237
Views
4
CrossRef citations to date
0
Altmetric
Research Article

Experimental research of the effect of face milling strategy on the flatness deviations

, ORCID Icon, ORCID Icon &
Pages 235-244 | Received 29 May 2020, Accepted 28 Aug 2020, Published online: 11 Sep 2020
 

ABSTRACT

In this paper the dependencies between face milling strategy of EN AW6082-T6 aluminum alloy samples, with difference thicknesses (6, 8, and 12 mm) and two cold rolling directions, and flatness deviations were presented. Three strategies of milling included different proportions of material removed from both sides of the plates. This approach allowed to control the proportions of residual surface stresses on both sides of the specimens, which were created by the cold rolling process. The face milling strategy involving the symmetrical removal of material from both sides of the sample resulted in the best results of flatness deviations. This strategy was most effective for both rolling directions. It has been observed that the use of an appropriate face milling strategy is particularly important for thin sheets (6 mm thick). In the case of thicker plates (12 mm thick), the selected strategy has less impact on the final values of flatness deviations.

Acknowledgments

The authors would like to acknowledge Eng. Roman Jakubek and MSc. Eng. Jan Westa from the company Mechanika - Radmor Sp. z o.o. in Gdynia, Poland, for supplying materials for this work and substantive consultations.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 561.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.