435
Views
19
CrossRef citations to date
0
Altmetric
Original Articles

Predicting the ultimate tensile strength and wear rate of aluminium hybrid surface composites fabricated via friction stir processing using computational methods

, , &
Pages 1707-1726 | Received 14 Jun 2021, Accepted 14 Sep 2021, Published online: 28 Sep 2021
 

Abstract

In the present study, aluminium hybrid surface composites were prepared by incorporating boron carbide (B4C) and Aluminium oxide (Al2O3) ceramic particles via the Friction Stir Processing (FSP) route. Tool rotational speed, Tool traverse speed, Axial force, and Reinforcement ratio were the chosen process parameters. Response Surface Method (RSM) based Central Composite Design (CCD) was used to conduct the experimental trials. A second-order regression equation was developed for the responses, ultimate tensile strength (UTS), and wear rate (WR). Statistical tests were performed to check the adequacy of the regression models. The effect of process parameters on the responses was studied. It was found that tool traverse speed was the most dominant process parameter, followed by tool rotational speed, axial force, and reinforcement ratio. The optimal process parameters for the responses were found using a genetic algorithm, where the regression equations from RSM were used as the objective function.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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 432.00 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.