Scheduling a hybrid flowshop with parallel machines for aircraft assembly production
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
The new P2/HFS|Prec|Cmaxscheduling problem is found within an aerospace fuselage manufacturing environment and is a combinatorial problem addressed using dispatching rules. A newly proposed dispatching rule, named ‘batch and match’, was created by exploiting the combined elements of a) product assembly characteristics and b) processing time on a shared resource, is used to find solutions for minimizing makespan and waiting time for ten fuselage sets. A new manufacturing tool incorporates models for calculation of makespan and waiting time in the system. The best schedule, found using the new dispatching rule and a weighting system for ranking makespan and waiting time, was DCAB (LI), this schedule gives a reduced makespan of 2.61% against the benchmark longest imminent operation rule. The DCAB (LI) schedule also shows a reduction in waiting time of 53.5% per fuselage set created. This ‘batch and match’ dispatching method performs better than other rules and offers a solution to shared resources that limit processing in hybrid flowshops with precedence constraints.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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