A Special Purpose Simulation Template for Modeling Tire Usage of Mining Truck Fleet
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
The logistics for the supply of tires for trucks utilized in mining operations are generally affected by their demand and supply on the market. In times of high demand and tire scarcity, operations of most companies with large truck fleets are affected due to inadequate analysis and tire usage planning. The lack of a proper tool for practitioners to use for this purpose has contributed to the problem. This study proposes a special purpose simulation template that can be used to solve the problem. The template was developed for analyzing a six tire truck because it is the most common truck type used in mining operations. It utilizes statistical distributions fitted to historic field data of tire usage, and outputs the most likely number of used, early failed and worn out tires for the analyzed period. A simulation based approach was adapted because of the dynamic and random nature of the tire usage problem which does not lend itself to analytical solutions.
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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 | 0.001 | 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 | 0.001 |
| 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