Investigating the impact of drill material on hole quality in jute/palm fiber reinforced hybrid composite drilling with uncertainty analysis
Bibliographic record
Abstract
This study presents a method for modelling, predicting, and evaluating the impact of drill materials on the drilling process of hybrid palm/jute polyester composites, with the aim of enhancing hole quality regarding delamination, circularity, and cylindricity. Three drill materials, including High-Speed Steel (HSS), 5 % Cobalt-coated High-Speed Steel (HSS-Co5), and Solid Carbide drills were tested, and their impacts on drilling performance were assessed. Through thorough experimentation and statistical analysis, significant differences in results were observed between HSS drills and both HSS-Co5 and Solid Carbide drills. However, the variation in results between HSS-Co5 and Solid Carbide drill results was minimal. Additionally, the findings highlight notable disparities among drill types concerning uncertainty. The results also indicate that feed rate, drill material, and their interaction play crucial roles in determining drilling efficiency. Specifically, HSS drills consistently outperformed HSS-Co5 and Solid carbide drills, demonstrating superior performance in minimizing delamination, improving circularity, and enhancing cylindricity along with lower uncertainty.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".