A guideline to implement a CPS architecture in an SME
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 Industry 4.0 context, data valorisation allows industries to develop new capabilities, create competitive advantages and achieve manufacturing sustainability, but technological infrastructures are needed to support system interoperability and to manage datas. These infrastructures are not enought mature in many industrial environments, especially in small and medium enterprises (SMEs). Technology integration is challenging due to system and information heterogeneity , and even more so in SMEs that have constraint environment and which lack specific research study. . Although several approaches have been proposed, the literature lacks empirical evidence of the adoption of new technologies in SMEs. This paper presents a guideline for implementing a Cyber-Physical system (CPS) architecture in an SME and its application in an organic flour mill in Montreal. The case study provides evidence of the possibility to implement a CPS architecture in SMEs and can serve as an inspiration for SME to develop an Industry 4.0 strategy.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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