Discrete-event simulation-based decision making of Just-In-Time strategies for precast concrete supply chain using batch delivery and offsite inventory level
Bibliographic record
Abstract
Precast concrete (PC) can potentially improve construction industry projects when used as a primary process in the precast concrete supply chain (PCSC). Successful inventory reduction and on-time delivery are essential in the PCSC because of critical scheduling and cost factors. To solve these challenges, this study applied Just-In-Time (JIT) strategies in the PCSC using the Discrete-Event Simulation (DES) model to help manufacturers identify the optimal decision. The factors considered were offsite inventory levels (based on days buffered) and batch delivery decisions that reduced supply penalties and improved construction performance. The model was validated based on a precast project experiment in Vietnam; the model provided a saving of 52% in manufacturer penalties and reduced construction idle work by 77%. An optimal combined decision was provided for the manufacturer, such as a 1day-4batch decision with maximum benefit and a 2day-2batch decision for safety using an uncertainty risk consideration in the PC wall panel study case. This research contributes a tool to help manufacturers in decision making and promotes the use of JIT applications/strategies in the PCSC process.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".