Link Between Sustainability and Industry 4.0: Trends, Challenges and New Perspectives
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
The increasing number of studies that underline the relationship between industry 4.0 and sustainability shows that sustainability is one of the pillars of smart factories. Through a bibliometric performance and network analysis (BPNA), this research describes the existing relationship between industry 4.0 and sustainability, the strategic themes from 2010 to March 2019, as well as the research gaps for proposing future work. With this goal in mind, 894 documents and 5621 keywords were included for bibliometric analysis, which were treated with the support of Science Mapping Analysis Software Tool (SciMAT). The bibliometric performance analysis presented the number of publications over time and the most productive journals. The strategic diagram shown 12 main research clusters, which were measured according to bibliometric indicators. Moreover, the network structure of each cluster was depicted, and the patterns found were discussed based on the documents associated to the network. Our findings show the scientific efforts are focused to enhance economic and environmental aspects and highlights a lack of effort relating the social sphere. Finally, the paper concludes the challenges, perspectives, and suggestions for the potential future work in the field of study relating to industry 4.0 and sustainability.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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