Procedure to Ensure On-Time Delivery of Materials in Multifamily Housing Construction Projects Using Just-In-Time and Kitting In Small Construction
Bibliographic record
Abstract
Construction companies are responsible for purchasing materials for the execution of construction projects, which consist of different stages; however, many times the materials do not arrive on time at the construction site.The material supply process is important within construction projects as it directly impacts the budget and schedule of the work.However, one of the most influential factors causing the delay in the delivery of material is the lack of a logistics plan for the supply of material in small companies.However, this leads to delays in the progress and delivery of the work.For this reason, this research focuses on ensuring the delivery time of construction materials in small construction companies for multi-family housing construction projects, specifically in the supply of materials through the use of the Just in Time and Kitting methodology, applying the use of an ERP.In this research, the following methodology is followed: (A) registration and analysis of information through expert judgment, (B) determination of the conventional material supply process in small construction companies, (C) development of the new supply process and (D) implementation of the new material supply process using the JIT and Kitting methodology.Finally, the result is a reduction in the delivery time of materials in the supply process, the metric being the average delivery time.In addition, a better management of the material supply process is obtained, in the logistics part.And the perception of the participants improved with the implementation of the new process.It is mainly concluded that the methodology used allows to ensure the delivery time of material, thus reducing the time in said process.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".