Cutting tool remaining useful life during turning of metal matrix composites
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, the conditional reliability function and the Remaining Useful Life (RUL) of a cutting tool are estimated as a function of the current condition's states. RUL is estimated based on the available information obtained from condition monitoring. The cutting forces' measurements define the states, and are considered as the monitoring signals that offer diagnosis of the tool wear state. The cutting tool is used under constant machining parameters, namely the cutting speed, the feed rate, and the depth of cut. Experimental data is collected during turning titanium metal matrix composites (TiMMCs) which are a new generation of materials and have proven to be viable in aerospace application. Two modeling tools are used to model the tool's reliability and hazard functions; The Proportional Hazards Model (PHM), which is a statistical tool that uses EXAKT software, and the Logical Analysis of Data (LAD), which is a machine learning tool that uses cbmLAD software. A comparison between the two approaches is given. The results are presented, and the practical use of these results is discussed. The Remaining Useful Life (RUL) of a cutting tool during turning TiMMCs, and its conditional reliability function are estimated as functions of the current condition's states.
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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