Six Sigma
Advanced Tools for Black Belts and Master Black Belts
1st Edition
Published on 4. April 2007
426 pages
978-0-470-06199-2 (ISBN)
Description
The 2007 winner of the Masing Book Prize sets out important SixSigma concepts and a selection of up-to-date tools for qualityimprovement in industry.
Six Sigma is a widely used methodology for measuring andimproving an organization's operational performance through arigorous analysis of its practices and systems.
This book presents a series of papers providing a systematic'roadmap' for implementing Six Sigma, following theDMAIC (Define, Measure, Analyse, Improve and Control) phasedapproach. Motivated by actual problems, the authors offerinsightful solutions to some of the most commonly encounteredissues in Six Sigma projects, such as validation of normality,experimentation under constraints and statistical control ofcomplex processes. They also include many examples and case studiesto help readers learn how to apply the appropriate techniques toreal-world problems.
Key features:
* Provides a comprehensive introduction to Six Sigma, with acritical strategic assessment and a SWOT (Strengths, Weaknesses,Opportunities and Threats) analysis.
* Presents some prominent design features of Six Sigma, and anewly proposed roadmap for healthcare delivery.
* Sets out information on graphical tools, including fishbonediagrams, mind-maps, and reality trees.
* Gives a thorough treatment of process capability analysis fornon-normal data.
* Discusses advanced tools for Six Sigma, such as statisticalprocess control for autocorrelated data.
Consolidating valuable methodologies for process optimizationand quality improvement, Six Sigma: Advanced Tools for BlackBelts and Master Black Belts is a unique reference forpractising engineers in the electronics, defence, communicationsand energy industries. It is also useful for graduate studentstaking courses in quality assurance.
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Loon Ching Tang | Thong Ngee Goh | Hong See Yam
Six Sigma - Advanced Tools for Black Belts and Master Black Belts
Software
10/2006
Wiley
€89.49
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Loon Ching Tang | Thong Ngee Goh | Hong See Yam
Six Sigma
Advanced Tools for Black Belts and Master Black Belts
Book
10/2006
1st Edition
Wiley
€160.50
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Persons
Loon Ching Tang, Industrial & Systems EngineeringDepartment, National University of Singapore, 1. Engineering Drive2, Singapore 117576
Loon Ching Tang is currently Associate Professor at the Industrial& Systems Engineering Department, National University ofSingapore. He has been lecturing at the University since 1992 andhis research interests include design for Six Sigma, reliabilitytesting and prediction for electronic products, and statisticalmethods for quality improvement. He is also Manager of the GraduateProgramme, Leader of the Quality Engineering Research Group andDeputy Head of Research in the department. Alongside his work atthe university, Professor Tang has consulted for companies such asPhilips (DAP), Hewlett-Packard, and the Ministry of Defence. He haswritten over 50 journal articles, book chapters and edited andwritten for the publication Operational Research Applications inSingapore (Operational Research Society of Singapore).
Thong Nee Goh, Industrial & Systems EngineeringDepartment, National University of Singapore, 1. Engineering Drive2, 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 highyield processes, experimental strategies for yield improvement ofcomplex processes and application of Six Sigma methodologies. Healso on the Editorial Board of a number of quality and reliabilityengineering journals, including Quality Reliability EngineeringInternational (Wiley), and he authored the second mostdownloaded article in 2004: "A Strategic Assessment of SixSigma".
Hong See Yam, Six Sigma Director (Asia Pacific), SeagateTechnology International
Timothy Yaop, Six Sigma Master Black Belt, SeagateTechnology International
Content
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. Tangand H. S. Yam).
7. Fishbone Diagrams vs. Mind Maps (TimothyYoap).
8. Current and Future Reality Trees (TimothyYoap).
9. Computing Process Capability Indices for Nonnormal Data: AReview and Comparative Study (L. C. Tang, S. E. Thanand B. W. Ang).
10. Process Capability Analysis for Non-Normal Data withMINITAB (Timothy Yoap).
PART C: ANALYZE PHASE.
11. Goodness-of-Fit Tests for Normality (L. C. Tangand 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 Limitsof Cpk (L. C. Tang, S. E. Thanand B. W. Ang).
14. Data Transformation for Geometrically Distributed QualityCharacteristics (T. N. Goh, M. Xie and X. Y.Tang).
15. Development of A Moisture Soak Model For Surface MountedDevices (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 OperationalConstraints (T. N. Goh).
18. Taguchi Methods: Some Technical, Cultural and PedagogicalPerspectives (T. N. Goh).
19. Economical Experimentation via 'LeanDesign' (T. N. Goh).
20. A Unified Approach for Dual Response SurfaceOptimization (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 andAutocorrelation 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 AutocorrelatedObservations (L. C. Tang and O. O. Atienza).
Index.
