A FRAMEWORK FOR COMBINING SUSTAINABILITY CRITERIA WITH STAKEHOLDER REQUIREMENTS AT THE EARLY STAGE OF PRODUCT IDEA GENERATION PROCESS
Bibliographic record
Abstract
This paper combines sustainable development (SD) criteria with a list of conventional customer requirements to develop a basic functional design that minimizes negative environmental and societal impacts throughout product’s life cycle. The methodology used in this article is rooted in Quality Function Deployment (QFD). QFD is related to systems engineering as a method of translating stakeholders needs into detailed system requirements. Proposed framework can effectively increase consumer’s recognition for sustainable product. This article demonstrates the usefulness of the proposed framework in developing an Energy-using Product (EuP) (a hair dryer). This paper is the first step in laying the framework for an analytical tool in the management of sustainability in product design and development. In future, authors would like to implement this framework in real life product design and development process to find out opportunities for improvement.
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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 | 0.027 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".