ENVIRONMENT-BASED DESIGN (EBD) APPROACH TO DEVELOPING QUALITY MANAGEMENT SYSTEMS: A CASE STUDY
Bibliographic record
Abstract
This paper shows how to develop a manual for Quality Management System (QMS) by using a design methodology - Environment Based Design (EBD). The EBD includes three interdependent design activities: environment analysis, conflict identification and solution generation. The EBD is particularly effective when customers' wants are not clearly understood where designers can be given the right direction through the analysis of the product's working environment. In the case study presented in this paper, the customer wanted to develop a quality manual for a flow monitoring service. The challenge was that the content and structure of the final manual were not clear to the designers. By taking this task as a design problem, the EBD was applied to analyse the current service including the organization structure, the business processes, and the existing documents. After critical conflicts were identified, the quality manual and a data processing software system were produced for the client. This application of the EBD shows its effectiveness as a generic design methodology.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".