Efficient uncertainty estimation of indirectly measured geometric errors of five-axis machine tools via Monte-Carlo validated GUM framework

Saeid Sepahi-Boroujeni, J. R. René Mayer and Farbod Khameneifar

Article (2021)

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Department:	Department of Mechanical Engineering
PolyPublie URL:	https://publications.polymtl.ca/46555/
Journal Title:	Precision Engineering (vol. 67)
Publisher:	Elsevier Inc.
DOI:	10.1016/j.precisioneng.2020.09.027
Official URL:	https://doi.org/10.1016/j.precisioneng.2020.09.027
Date Deposited:	18 Apr 2023 15:00
Last Modified:	25 Sep 2024 16:34

Cite in APA 7:	Sepahi-Boroujeni, S., Mayer, J. R. R., & Khameneifar, F. (2021). Efficient uncertainty estimation of indirectly measured geometric errors of five-axis machine tools via Monte-Carlo validated GUM framework. Precision Engineering, 67, 160-171. https://doi.org/10.1016/j.precisioneng.2020.09.027
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