New dependency model and biological analogy for integrating product design for variety with market requirements
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
Variety in product design is a result of diversity of needs in different domains and market segments. The two-way interaction and dependency between product design features and customer requirements is analogous to co-evolution in nature, where two groups of different species evolve to co-exist. A new method for designing products, families and platforms by recognising commonalities and core features, using the concept of co-evolution, is introduced in this paper. Cladistics is used to identify product component modules which correspond to common regional market requirements. Algorithms for functional and structural analysis as well as product variants generation have been developed. Complex dependency interactions and modularity relationships are modelled using liaison graphs and cladograms. A case study of washing machines is detailed and used to validate this novel application of the co-evolution dependency model in product families and platform design, demonstrating its use in the world of artefacts co-development. The proposed model is capable of satisfying different market segments’ requirements, while minimising the cost associated with product variety, by promoting modular product family design. It selects the best product variant(s) for each market segment and minimises component redundancy.
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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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