Simulation-Based Study of the Resilience of Flexible Manufacturing Layouts Subject to Uncertain Demands of Product Variants
Why this work is in the frame
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Bibliographic record
Abstract
Due to market competition, manufacturers typically produce their products with different customized features, leading to the production of product variants (or a product family). Since the market trend can change swiftly, the demands of individual product variants can be difficult to predict. Two flexible manufacturing layouts are commonly considered: functional and cellular layouts. While the functional layout is more resilient to demand changes due to better resource pooling, the cellular layout can be more productive on some occasions due to better routing efficiency. In this context, the purpose of this paper is to quantify and study the criticality of product variants. The criticality score of a product variant can estimate and rank which product variants can sensitively cause bottlenecks in the functional and cellular layouts. The proposed criticality analysis starts with the estimation of bottleneck machines. Through the dependency information of machines and parts, we can estimate the criticality of product variants. The criticality analysis is demonstrated and examined through a simulation study with a study case involving the production of five furniture products with 16 unique parts using 11 machines. The simulation results show that the productions with more critical product variants tend to deteriorate the completion time of the cellular layout more severely. In practice, manufacturers can use the proposed criticality analysis to evaluate the criticality of product variants and support their facility layout decision. For example, if more demand for critical products is expected, the layout should support more resource pooling (e.g., functional layouts).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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