EXTENDED TARGET WEIGHING APPROACH (ETWA): IMPACT AND RISK ANALYSIS OF LIGHTWEIGHT CONCEPTS IN THE PRODUCT-PRODUCTION SYSTEM-CO-DESIGN
Bibliographic record
Abstract
Abstract Lightweight design in interconnected systems becomes more and more complex as the interdependencies cannot be overseen by the product developer. Varying one component might not only influence the interfaces to other components but also the underlying production systems. Therefore, this contribution focuses on the product/production interdependencies and how they can be supported within lightweight design. Based on a functional description of the product it is possible to derive new lightweight design solutions and also to evaluate the change propagation in the production system. For this, a method for the impact and risk analysis is integrated in the lightweight design method Extended Target Weighing Approach (ETWA). By doing so, a risk value for the adapted production system can be calculated and different design concepts can be compared. The application of the developed method on a simplified use-case shows great potentials when evaluating the impact of a newly developed lightweight design solution on an already existing production system supporting the product development in decision making.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".