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

Viewed

Total article views: 1,006 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
623 338 45 1,006 27 24
  • HTML: 623
  • PDF: 338
  • XML: 45
  • Total: 1,006
  • BibTeX: 27
  • EndNote: 24
Views and downloads (calculated since 22 Apr 2021)
Cumulative views and downloads (calculated since 22 Apr 2021)

Viewed (geographical distribution)

Total article views: 949 (including HTML, PDF, and XML) Thereof 949 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 27 Mar 2024
Download
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.