Hong See Yam & Loon Ching Tang 
Six Sigma 
Advanced Tools for Black Belts and Master Black Belts

The 2007 winner of the Masing Book Prize sets out important Six
Sigma concepts and a selection of up-to-date tools for quality
improvement in industry.

Six Sigma is a widely used methodology for measuring and
improving an organization’s operational performance through a
rigorous analysis of its practices and systems.

This book presents a series of papers providing a systematic
‘roadmap’ for implementing Six Sigma, following the
DMAIC (Define, Measure, Analyse, Improve and Control) phased
approach. Motivated by actual problems, the authors offer
insightful solutions to some of the most commonly encountered
issues in Six Sigma projects, such as validation of normality,
experimentation under constraints and statistical control of
complex processes. They also include many examples and case studies
to help readers learn how to apply the appropriate techniques to
real-world problems.

Key features:

* Provides a comprehensive introduction to Six Sigma, with a
critical strategic assessment and a SWOT (Strengths, Weaknesses,
Opportunities and Threats) analysis.

* Presents some prominent design features of Six Sigma, and a
newly proposed roadmap for healthcare delivery.

* Sets out information on graphical tools, including fishbone
diagrams, mind-maps, and reality trees.

* Gives a thorough treatment of process capability analysis for
non-normal data.

* Discusses advanced tools for Six Sigma, such as statistical
process control for autocorrelated data.

Consolidating valuable methodologies for process optimization
and quality improvement, Six Sigma: Advanced Tools for Black
Belts and Master Black Belts is a unique reference for
practising engineers in the electronics, defence, communications
and energy industries. It is also useful for graduate students
taking courses in quality assurance.

قائمة المحتويات

Preface.

PART A: SIX SIGMA: PAST, PRESENT AND FUTURE.

1. Six Sigma: A Preamble (H. S. Yam).

2. A Strategic Assessment of Six Sigma (T. N.
Goh).

3. Six Sigma SWOT (T. N. Goh and L. C. Tang).

4. The Essence of Design for Six Sigma (L. C.
Tang).

5. Fortifying Six Sigma with OR/MS Tools (L. C.
Tang, T. N. Goh and S. W. Lam).

PART B: MEASURE PHASE.

6. Process Variations and Their Estimates (L. C. Tang
and H. S. Yam).

7. Fishbone Diagrams vs. Mind Maps (Timothy
Yoap).

8. Current and Future Reality Trees (Timothy
Yoap).

9. Computing Process Capability Indices for Nonnormal Data: A
Review and Comparative Study (L. C. Tang, S. E. Than
and B. W. Ang).

10. Process Capability Analysis for Non-Normal Data with
MINITAB (Timothy Yoap).

PART C: ANALYZE PHASE.

11. Goodness-of-Fit Tests for Normality (L. C. Tang
and S. W. Lam).

12. Introduction to the Analysis of Categorical Data
(L.C. Tang and S. W. Lam).

13. A Graphical Approach to Obtaining Confidence Limits
of Cpk (L. C. Tang, S. E. Than
and B. W. Ang).

14. Data Transformation for Geometrically Distributed Quality
Characteristics (T. N. Goh, M. Xie and X. Y.
Tang).

15. Development of A Moisture Soak Model For Surface Mounted
Devices (L. C. Tang and S. H. Ong).

PART D: IMPROVE PHASE.

16. A Glossary for Design of Experiments with Examples
(H. S. Yam).

17. Some Strategies for Experimentation under Operational
Constraints (T. N. Goh).

18. Taguchi Methods: Some Technical, Cultural and Pedagogical
Perspectives (T. N. Goh).

19. Economical Experimentation via ‘Lean
Design’ (T. N. Goh).

20. A Unified Approach for Dual Response Surface
Optimization (L. C. Tang and K. Xu).

PART E: CONTROL PHASE.

21. Establishing Cumulative Conformance Count Charts
(L. C. Tang and W. T. Cheong).

22. Simultaneous Monitoring of the Mean, Variance and
Autocorrelation Structure of Serially Correlated Processes
(O. O. Atienza and L. C. Tang).

23. Statistical Process Control for Autocorrelated Processes
:ASurvey and An Innovative Approach (L. C. Tang and O. O.
Atienza).

24. Cumulative Sum Charts with Fast Initial Response
(L. C. Tang and O. O. Atienza).

25. CUSUM and Backward CUSUM for Autocorrelated
Observations (L. C. Tang and O. O. Atienza).

Index.

عن المؤلف

Loon Ching Tang, Industrial & Systems Engineering
Department, National University of Singapore, 1. Engineering Drive
2, Singapore 117576

Loon Ching Tang is currently Associate Professor at the Industrial
& Systems Engineering Department, National University of
Singapore. He has been lecturing at the University since 1992 and
his research interests include design for Six Sigma, reliability
testing and prediction for electronic products, and statistical
methods for quality improvement. He is also Manager of the Graduate
Programme, Leader of the Quality Engineering Research Group and
Deputy Head of Research in the department. Alongside his work at
the university, Professor Tang has consulted for companies such as
Philips (DAP), Hewlett-Packard, and the Ministry of Defence. He has
written over 50 journal articles, book chapters and edited and
written for the publication Operational Research Applications in
Singapore (Operational Research Society of Singapore).

Thong Nee Goh, Industrial & Systems Engineering
Department, National University of Singapore, 1. Engineering Drive
2, Singapore 117576

Thong Nee Goh is currently Professor at the Industrial &
Systems Engineering Department, National University of Singapore.
His research interests include statistical techniques for high
yield processes, experimental strategies for yield improvement of
complex processes and application of Six Sigma methodologies. He
also on the Editorial Board of a number of quality and reliability
engineering journals, including Quality Reliability Engineering
International (Wiley), and he authored the second most
downloaded article in 2004: ‘A Strategic Assessment of Six
Sigma’.

Hong See Yam, Six Sigma Director (Asia Pacific), Seagate
Technology International

Timothy Yaop, Six Sigma Master Black Belt, Seagate
Technology International