Six Sigma
Advanced Tools for Black Belts and Master Black Belts
Loon Ching Tang, Thong Ngee Goh, Hong See Yam, Timothy Yoap
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Six Sigma
Advanced Tools for Black Belts and Master Black Belts
Loon Ching Tang, Thong Ngee Goh, Hong See Yam, Timothy Yoap
Ă propos de ce livre
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.