Benchmarking and Improving Dimensional Quality on Modular Construction Projects – A Case Study
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
Dimensional quality plays a key role in project success for modular construction. While approaches exist for reducing rework associated with dimensional variability in traditional construction (i.e., onsite resolution), more proactive approaches must be employed during offsite production of modules. Unfortunately, the stricter dimensional quality demands in modular construction are not yet completely addressed in existing guidelines or studies. As such, contractors often must resort to use of reactive measures to reduce rework. This paper bridges this gap by demonstrating how to implement continuous benchmarking and improvement of dimensional quality by comparing as-built and nominal 3D geometric data across modular construction projects. A case study is presented for two nearly identical modular construction projects, which are carried out in succession. The first project is used to quantify and benchmark key impacts on overall dimensional quality, while strategic improvements are introduced in the second project to improve quality and reduce rework. The results of this study demonstrate how contractors can achieve adequate dimensional quality and reduce rework on successive modular construction projects.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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