Six Sigma is a management program that provides tools that help manufacturers obtain efficient, stream-lined production to coincide with ultimate high quality products. Lean Six Sigma will show how the well-regarded analytical tools of Six Sigma quality control can be successfully brought into the well-established models of “lean manufacturing,” bringing efficient, stream-lined production and high quality product readily together. This book offers a thorough, yet concise introduction to the essential mathematics of Six Sigma, with solid case examples from a variety of industrial settings, culminating in an extended case study.
Various professionals will find this book immensely useful, whether it be the industrial engineer, the industrial manager, or anyone associated with engineering in a technical or managing role. It will bring about a clear understanding of not only how to implement Six Sigma statistical tools, but also how to do so within the bounds of Lean manufacturing scheme. It will show how Lean Six Sigma can help reinforce the notion of “less is more,” while at the same time preserving minimal error rates in final manufactured products.
Reviews the essential statistical tools upon which Six Sigma rests, including normal distribution and mean deviation and the derivation of 1 sigma through six sigma Explains essential lean tools like Value-Stream Mapping and quality improvement tools like Kaizen techniques within the context of Lean Six Sigma practice *Extended case study to clearly demonstrate how Six Sigma and Lean principles have been actually implemented, reducing production times and costs and creating improved product quality
Industrial Engineers; Quality Control and Reliability Engineers; Mechanical Engineers; Chemical Engineers; Electrical Engineers; Managers in manufacturing and Process Industries; Graduate Students; Graduate Students in Industrial Engineering in courses on Quality Control, Reliability, Advances Production Control, Statistical Quality Control and Advanced Manufacturing Graduate Business Students concentrating in Manufacturing and Industrial Management
Chapter 9 Case Study 9.1: Methodology for Machine Downtime Reduction. A Green Belt methodology 9.1.1 Phase 0: Problem Statement 9.1.2 Phase 1: Data collection and measurement 9.1.3 Phase 2: Analysis of measurement 9.1.4 Phase 3: Improvement and verify the analyzed data 9.1.5 Phase 4: Control and maintain Case Study 9.2: Methodology for Defect Reduction in Injection Molding Tools Life time. A Black Belt methodology. 9.2.1 Phase 0: Statement of Issues 9.2.2 Phase 1: Data collection and measurement 9.2.3 Phase 2: Analysis of collected data 9.2.4 Phase 3: The process of improvement 9.2.5 Phase 4: The process of control and maintain
Chapter 10. Case Study: Methodology for Defect Reduction in Injection Molding a Multi-Factor Central Composite Design Approach. A Master Black Belt methodology 10.1 Scope of Injection Molded Parts 10.2 Composite Design Methodology (Design Of Experiment) 10.3 Modeling (Prediction Equations) 10.4 Simulation 10.5 Conclusion
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- © Butterworth-Heinemann 2006
- 15th June 2006
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Chemical Engineer & Lean Six Sigma Master Black Belt Certified
Hunter Industries, Inc.
San Marcos, CA
Chemical Engineer & Lean Six Sigma Master Black Belt Certified Hunter Industries, Inc. San Marcos, CA
“… a textbook for academics and manufacturers that covers statistical theory and concepts, as well as the how-to’s of engineering and implementing Six Sigma.” — Automation World, October 2006