Research Article
A Machine Learning Approach to Optimize, Model, and Predict the Machining Factors in Dry Drilling of Nimonic C263
| Source | SOS | df | MS | F value | value |
| Model | 7.462E + 05 | 9 | 82907.42 | 113.34 | <0.0001 | N | 5.787E + 05 | 1 | 5.787E + 05 | 791.17 | <0.0001 | F | 20931.63 | 1 | 20931.63 | 28.62 | <0.0001 | 2ρ | 72323.10 | 1 | 72323.10 | 98.87 | <0.0001 | | 2087.67 | 1 | 2087.67 | 2.85 | 0.1094 | | 76.19 | 1 | 76.19 | 0.1042 | 0.7508 | | 3747.33 | 1 | 3747.33 | 5.12 | 0.0370 | N2 | 32511.57 | 1 | 32511.57 | 44.45 | <0.0001 | f2 | 16.81 | 1 | 16.81 | 0.0230 | 0.8813 | 2ρ2 | 3937.57 | 1 | 3937.57 | 5.38 | 0.0330 | Residual | 12435.11 | 17 | 731.48 | | | Cot. total | 7.586E + 05 | 26 | | | | R-square: 98% and adj. R-square: 97% |
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