Formulation of a pull production system for optimal inventory control of temporary rebar assembly plants
Why this work is in the frame
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Bibliographic record
Abstract
Temporary fabrication plants such as rebar assembly and precast segment shops are increasingly used in large scale construction projects to provide a construction site of its material needs. A plant needs to be operated in such a way that it is flexible enough to adapt to changing project demands while minimizing inventories. Meeting such needs requires careful control of the level of raw materials and assembly products fabricated in the plant, the two main types of inventories. However, in practice the ordering of raw materials and assembly times are ad hoc, leading to excess inventories and added costs to the project. This paper presents a methodology for effective, efficient, and economic control of inventory levels in temporary rebar assembly plants. Ordering processes are formalized to convert existing approaches into a pull production system. Given this transformation, a methodology is presented that employs Monte Carlo simulation and optimization techniques to identify inventory levels that minimize inventory costs while simulating variability in demand, procurement lead times, and production capacity. A retrospective case on a rebar assembly plant shows that the same amount of work can be performed with significantly less inventory levels when applying the proposed production methodology. It also provides evidence that the cost savings from inventory costs outweigh any additional holding or delivery costs associated with a pull production system.
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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 | 0.000 | 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 | 0.000 |
| 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 it