Evaluation of the Variable Component of Truck Travel Time Based on the Maximum Speed for an Optimal Management of the Fleet, Case of Boukhadra Iron Ore Mine, NE Algeria
Bibliographic record
Abstract
This work focuses on the loading and haulage works which are crucial operations and of major importance for the mining exploitation and whose costs are very high and represent up to 70% of the total price of the entire supply chain production.It is advisable to make a judicious choice of loading and transport machines and to assign them well to limit waiting times and increase yields, which will of course lead to the realization of the planned production.The allocation of trucks and the number assigned to the shovels is an important work for the operator, in this context the present work concerns the open pit mine of Boukhadra (Tebessa), one of the largest iron deposits in Algeria.Based on truck timing data and the characteristics of excavators, trucks, and roads, an analysis of the current status of loading and transport work was made, which showed high waiting times of the shovel.Based on the performance curves of the CATERPILLAR trucks, we determined the appropriate speeds and therefore the determination of the number of trucks necessary to reduce the waiting times of the excavator.
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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 | 0.002 | 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 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".