Linkage of Truck-and-shovel Operations to Short-term Mine Plans Using Discrete Event Simulation
Bibliographic record
Abstract
The scope of this research is concerned with improving truck-and-shovel systems’ efficiency using simulation. The major shortcomings of the current simulation models reviewed in literature are: a) considering shovels as continuously working equipment, b) modeling the system based on a shovel’s production requirements, and c) considering only the total tonnage of material hauled with neither any measure of material quality nor a link to the mine production schedule. The objective of this study is to develop, implement, and verify a simulation model to analyze the behavior of a truck-and-shovel haulage system in open-pit mining in conjunction with short-term plans. The simulation model imitates the complex truck-and-shovel system, and considers the uncertainties associated with the operations of trucks and shovels. It guarantees that the operational plans will honor the optimum net present value obtained in the scheduling phase. The simulation model is verified by a case-study measuring key performance indicators of the truck-and-shovel haulage system.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".