Usability of the design structure matrix for automotive design engineering
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
In this thesis the author discusses the Design Structure Matrix (DSM) as a best practice. The DSM provides project management structure, develop and modularises the systems level design of products, performs project scheduling, tasks interdependency, resource allocation, dependent tasks planning, and provides proper communication and coordination structure. The DSM tool is applied to two case studies of the design of a gasoline/electric hybrid vehicle power train and one case study of assembly design, with concentrated emphasis on the recommendations on how the specific cases in this thesis can benefit. A novel analytic feature Relative Significance Summation Clustering (RSSC) of the DSM is also identified, which appears to be otherwise unreported in the literature. The case studies analysis demonstrates that the DSM tool can be used to develop a deeper understanding of the system level design, project management, and assembly design. The DSM tool was successful at providing a representation of many of the issues and insights identified in the case study analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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