Generating labour cost budget for a construction-oriented fabrication facility: simulation-based resource scheduling approach
Bibliographic record
Abstract
A novel labour-hour budgeting method is proposed by integrating productivity concepts in project scheduling and budgeting to enhance the accuracy of labour cost budgeting for planning labour-intensive projects. The proposed method applies discrete event simulation approach to represent crew formation, labour resource utilization, and labour resource flowing between consecutive activities, which allows for quantitatively characterizing the impact of labour semi-productive time on labour cost budgeting as a time-dependent variable. Simulation-based assessment of variations in crew sizes and labour allocations is conducive to reducing semi-productive time and thus enhancing the cost performance of the whole project. The proposed method is then applied in a real-world case study for planning steel girder fabrication projects in construction of highway bridges. Not limited to budgeting for labour resources in construction-oriented fabrication facility, the research contributions are also significant to other construction planning settings where limited resources are shared and utilized among different activities.
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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 | 0.000 | 0.001 |
| 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".