Optimisation of surface roughness when CNC Turning of Al-6061: Application of Taguchi Design of experiments and genetic algorithm / Boppana V. Chowdary...[et al.]

V. Chowdary, Boppana and Jahoor,, Riaz and Ali,, Fahraz and Trishel, Gokool (2019) Optimisation of surface roughness when CNC Turning of Al-6061: Application of Taguchi Design of experiments and genetic algorithm / Boppana V. Chowdary...[et al.]. Journal of Mechanical Engineering (JMechE), 16 (2). pp. 77-91. ISSN 1823-5514 ; 2550-164X

Abstract

Surface roughness is often used as a measure to identify surface integrity of machined parts. The objective of this study was to optimise part surface roughness by investigating the effects of cutting speed, feed rate, depth of cut and tool nose radius on the surface roughness of Aluminium 6061. A five-level L25 Taguchi orthogonal array was modified to accommodate a four-level process parameter. The optimization was conducted on the prediction model generated by use of Response Surface Methodology (RSM) together with Analysis of Variance (ANOVA), and confirmation test validated the predicted values obtained from the Genetic Algorithm (GA). The best combination of parameters for minimum surface roughness was found to be a cutting speed of 250 m/min, feed rate of 0.03 mm/rev, depth of cut of 0.2 mm and tool nose radius of 0.503 mm. The study proves the efficacy of the GA approach in optimisation of machining parameters for improved surface roughness.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
V. Chowdary, Boppana
boppana.chowdary@sta.uwi.edu
Jahoor,, Riaz
UNSPECIFIED
Ali,, Fahraz
UNSPECIFIED
Trishel, Gokool
UNSPECIFIED
Subjects: T Technology > TJ Mechanical engineering and machinery
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Mechanical Engineering
Journal or Publication Title: Journal of Mechanical Engineering (JMechE)
UiTM Journal Collections: UiTM Journal > Journal of Mechanical Engineering (JMechE)
ISSN: 1823-5514 ; 2550-164X
Volume: 16
Number: 2
Page Range: pp. 77-91
Keywords: Algorithm, Optimisation, Surface Roughness, CNC Turning.
Date: 2019
URI: https://ir.uitm.edu.my/id/eprint/36424
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