Bibliographic record
Abstract
Modules for the Underground Mine O. Lundhede, O. Pettersson Pages 168-178 (2013 Proceedings of the 30th ISARC, Montréal, Canada, ISBN 978-1-62993-294-1, ISSN 2413-5844) Abstract: Today, systems and machinery usually are designed to meet only one specific customers requirements. One reason for this is that underground automation and smart functions are often developed tightly together with a customer. This is natural, since risk and cost can be shared between the customer and the supplier. Nevertheless, when the automation product develops and the market increase this will cause problems: The highly specialized products will not fulfill the next customers demands. In order to cope with this problem, Atlas Copco works towards a common platform. Instead of designing solutions for specific customers, we will lift the abstraction and focus on standardized modules. These modules, or function blocks, can then be combined in a large variety of configurations. The benefits of combining modules into products are, for example: increased flexibility when options are available for many machines; easier commissioning and maintenance since less different spare parts and tools are needed; and easier operation since the user interfaces have a similar look and feel. This paper will present the ongoing work towards standardized modules. We will discuss how our Rig Control System (RCS) allows for modular design at Atlas Copco. RCS has number of standardized modules that are used in different surface and underground mining and tunneling equipment. These modules are also used for optional products such as, drilling, radio-remote control, and telematics systems. Keywords: Automation in mining, Robotics DOI: https://doi.org/10.22260/ISARC2013/0018 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.152 | 0.058 |
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".