Supply chain network design with considerations for modular assembly
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
We present a supply chain optimisation model that simultaneously considers sourcing decisions for each part in a complex multi-level bill of materials (BOM) but decides on which should be assembled into subassemblies or modules. Indeed, some parts in the BOM are flexible in the sense that they can be grouped with other parts or subassemblies to form modules. The problem is to find the composition of the modules and the assignment of modules and parts to subcontractors while minimising the overall supply chain cost. The problem considered is one faced by a jet engine manufacturer when designing its multi-echelon, multi-period, multi-product supply chain network with deterministic demand. The mixed integer programming model considers multiple sourcing where the number of parts sourced from a business partner must exceed a lower bound as dictated by purchasing contracts. Computational results are presented for different scenarios allowing the combined analysis of supply chain design and supplier relationships.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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