The role of statistical design of experiments in Six Sigma: Perspectives of a practitioner

Quality Engineering

Volumn 14, Issue 4, 2002, Pages 659-671

  Goh, T N ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Design for Six Sigma; Design of experiments; Robust design; Six Sigma; Statistical quality control; Taguchi methods

Indexed keywords

PERSONNEL TRAINING; PRODUCT DESIGN; QUALITY OF SERVICE; STATISTICAL METHODS;

SIX SIGMA; TAGUCHI METHODS;

QUALITY CONTROL;

EID: 0036609905     PISSN: 08982112     EISSN: None     Source Type: Journal    
DOI: 10.1081/QEN-120003565     Document Type: Article

References (44)

1. Six Sigma: A breakthrough strategy for profitability
2. The evolution of Six Sigma
3. Six Sigma improves both statistical training and processes
4. Six Sigma and the future of the quality profession
5. Impact of Six Sigma on quality engineering
6. The statistically designed experiment
7. Off-line quality control, parameter design, and the Taguchi method (with discussion)
8. An overview of the strategy and tactics of Taguchi
9. Taguchi methods: Some technical, cultural and pedagogical perspectives
10. An explanation and critique of Taguchi's contribution to quality engineering
11. Signal to noise ratios, performance criteria and transformations (with discussions)
12. Cautions for Taguchi lovers
13. Interactions: Ignore them at your own risk (how Taguchi's confirmation run strategy can lead to trouble)
14. The impact of Six Sigma improvement a glimpse into the future of statistics
15. Industrial use of statistically designed experiments: Case study references and some historical anecdotes
16. Information transformation perspective on experimental design in Six Sigma
17. Better than Taguchi orthogonal tables
18. Dorian Shainin's variables search procedure: A critical assessment
19. Robust design: A cost-effective method for improving manufacturing processes
20. Creating robust work processes