The integration of quality management and continuous improvement methodologies with management systems
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
For organisations to be successful, the use of well-structured management systems (MSs), quality management (QM) approach and methodologies for continuous improvement (CI) are all essential. Total quality management (TQM) has been a dominant management concept for CI utilising Deming's concepts of Plan-Do-Check-Act (PDCA). Lean Six Sigma (LSS) is a widely-accepted methodology for CI considered among most modern in the 2000s. Recently, different MSs have gained more attention as they form critical infrastructure for improving and controlling different operating areas of any organisation. In many industries, CI methodologies and MSs are separately implemented, either formally or informally. The lack of their proper integration is one of the main reasons why lots of implementation efforts of CI fail, since it ensures alignment of activities and provides industry with competitive advantage. Thus, the need and benefits for formulating such integration of QM and CI with a comprehensive MS are discussed in this study.
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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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