Impact of Building Information Modeling on Just-in-Time Material Delivery
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
The purpose of this research is to evaluate the impact of Building Information Modeling (BIM) on Just-In-Time (JIT) material delivery, with a focus on how the use of BIM can help improve efficient implementation of JIT and reduce the cost of material management. Previous research and a number of case studies have addressed the positive impact of BIM on construction at large but none focused on JIT in construction. This paper presents a methodology for selecting reliable material vendors. It also utilises the integration of BIM and scheduling software to generate quantities of material and its required delivery time to improve the flow process and improve its reliability to minimise related delays and productivity losses arising from idle and non-productive time of equipment and labour on jobsites. 4D visualization is utilized to support coordination and timing of JIT material deliveries in an effort to minimize congestion on job sites. Case studies on JIT material deliveries are presented and the impact of BIM implementation on reducing the cost of material management is evaluated. The joint effect of BIM and JIT on quality control, elimination of waste, reduction of inventory buffers, and on relationships with material vendors are evaluated by analysing and comparing data from case studies. The paper also presents a methodology based on multi-attribute decision criteria for modelling the selection criteria for material vendors. The model can assist in ranking vendors not only based on cost and quality but also on their reliability in delivering material on time.
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.
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 | 0.001 |
| 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 it