Articles | Volume 10, issue 1
https://doi.org/10.5194/jsss-10-101-2021
https://doi.org/10.5194/jsss-10-101-2021
Regular research article
 | 
22 Apr 2021
Regular research article |  | 22 Apr 2021

Measurement uncertainty assessment for virtual assembly

Manuel Kaufmann, Ira Effenberger, and Marco F. Huber

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Latest update: 13 Feb 2025
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Short summary
Virtual assembly (VA) is a method for the quality prediction of assemblies considering local form deviations of relevant geometries. Point clouds of measured objects are registered in order to recreate the objects’ hypothetical physical assembly state, which is strongly influenced by the measurement uncertainty of individual points. Thus, we studied the propagation of uncertainties by VA. The results reveal larger propagated uncertainties by VA compared to the unconstrained Gaussian best fit.
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