CNC Turning Parameter Optimization for Surface Roughness of Aluminium-2014 Alloy Using Taguchi Methodology
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Bibliographic record
Abstract
The optimization of machining parameters is critical to the quality of machined products and the production rate. This paper aims to optimize the surface roughness of aluminium-2014 alloy by adjusting the machining parameters of computer numerical control (CNC) turning, including, cutting speed, depth of cut and feed rate. According to L9 orthogonal array, a total of nine experiments were conducted according to Taguchi method with different parameter settings. The surface roughness of the machined products was measured by a roughness tester, and evaluated by signal-to-noise ratio (SNR). The analysis of variance (ANOVA) was conducted to find the optimal parameter settings for surface roughness. The results show that the cutting speed is the most influential parameter (67.28 %) on surface roughness, followed by feed rate (32.28 %) and depth of cut (0.33 %) for surface roughness. Hence, the surface roughness can be optimized by minimizing the feed rate and depth of cut.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it