Quality management in heavy duty manufacturing industry: TQM vs. Six Sigma
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
‘Is TQM a management fad?’ This question has been extensively documented in the quality management literature, and is tackled in this research through a critical literature review on the area. The ‘TQM vs. Six Sigma' debate, which has also been a fundamental challenge in this research field, is addressed by a thematic and chronological review of the peer papers. To evaluate this challenge in practice, a primary research in heavy duty machinery production industry has been conducted using a case-study on J C Bamford Excavators Ltd, the largest European construction machinery producer. The result highlights the fact that TQM is a natural foundation upon which to build Six Sigma; and not surprisingly the quality yield in a TQM approach complemented by Six Sigma is far higher and more stable than when TQM with no Six-Sigma focus is put in place, thus presenting the overall finding that TQM and Six Sigma are complements, not substitutes. The study concludes with an overview on quality management approaches in the heavy duty manufacturing industry to highlight the way forward.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it