Optimization of Carbonitrided AISI 1022 Self-drilling Tapping Screw Process Parameters Using Taguchi Approach
Bibliographic record
Abstract
The manufacturing processes of self-drilling tapping screws, which are widely used for construction works, include wiremanufacturing, forming, heat treating, and coating. A low-carbon steel wire of AISI 1022 is used to easily fabricate into self-drilling tapping screws. The majority of carbonitriding activity is performed to improve the wear resistance without affecting the soft, tough interior of the screws in self-drilling operation. In this study, Taguchi method is used to obtain optimum carbonitriding conditions to improve the mechanical properties of AISI 1022 self-drilling tapping screws. The carbonitriding qualities of self-drilling tapping screws are affected by various factors, such as quenching temperature, carbonitriding time, atmosphere composition (carbon potential and ammonia level), tempering temperature and tempering time. The effects of carbonitriding parameters affect the quality characteristics, such as case hardness and core hardness. It is experimentally revealed that the factors of carbonitriding time and tempering temperature are significant for case hardness, while only tempering temperature is significant for core hardness. The optimum mean case hardness is 649.2HV, and the optimum mean core hardness is 439.7HV. The new carbonitriding parameter settings evidently improve the performance measures over their values at the original settings. The strength of the carbonitrided AISI 1022 selfdrilling tapping screws is effectively improved. The results may be used as a reference for fastener manufacturers.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".