Taguchi Full Factorial Design of Experiments Optimisation of Cutting Parameters for Energy Efficiency and Surface Roughness during the Dry Turning of EN19 Material

ISSN Print: 2331-4222
ISSN Online: 2331-4249
www.scirp.net/journal/wjet
E-mail: [email protected]

Citations

"Taguchi Full Factorial Design of Experiments Optimisation of Cutting Parameters for Energy Efficiency and Surface Roughness during the Dry Turning of EN19 Material"
written by Nicholas Tayisepi, Albert Nkulumo Mnkandla, Godfrey Tigere, Oscar Gwatidzo, Winnie Mutenhabundo, Emmanuel Ndala, Lovelace Makakatanwa Wagoneka,
published by World Journal of Engineering and Technology, Vol.12 No.2, 2024

has been cited by the following article(s):

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[1]	A dynamic surface roughness prediction system based on machine learning for the 3D-printed carbon-fiber-reinforced-polymer (CFRP) turning Journal of Intelligent Manufacturing, 2025 DOI:10.1007/s10845-025-02602-8