An axiomatic design theory for design of apparel products
Bibliographic record
Abstract
An apparel product has a unique feature other than other products in that apparel product design must consider three categories of design requirements, namely function (governed by natural sciences), comfort (governed by ergonomics), and pleasure (governed by aesthetics and psychology). This paper proposes a general design theory for apparel products. The theory is based on Axiomatic Design Theory (ADT), which is for the functional aspect of products, particularly by adapting ADT to apparel product design, to which all the aspects (function, comfort, pleasure) need to be considered. The proposed theory is thus called the Axiomatic Design Theory For Apparel (ADT-FA). The ADT-FA has two axioms. Axiom 1 (apparel) concerns coupling in the design requirement, and Axiom 2 (apparel) concerns redundancy in the design parameter. The proposed theory is preliminarily validated with the Zoot suit, which is well known in the community of apparel design. The work opens an avenue for more validations in future.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".