ANALISIS FOTO MAKRO TERHADAP KEKASARAN BAJA ST 60 HASIL PEMBUBUTAN FACING DI MESIN CNC HARDINGE
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Technological advances have made the manufacturing sector an industry that needs to develop and compete globally, one of which is CNC machines which produce quality products for industrial needs. In producing a material at CNC machine, the latest design software is needed, namely Autodesk Fusion 360. Apart from lest, on then machine processing, it is desired to produce a material surface with a good roughness value. The desired result of this research is to analyze roughness value towards facing turning results on CNC machines for variations in spindle speed, namely 410 rpm, 450 rpm, 660 rpm, 900 rpm, 1100 rpm and 1200 rpm using carbide chisels and dromus coolant. The roughness of the facing surface can be assessed using a Surface Roughness Tester and analyzing the material structure using macro photos. The results of specimen testing showed that the smallest roughness value occurred of a spindle speed of 1200 rpm with a value of Ra = 0.810 µm and the output of observations make use macro photos represent that the roughness structure of the material was very smooth compared to the production process on CNC machines using other spindle speeds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.044 | 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