Evaluation of lean practices in warehouses: an analysis of Brazilian reality
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
Purpose This article aims to investigate the most applied lean warehouse practices in Brazilian warehouses. Design/methodology/approach To perform this research, three phases were conducted: a literature review, a multiple case study, and an analysis of lean warehouses practices implementation by an engineering committee. Thus, both qualitative and quantitative approaches were used. Additionally, the study has an applied nature, with an exploratory and descriptive character. Findings Results showed that regardless of the type of criterion used, the most implanted practices are those that do not involve investments in technology. On the other hand, practices like RFID and Cross Docking systems were not found in any of the operations, which shows numerous possibilities for improvement. Originality/value The main contribution of this article is to initiate a debate about the management and productivity of Brazilian warehouses, a theme still little explored by the academic community despite the importance that the logistic scenario represents for Brazil as an emerging country and leader in Latin America, participating actively in several global supply chains.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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