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High-frequency electrically-assisted turning: Application to aluminium

conference contribution
posted on 2024-07-31, 14:43 authored by Ahmad Abdul-Kadir, Konstantinos BaxevanakisKonstantinos Baxevanakis, Anish RoyAnish Roy
The manufacturing of engineering alloys has been developing over the years to meet the increasing demand for more efficient techniques and high-quality products. The electrically and ultrasonically-assisted manufacturing processes have been gaining attention due to their potential in reducing energy consumption and improving machined surface qualities. This research explores the capability of the combination of these techniques using continuous and pulsed currents at high frequencies to improve the machinability of metals. Electric current is applied to the workpiece through the cutting tool to harness the electroplastic effect with local softening due to high current density at the cutting zone. The electric current was delivered into the workpiece in continuous and in pulses at different peak current values, with low cutting speed and feed rate. Ultrasonic vibrations were added to amplify the current frequency and reduce the cutting force. Results showed a reduction in cutting force and surface roughness when electric current was applied in pulses at a high peak current. The study showed that electrically-assisted turning has great potential to help improve the machinability of materials.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2023)

Volume

2

Pages

13 - 20

Publisher

Springer

Version

  • AM (Accepted Manuscript)

Rights holder

© The Author(s), under exclusive license to Springer Nature Switzerland AG

Publisher statement

This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-49421-5_2. Use of this Accepted Version is subject to the publisher’s Accepted Manuscript terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms

Publication date

2024-05-29

Copyright date

2024

ISBN

9783031494208; 9783031494215

ISSN

2211-0984

eISSN

2211-0992

Book series

Mechanisms and Machine Science

Language

  • en

Editor(s)

Andrew D. Ball; Zuolu Wang; Huajiang Ouyang; Jyoti K. Sinha

Depositor

Dr Konstantinos Baxevanakis. Deposit date: 3 July 2024

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