Multiobjective Optimization of Surface Roughness and Tool Wear in High-Speed Milling of AA6061 by Machine Learning and NSGA-II
This work addresses the prediction and optimization of average surface roughness (Ra) and maximum flank wear (Vbmax) of 6061 aluminum alloy during high-speed milling. The investigation was done using a DMU 50 CNC 5-axis machine with Ultracut FX 6090 fluid. Four factors were examined: the table feed...
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| Tác giả chính: | , , |
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| Định dạng: | Bài trích |
| Ngôn ngữ: | English |
| Nhà xuất bản: |
Hindawi
2022
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| Chủ đề: | |
| Truy cập trực tuyến: | https://www.hindawi.com/journals/amse/2022/5406570/ https://dlib.phenikaa-uni.edu.vn/handle/PNK/5977 https://doi.org/10.1155/2022/5406570 |
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| Tóm tắt: | This work addresses the prediction and optimization of average surface roughness (Ra) and maximum flank wear (Vbmax) of 6061 aluminum alloy during high-speed milling. The investigation was done using a DMU 50 CNC 5-axis machine with Ultracut FX 6090 fluid. Four factors were examined: the table feed rate, cutting speed, depth of cut, and cutting length. Three levels of each factor were examined to conduct 81 experiment runs. The response parameters in these experiments were measurements of Ra and Vbmax. |
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