LEAN Approach for the Impact Study in the European Foundation for Quality Management Model Score
Bibliographic record
Abstract
Purpose: The main objective of this article is the description, analysis and explanation of the development of an integrated management model, supported by the LEAN management tools, for manufacturing companies that worked along the time on a mass production bases.Design/Methodology/Approach: The methodology used was the integration of a model supported by the EFQM – European Foundation for Quality Management system, with the principles, tools and indicators of LEAN management system.Findings: The fundamental discoveries found in the analysis and application of the case study are located in four fundamental aspects, first related to the definition of a purpose for the company ; second the clear and correct description of the business processes involved, third the involvement of people and teams and fouth the application of a thought of continuous and permanent improvement.Originality/Value: From the point of view of added value for organizations, we understand that the levels of productivity, competitiveness and value creation for shareholders are the increasingly important elements of action, and the promotion of the implementation of models that promote cost reduction and increased product quality levels are absolutely essential. The recommendations are for the implementation of new management philosophies based on the integrated behavior of continuous improvement, reduction of waste in processes and activities and constant monitoring of results through the correct application of management indicators.
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.
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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".