A Machine Learning Approach to Optimize, Model, and Predict the Machining Factors in Dry Drilling of Nimonic C263
In this present paper, the machine learning approach is used to optimize, model, and predict the factors during drilling Nimonic C263 under dry mode. Nimonic C263 is tough to machine aero alloys, and it is required to find a predictive model and to optimize the factors in drilling this alloy before...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/4856089 |
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