Modeling Concurrent Product Design: A Multifunctional Team Approach
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
A satisfaction-driven, multifunctional team approach is presented with application to concurrent product design. This team ap proach is based on optimization formalism in which different teams are responsible to perform their specified functions by controlling the individual sets of design variables. The functions of each team should characterize different aspects of product design in the collabora tive product development. In particular, the preference of each team against a design alternative is formalized using fuzzy set theory to seek the most favorite design that best fulfills the team goal. Two fuzzy set operators—"min" and "geometric mean"—are extended to ag gregate team's satisfaction metrics to describe the non-compensative and compensative relationships between teams. Team aggrega tion is based on the strategic team paradigms derived from game theory and the concept of responsibility and controllability. As a result, five design models are explored to reveal typical team interactions in design computing and then illustrated through the study of a de sign example.
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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 | 0.000 | 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) | 0.001 | 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