Six-Sigma and Taguchi Approaches to the Printed Circuit Board Quality Improvement
Bibliographic record
Abstract
Problem: The manufacturing of printed circuit board (PCB) has been popularly developed, which demands quality and being effective in increasing customers’ satisfaction, decreasing costs, reducing defects and profitable warranty. However, practical experiences in the process of using statistic quality method – to be particularly significant in the manufacturing of PCB have shown over 60% of all circuit failures relating to the printing process which is the most critical step in PCB manufacturing. Approach: The aims of this research are to apply the Six-Sigma DMAIC to reduce the defects and improve the quality of PCB. At the beginning steps, process capability analysis (PCA) is employed to inspect and analyze the current printing operations. Afterwards, Taguchi method is applied to design experiments, analyze the significant factors and determine the optimum settings.Results: Taguchi is the core statistical tools for Six Sigma improvement and attaining a higher Six Sigma level, so by applying the optimal settings, the printing process can also be improved.
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 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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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 teacher head, 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".