Lean Tools in the Context of Industry 4.0: Literature Review, Implementation and Trends
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
With the evolution of Industry 4.0, some problems related to inefficient digitalization become clearer in organizations. To minimize these problems, implementation of the lean philosophy is needed in the digital environment. However, before Lean can start to solve the digitalization problems, there is a need to digitalize its tools so that they can comprehend the Industry 4.0 dynamics and become more effective. The aim of this study is to contribute to the theoretical development of Lean tools in the context of Industry 4.0, promoting directions for the industrial sector from the evolution, difficulties, benefits, implementation and trends of Lean 4.0 tools. To achieve this objective, this study performs a systematic literature review and content analysis of 53 papers from 35 journals. The main results of the research show: (i) the characterization of the Lean 4.0 tools; (ii) the evolution of the Lean tools after the integration with digital technologies; (iii) the main trends of Lean 4.0; (iv) the proposal of a Lean 4.0 theoretical framework. From these results, this paper seeks to promote insights for studies in the area of Lean 4.0, as well as for companies to implement and use the Lean 4.0 tools for better improvement in their digital processes and avoid the digital waste.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
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