The Impact of Machining Parameters on Peak Power and Energy Consumption in CNC Endmilling
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Bibliographic record
Abstract
Machining in a production environment commonly relies on trying maximizing material removal rates (MRR). This is done at the expense of increased peak power loads on the machine tool and machine spindle, and at the expense of potentially increasing energy consumption. To begin to develop an understanding of the relationship between peak power and energy consumption with machining parameters, spindle and total machine tool power are measured directly during a series of dry and wet endmilling tests on a 3-acis CNC milling machine. Cutting speeds, feedrates, and endmill immersions are varied and the resulting peak power measurements analyzed. Increasing any one of these parameters increases MRR and the peak power loads of the spindle and machine tool. However, the actual energy consumption varies widely for each parameter and in some cases such as when we increase feedrates, can actually decrease dramatically. The results of the direct measurements are presented and discussed as they relate to metal cutting.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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