Lane Selection in an AGV-Based Asynchronous Parallel Assembly Line
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
Automated Guided Vehicles (AGVs) have the flexibility to meet the material handling requirements of asynchronous assembly lines. Furthermore, AGVs can select from among alternative paths in accordance with a prescribed lane selection rule, thereby facilitating the use of parallel server workstations. In this paper, motivated by our work in the automotive industry, several new lane selection rules are proposed. One of these, First Available Server/First Available Buffer/Balanced Work Content (FAS/FAB/BWC), is compared to two existing rules: Alternating Server, and First Available Server/First Available Buffer/Expected Completion Time (FAS/FAB/EC). Three performance measures - job throughput, workload balance among servers, and alteration of input job sequence - are employed, A SIMAN simulation model of a small, asynchronous parallel assembly line is used to study the impact on system performance of both the lane section rule and the number of parallel servers. Interaction between these two factors is studied though ANOVA. A number of interesting findings are reported for results of the lane selection rules with respect to the three performance measures. Their interpretation is used to motivate further research.
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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 | 0.001 | 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 | 0.001 |
| 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