Zugriffsnummer 41777
Dokumenttyp Konferenzartikel
Peer Review unbekannt
Sprache Englisch
Titel Determination of measurement uncertainty by Monte Carlo simulation
Autor(in); Institution
Heißelmann, Daniel; 5.3, Koordinatenmesstechnik, PTB-Braunschweig
Franke, Matthias; 5.3, Koordinatenmesstechnik, PTB-Braunschweig
Rost, Kerstin; 5.3, Koordinatenmesstechnik, PTB-Braunschweig
Wendt, Klaus; PTB-Braunschweig, retired staff
Kistner, Thomas; Carl Zeiss IMT, Oberkochen, GERMANY
Schwehn, Carsten; Hexagon Metrology GmbH, Wezlar, GERMANY
Quelle/Jahr Advanced Mathematical and Computational Tools in Metrology and Testing XI:(2018), 192 - 202
Schriftenreihe Series on advances in mathematics for applied sciences: 89
Herausgeber(in)
Forbes, Alistair B.; National Physical Laboratory, Teddington, UK
Eichstädt, Sascha; PSt, Präsidialer Stab, PTB-Braunschweig
ISBN 978-981-3274-29-7 ; 978-981-3274-31-0
DOI
Verlag New Jersey: World Scientific Publishing
Konferenzangaben Advanced Mathematical and Computational Tools in Metrology and Testing XI (AMCTM 2017), Glasgow, 29-31, August, 2017, UK
Freie Schlagworte Measurement uncertainty ; Monte Carlo-Simulation ; virtual coordinate measuring machine
Zusammenfassung Modern coordinate measurement machines (CMM) are universal tools to measure geometric features of complex three-dimensional workpieces. To use them as reliable means of quality control, the suitability of the device for the specific measurement task has to be proven. Therefore, the ISO 14253 standard requires, knowledge of the measurement uncertainty and, that it is in reasonable relation with the specified tolerances. Hence, the determination of the measurement uncertainty, which is a complex and also costly task, is of utmost importance. The measurement uncertainty is usually influenced by several contributions of various sources. Among those of the machine itself, e.g., guideway errors and the influence of the probe and styli play an important role. Furthermore, several properties of the workpiece, such as its form deviations and surface roughness, have to be considered. Also the environmental conditions, i.e., temperature and its gradients, pressure, relative humidity and others contribute to the overall measurement uncertainty. Modern coordinate measurement machines (CMM) are universal tools to measure geometric features of complex three-dimensional workpieces. To use them as reliable means of quality control, the suitability of the device for the specific measurement task has to be proven. Therefore, the ISO 14253 standard requires, knowledge of the measurement uncertainty and, that it is in reasonable relation with the specified tolerances. Hence, the determination of the measurement uncertainty, which is a complex and also costly task, is of utmost importance. The measurement uncertainty is usually influenced by several contributions of various sources. Among those of the machine itself, e.g., guideway errors and the influence of the probe and styli play an important role. Furthermore, several properties of the workpiece, such as its form deviations and surface roughness, have to be considered. Also the environmental conditions, i.e., temperature and its gradients, pressure, relative humidity and others contribute to the overall measurement uncertainty. Currently, there are different approaches to determine task-specific measurement uncertainties. This work reports on recent advancements extending the well-established method of PTB's Virtual Coordinate Measuring Machine (VCMM) to suit present-day needs in industrial applications. The VCMM utilizes numerical simulations to determine the task-specific measurement uncertainty incorporating broad knowledge about the contributions of, e.g., the used CMM, the environment and the workpiece.Currently, there are different approaches to determine task-specific measurement uncertainties. This work reports on recent advancements extending the well-established method of PTB's Virtual Coordinate Measuring Machine (VCMM) to suit present-day needs in industrial applications. The VCMM utilizes numerical simulations to determine the task-specific measurement uncertainty incorporating broad knowledge about the contributions of, e.g., the used CMM, the environment and the workpiece.
Themenbereich der Metrologie Länge, dimensionelle Metrologie

Zitierung

Heißelmann, D., Franke, M., Rost, K., Wendt, K., Kistner, T., & Schwehn, C. (2018). Determination of measurement uncertainty by Monte Carlo simulation. Advanced Mathematical and Computational Tools in Metrology and Testing XI (AMCTM 2017), Glasgow, 29-31, August, 2017, UK. https://doi.org/10.1142/9789813274303_0017

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