Multi-Response Optimization of Milling Process of Hardened S50C Steel Using SVM-GA Based Method
This study aims to find the optimized parameters for surveying the milling process of S50C steel in a minimum quantity lubrication (MQL) environment using a support vector machine-genetic algorithm (SVM-GA). Based on the experimental matrix designed by the Taguchi method, surface roughness and cutti...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Metals |
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| Online Access: | https://www.mdpi.com/2075-4701/13/5/925 |
| _version_ | 1797599050081501184 |
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| author | Thanh-Cong Nguyen Dung Hoang Tien Ba-Nghien Nguyen Quang-Cherng Hsu |
| author_facet | Thanh-Cong Nguyen Dung Hoang Tien Ba-Nghien Nguyen Quang-Cherng Hsu |
| author_sort | Thanh-Cong Nguyen |
| collection | DOAJ |
| description | This study aims to find the optimized parameters for surveying the milling process of S50C steel in a minimum quantity lubrication (MQL) environment using a support vector machine-genetic algorithm (SVM-GA). Based on the experimental matrix designed by the Taguchi method, surface roughness and cutting force data were collected corresponding to each experiment with changes in input parameters such as cutting speed, tooth feed rate, and axial depth of cut, along with changes in two parameters of the minimum lubrication system: flow rates and injection pressure. Through analysis by the SVR-NSGAII method, the study obtained the optimal parameters of cutting and lubricating conditions when prioritizing either surface roughness or focusing on the cutting force; however, the most comprehensive result is believed to be achieved by balancing these two factors. So, when striving for the neutral value of both output parameters, which are surface roughness (µm) and cutting force (N), the optimum parameters including injection pressure (MPa), flow rates (mL/h), cutting speed (m/min), feed rate (mm/tooth), and axial depth of cut (mm) are proposed. |
| first_indexed | 2024-03-11T03:29:41Z |
| format | Article |
| id | doaj.art-4d5f194717f743be8d6172826b8f6fd6 |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-03-11T03:29:41Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-4d5f194717f743be8d6172826b8f6fd62023-11-18T02:27:47ZengMDPI AGMetals2075-47012023-05-0113592510.3390/met13050925Multi-Response Optimization of Milling Process of Hardened S50C Steel Using SVM-GA Based MethodThanh-Cong Nguyen0Dung Hoang Tien1Ba-Nghien Nguyen2Quang-Cherng Hsu3Department of Mechanical Engineering, National Kaohsiung University of Science and Technology, 415 Chien-Kung Road, Kaohsiung City 80778, TaiwanFaculty of Mechanical Engineering, Hanoi University of Industry, No. 298, Cau Dien Street, Bac Tu Liem District, Hanoi 11950, VietnamFaculty of Information Technology, Hanoi University of Industry, No. 298, Cau Dien Street, Bac Tu Liem District, Hanoi 11950, VietnamDepartment of Mechanical Engineering, National Kaohsiung University of Science and Technology, 415 Chien-Kung Road, Kaohsiung City 80778, TaiwanThis study aims to find the optimized parameters for surveying the milling process of S50C steel in a minimum quantity lubrication (MQL) environment using a support vector machine-genetic algorithm (SVM-GA). Based on the experimental matrix designed by the Taguchi method, surface roughness and cutting force data were collected corresponding to each experiment with changes in input parameters such as cutting speed, tooth feed rate, and axial depth of cut, along with changes in two parameters of the minimum lubrication system: flow rates and injection pressure. Through analysis by the SVR-NSGAII method, the study obtained the optimal parameters of cutting and lubricating conditions when prioritizing either surface roughness or focusing on the cutting force; however, the most comprehensive result is believed to be achieved by balancing these two factors. So, when striving for the neutral value of both output parameters, which are surface roughness (µm) and cutting force (N), the optimum parameters including injection pressure (MPa), flow rates (mL/h), cutting speed (m/min), feed rate (mm/tooth), and axial depth of cut (mm) are proposed.https://www.mdpi.com/2075-4701/13/5/925milling processmulti-response optimizationsupport vector machinegeneric algorithmminimum quantity lubrication (MQL) |
| spellingShingle | Thanh-Cong Nguyen Dung Hoang Tien Ba-Nghien Nguyen Quang-Cherng Hsu Multi-Response Optimization of Milling Process of Hardened S50C Steel Using SVM-GA Based Method Metals milling process multi-response optimization support vector machine generic algorithm minimum quantity lubrication (MQL) |
| title | Multi-Response Optimization of Milling Process of Hardened S50C Steel Using SVM-GA Based Method |
| title_full | Multi-Response Optimization of Milling Process of Hardened S50C Steel Using SVM-GA Based Method |
| title_fullStr | Multi-Response Optimization of Milling Process of Hardened S50C Steel Using SVM-GA Based Method |
| title_full_unstemmed | Multi-Response Optimization of Milling Process of Hardened S50C Steel Using SVM-GA Based Method |
| title_short | Multi-Response Optimization of Milling Process of Hardened S50C Steel Using SVM-GA Based Method |
| title_sort | multi response optimization of milling process of hardened s50c steel using svm ga based method |
| topic | milling process multi-response optimization support vector machine generic algorithm minimum quantity lubrication (MQL) |
| url | https://www.mdpi.com/2075-4701/13/5/925 |
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