1050 Flexible Automation and Intelligent Manufacturing, FAIM2004, Toronto, Canada Assignment Flexibility in a Cellular Manufacturing System- Machine Pooling versus Labor Chaining-
Bibliographic record
Abstract
In this paper, we compare the effects of machine pooling and labor chaining by means of a simulation study. In this study, the independent variables are: (1) the level of machine pooling (no. of jobs that can be produced in more than one cell), (2) the level of labor chaining (no. of workers able to work in more than one cell), and (3) labor utilization/machine utilization. The dependent variable is the mean flow time of jobs. Major outcome of our study is that, within our simulation setting, machine pooling is more important than labor chaining. All interaction effects, however, appear to be significant. As a consequence of our study, we suggest that managers should support the development of procedures for inter-cell movements of jobs. If there is a certain level of routing flexibility over cells, it is in most CM environments not needed to support the possibility of moving workers from one cell to another cell. 1.
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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 | 0.000 | 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 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".