Performance metrics for testing statistical calculations in interlaboratory comparisons

Abstract

Interlaboratory comparisons are the most powerful tools for determining the competences of laboratories performing calibrations and testing. Performance metrics is based on statistical analysis, which can be very complex in certain cases, especially for testing where transfer standards (samples) are prepared by the pilot laboratory. Statistical quantities are calculated using different kinds of software, from simple Excel applications to universal or specific commercial programmes. In order to ensure proper quality of such calculations, it is very important that all computational links are recognized explicitly and known to be operating correctly. In order to introduce a traceability chain into metrology computation, the European project EMRP NEW 06 TraCIM was agreed between the EC and the European Metrology Association (EURAMET). One of the tasks of the project was also to establish random datasets and validation algorithms for verifying software applications in regard to evaluating interlaboratory comparison results. The statistical backgrounds for resolving this task, and the basic concept of the data generator are presented in this paper. Background normative documents, calculated statistical parameters, boundary conditions for generating reference data sets are described, as well as customer interface.

Experimental Evaluation of Ball Bar Standard Thermal Properties by Simulating Real Shop Floor Conditions

“…Stated uncertainty [14] is expanded uncertainty given by the CMM producer and checked by a verification test. The uncertainty has been proved by an interlaboratory comparison [15] within the project.…”

Verification of Statistical Calculations in Interlaboratory Comparisons by Simulating Input Datasets

“…[10,11]. In order to enable validation of statistical calculations in all possible types of interlaboratory comparisons, we have developed a special software application [12,13] that allows the user to choose between different types of comparisons in calibration and testing. The user can select boundary conditions for generating data sets and statistical quantities to be calculated.…”

“…Statistical quantities that are calculated in an evaluation process of intercomparison results are described in detail in [4,[12][13][14][15]. Only a short overview is given here in order to establish a statistical background for the software verification process.…”

“…Selection of proper criterion depends on the case of an interlaboratory comparison and is described in [4,[12][13].…”

Different Approaches in Uncertainty Evaluation for Measurement of Complex Surfaces Using Coordinate Measuring Machine

“…Mutual recognition arrangement in metrology requires complete traceability from the measurement in the user's laboratory through accredited laboratories to national primary standards and further to the definition and realization of measuring unit. From the stand point of legal metrology it is easy to achieve through regional and international key and supplementary intercomparisons [12], [13].…”