Training for managers not skilled in Industry 4.0 basis: what is the most suitable content to be covered?
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 study aims to validate adequate content for Industry 4.0 training recommended to managers unfamiliar with this theme and intends to get a holistic view. A Delphi Method was conducted with experts in Industry 4.0 and training. These experts evaluated an initial training content structure segmented into seven modules based on academic literature. The consensus was reached in two rounds with the participation of twenty-seven (27) experts in the first round and twenty (20) experts in the second round. The results were discussed considering literature statements. The initial training content structure was reordered and an additional module was appended. The validated training content structure considers a total of eight modules ordered as follows: Business Management Models Impact; Product Personalisation and Smart Products; Smart Factory and Integration; Modularity and Service Orientation; Decentralisation and Interoperability; Virtualisation and Real-Time Capability; Corporate Social Responsibility (CSR) and Sustainability Impact; and Industry 4.0 Implementation. The results presented here are helpful for academics, consultants, and professionals who need to design courses and training about Industry 4.0 theme. It is essential to mention that no similar papers were found in scientific databases, reinforcing the originality and the contribution of this research.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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