Challenges and Solutions to Adopt Smart Maintenance in SMEs: A Literature Review and Research Agenda
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
Industry 4.0 (I4.0) is transforming maintenance strategies, ushering in an era of smart maintenance. Smart maintenance has been extensively studied since 2011; however, the SMEs’ attributes are barely involved. Smart maintenance is a game-changer for SMEs by bolstering their competitiveness in cost, reliability, and efficiency. This paper comprehensively reviews the literature on the application of smart maintenance in SMEs. Despite limited papers on smart maintenance for SMEs, a surge has been observed in recent years, underscoring the relevance of this review. It also synthesizes the literature to pinpoint the challenges and opportunities associated with implementing smart maintenance in SMEs. Furthermore, it outlines future research directions in terms of theory, context, and methodology.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| 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