Exploring the Effects of Industry 4.0/5.0 on Human Factors: A Preliminary Systematic Literature Review
Bibliographic record
Abstract
Industry 5.0, built on the foundation of Industry 4.0, aims to integrate human capabilities and principles for a sustainable and human-centric industrial paradigm. This article proposes a systematic literature review to explore the empirical effects of Industry 4.0/5.0 (I4.0/5.0) technologies on human factors, emphasizing the often overlooked physical, psychological, and cognitive dimensions. The methodology, adhering to PRISMA guidelines, involved a Scopus search spanning from 2005-2023, ultimately resulting in a selection of 15 articles. The preliminary results depict the studied I4.0/5.0 technologies and their impact on workers’ physical, psychological, and cognitive aspects. Some (I4.0/5.0) technologies received significant attention, such as human-robot communication and human-robot interaction, while others remain understudied. The limited number of papers makes it difficult to compare and generalize the empirical results reported. In this regard, we propose avenues for refining this systematic literature review in future research endeavors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.025 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".