An Integrated BIM System to Track the Time and Cost of Construction Projects: A Case Study
Bibliographic record
Abstract
Many construction projects suffer from poor design and from inconsistent time and cost management. This situation has led to rethinking of the industry’s performance and how it could be improved. Technology is breaking through design and management practices. Earned value management (EVM) enables better management of time and cost constraints. Building Information Modeling (BIM) is recognized to improve the planning and realization of a construction project. The present paper proposes an integrated time and cost management system (ITCMS), where an EVM platform is used in a virtual environment during the planning and construction phases of a project. The ITCMS enables early involvement and project integration plus thorough time and cost management. The system consists of four modules and 13 different processes. The ITCMS is beneficial at the design stage; construction professionals are able to synchronize the building model with time and cost parameters as well as optimize it through a clash detection process that results in budget and schedule compressions early on. The ITCMS is a useful tool for construction and engineering managers that strive to increase projects’ performance. The authors demonstrate in this paper the validity of using the ITCMS through an actual project.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".