Optimisation of surface roughness when CNC Turning of Al-6061: Application of Taguchi Design of experiments and genetic algorithm / Boppana V. Chowdary...[et al.]
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 f...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM)
2019
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/36424/ |
| _version_ | 1848809048492736512 |
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| author | V. Chowdary, Boppana Jahoor,, Riaz Ali,, Fahraz Trishel, Gokool |
| author_facet | V. Chowdary, Boppana Jahoor,, Riaz Ali,, Fahraz Trishel, Gokool |
| author_sort | V. Chowdary, Boppana |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T23:08:25Z |
| format | Article |
| id | uitm-36424 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T23:08:25Z |
| publishDate | 2019 |
| publisher | Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-364242020-11-09T07:49:47Z https://ir.uitm.edu.my/id/eprint/36424/ Optimisation of surface roughness when CNC Turning of Al-6061: Application of Taguchi Design of experiments and genetic algorithm / Boppana V. Chowdary...[et al.] jmeche V. Chowdary, Boppana Jahoor,, Riaz Ali,, Fahraz Trishel, Gokool TJ Mechanical engineering and machinery 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. Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM) 2019 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/36424/1/36424.pdf 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.]. (2019) Journal of Mechanical Engineering (JMechE) <https://ir.uitm.edu.my/view/publication/Journal_of_Mechanical_Engineering_=28JMechE=29.html>, 16 (2). pp. 77-91. ISSN 1823-5514 ; 2550-164X https://jmeche.uitm.edu.my/ |
| spellingShingle | TJ Mechanical engineering and machinery V. Chowdary, Boppana Jahoor,, Riaz Ali,, Fahraz Trishel, Gokool Optimisation of surface roughness when CNC Turning of Al-6061: Application of Taguchi Design of experiments and genetic algorithm / Boppana V. Chowdary...[et al.] |
| title | Optimisation of surface roughness when CNC Turning of Al-6061: Application of Taguchi Design of experiments and genetic algorithm / Boppana V. Chowdary...[et al.] |
| title_full | Optimisation of surface roughness when CNC Turning of Al-6061: Application of Taguchi Design of experiments and genetic algorithm / Boppana V. Chowdary...[et al.] |
| title_fullStr | Optimisation of surface roughness when CNC Turning of Al-6061: Application of Taguchi Design of experiments and genetic algorithm / Boppana V. Chowdary...[et al.] |
| title_full_unstemmed | Optimisation of surface roughness when CNC Turning of Al-6061: Application of Taguchi Design of experiments and genetic algorithm / Boppana V. Chowdary...[et al.] |
| title_short | Optimisation of surface roughness when CNC Turning of Al-6061: Application of Taguchi Design of experiments and genetic algorithm / Boppana V. Chowdary...[et al.] |
| title_sort | optimisation of surface roughness when cnc turning of al-6061: application of taguchi design of experiments and genetic algorithm / boppana v. chowdary...[et al.] |
| topic | TJ Mechanical engineering and machinery |
| url | https://ir.uitm.edu.my/id/eprint/36424/ https://ir.uitm.edu.my/id/eprint/36424/ |