Estimating Potential Cost Savings from Implementing an Innovative TBM Guidance Automation System
Bibliographic record
Abstract
It is vitally important to evaluate costs, benefits and risks associated with adopting a new method or technology prior to field implementation. The present research proposes a framework for estimating potential cost savings by implementing new method or technology in the field in terms of: (1) productivity-dependent crew cost; (2) time-dependent indirect cost; and (3) time-independent indirect cost in the current practice that can be removed. In regards to system reliability, the proposed framework guides the identification of possible breakdown event categories and the evaluation of probabilities and consequences for each category of event. A case study is presented in the context of developing an innovative TBM guidance automation system in tunnel construction. Potential cost saving resulting from implementing the new automation system for a 1,000-meter-long drainage tunnel project in Edmonton, Alberta is estimated to be $346k, which far outweighs the additional cost associated with system reliability (about $ 34k) by about ten-fold.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".