The Evolution of Rapid Production: How to Adopt Novel Manufacturing Technology
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
This research focuses on the evolution and adoption of rapid production. We investigate the ways novel rapid production technology offers competitive advantage to companies, and argue that benefiting from this technology requires significant changes in business beyond manufacturing. The study is centered on core areas that need to be addressed when adopting such rapid production technology: business models, processes, IPR, industry characteristics, product/service transition, logistics and materials. Of note, whereas 3D printing has been praised as the “next big thing” in personal fabrication, it is just a stage in an ongoing transition from rapid prototyping toward rapid manufacturing. In the study, we establish and discuss two frameworks: 1) evolutionary steps in rapid production, and 2) key business imperatives to be addressed when adopting rapid production technology. We conclude by arguing that all firms should adopt rapid production technology to avoid becoming at a disadvantage.
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 | 0.000 | 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 | 0.000 |
| 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