Function Module Partition for Complex Products and Systems Based on Weighted and Directed Complex Networks
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
Modular design is an effective approach to shorten lead-time and reduce cost for development of complex products and systems (CoPS). Because the physical details of the product are not available at the conceptual design stage, considerations in the downstream product development phases such as manufacturing and assembly cannot be used for partition of modules at the conceptual design stage. Since design solution at the conceptual design stage can be modeled by functions and relationships among these functions such as function flows including information flows, material flows, and energy flows, a novel approach is introduced in this research for function module partition of CoPS through community detection using weighted and directed complex networks (WDCN). First, the function structure is obtained and mapped into a weighted and directed complex network. Based on the similarity between behaviors of communities in WDCN and behaviors of modules in CoPS, a LinkRank-based community detection approach is employed for function module partition through optimization with simulated annealing. The function module partition for the power mechanism in a large tonnage crawler crane is conducted as a case study to demonstrate the effectiveness of the developed approach.
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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 | 0.000 |
| 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