The Performance Evaluation of Different Modular Construction Supply Chain Configurations Using Discrete Event Simulation
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
Modular construction and off-site prefabrication methods are gradually replacing traditional on-site construction due to their many advantages, but a key problem remains how to derive the maximum amount of the benefit. Construction supply chain (CSC) management, which is able to create an intensive interflow and quality alignment among different sectors involved in the whole construction lifecycle, could potentially accelerate the development of modular construction. Nevertheless, the benefits of CSC management in terms of sustainability and economics may vary due to the various configurations of the supply chain to which CSC management is applied. Previous research focused mainly on the factors related to CSC management strategy and purchase decisions. Different modular construction supply chain configurations are rarely compared and have yet to be taken into consideration for impact analyzation. This paper aims to investigate the relationship between supply chain configuration and supply chain performance in the context of modular construction. Several supply chain configuration models based on a real modular construction project are proposed in this study. Discrete event simulation (DES) is used to test the impact of these supply chain configuration models on the overall supply chain performance. Evaluation criteria were developed for scenario comparison.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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