Project Details
ALEMON - "Differentiation between measurement uncertainty and model error in the description of measurement processes"
Subject Area
Measurement Systems
Term
since 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 508590565
Since every measurement process is inherently subject to uncertainty, the further use of measurement data subject to uncertainty means that derived statements are also uncertain. This can lead to erroneous decisions. If the measurement uncertainty when inspecting a produced feature is too high and the feature is close to the specification limits, the decision as to whether the feature is within or outside the specification is risky. As a result, parts that are within specification may be rejected during inspection (α-failure) or vice versa (β-failure). In the second case, this means that defective parts are passed on to the customer, where they may cause damage for which the producer is responsible. Both cases, depending on production and defect costs, can lead to a high economic loss. Since the risk of wrong decisions cannot be determined and thus controlled without knowledge of the measurement uncertainty when collecting measurement data, measurement values without measurement uncertainty information are worthless. Previous methods for determining the measurement uncertainty use a model of the measurement as the basis for specifying the measurement uncertainty. With this model, the measurement uncertainty is determined based on the natural fluctuations of the input variables. Systematic deviations within the measurement process are taken into account when determining the measurement uncertainty, provided that they cannot be eliminated. Deviations between reality and model in the sense of a model error, however, are often not taken into account when determining the measurement uncertainty. As a result, the specified measurement uncertainty may be overestimated and costs may be incurred due to the incorrect specification of the manufacturing tolerance range. For the exact determination of the measurement uncertainty, it is therefore necessary to differentiate between the measurement uncertainty and the model error.
DFG Programme
Research Grants