. The method will involve repeated measurements of calibrated parts to evaluate uncertainty (like in ISO/TS 15330-3). A case study will be proposed.