Constructability Concepts, Significance, and Implementation
Bibliographic record
Abstract
Improving the productivity and quality of construction projects along with the minimization of cost and time are significant concerns in construction engineering and management. These concerns have stimulated specialists to gather the best practices and generate new techniques leading to more productive projects. Constructability review is one of the established methods for integrating design and construction phases, taking construction knowledge and experience into consideration in the early stages of a project. Performing an appropriate constructability review is one of the best practical solutions for projects that may potentially end up with high costs, schedules overruns, and complicated designs. In this process, by continuous involvement of experts in all phases of projects, their knowledge and experience will be reflected in the project considerations, leading to a feasible design and construction. This paper aims to provide a comprehensive list of constructability concepts and their significance by reviewing the literature and complement it with a survey from industrial experts. The list of compiled constructability concepts is divided into conceptual phase, design and procurement, and field operation phases. The significance of constructability concepts, regarding each stage of a project, was identified through a survey. Finally, constructability implementation in a steel fabrication company using defined constructability concepts was studied, and recommendations for improving their practice by applying this research’s output are provided.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".