Grouping operations in cellular manufacturing considering alternative routings and the impact of run length on product quality
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
When a production lot is split into alternative routes, the production run in each route will be shortened. Merging sub-lots from different alternative routes to one selected route will result in a longer production run in the selected route. Such variation in product run length could have impacts on product quality. The paper formulates a mathematical programming model for optimal lot splitting into alternative routes to account for the impact of production run length on product quality in a cellular manufacturing environment. A genetic algorithm is developed to solve the proposed model efficiently. Numerical examples are presented to demonstrate the features of the proposed model and computational efficiency of the solution method. It further proposes extensions of the developed model and solution procedure to consider cell formation decisions when the impact of splitting production lots into alternative routes on product quality is considered.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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