Research Article
A Machine Learning Approach to Optimize, Model, and Predict the Machining Factors in Dry Drilling of Nimonic C263
Table 6
ANOVA for surface roughness.
| Source | SOS | df | MS | F value | value |
| Model | 0.0333 | 9 | 0.0037 | 5.00 | 0.0022 | N | 0.0008 | 1 | 0.0008 | 1.04 | 0.3215 | F | 0.0000 | 1 | 0.0000 | 0.0312 | 0.8619 | 2ρ | 0.0122 | 1 | 0.0122 | 16.46 | 0.0008 | | 0.0024 | 1 | 0.0024 | 3.30 | 0.0869 | | 0.0002 | 1 | 0.0002 | 0.2556 | 0.6196 | | 0.0039 | 1 | 0.0039 | 5.26 | 0.0348 | N2 | 0.0104 | 1 | 0.0104 | 14.01 | 0.0016 | f2 | 0.0025 | 1 | 0.0025 | 3.34 | 0.0853 | 2ρ2 | 0.0018 | 1 | 0.0018 | 2.43 | 0.1375 | Residual | 0.0126 | 17 | 0.0007 | | | Cot. total | 0.0458 | 26 | | | | R-square: 75% and adj. R-square: 60% |
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