Essentials of Lean Six Sigma


  • Salman Taghizadegan, Chemical Engineer & Lean Six Sigma Master Black Belt Certified Hunter Industries, Inc. San Marcos, CA

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.
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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 ManufacturingGraduate Business Students concentrating in Manufacturing and Industrial Management


Book information

  • Published: June 2006
  • ISBN: 978-0-12-370502-0


“… 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

Table of Contents

PART I: Statistical Theory and ConceptsChapter 1. Introduction to Essentials of Lean Six Sigma (6)Strategies1.1 Lean Six Sigma (6 ) Concepts Review1.1.1 The Philosophy1.1.2 Lean/Kaizen Six Sigma Engineering1.2 Six Sigma Background1.3 Some Six Sigma SuccessesChapter 2. Statistical Theory of Lean Six Sigma (6 ) Strategies2.1 Normal Distribution Curve2.2 Six Sigma Process Capability Concepts2.2.1 Six Sigma Short Term Capability2.2.2 Estimation of Six Sigma Long Term CapabilityChapter 3. Mathematical Concepts of Lean Six Sigma Engineering Strategies3.1 Process Modeling (The heart of Lean Six Sigma)3.2 The Normal Distribution3.3 The Standard Normal Distribution3.4 t-Distribution3.4.1 Confidence interval for difference of two mean3.5 Binomial Distribution3.6 Poisson Distribution3.7 Exponential Distribution3.8 Hypegeometric Distribution3.9 Normality Test3.9.1 Kurtosis 3.9.2 Anderson Darling3.10 Reliability Engineering and Estimation3.11 Quality CostPART II Six Sigma Engineering and ImplementationChapter 4. Six Sigma Continuous Improvement4.1 Six Sigma Continuous Improvement Principles4.2 Six Sigma Systems4.2 Six Sigma Improvement and Training ModelChapter 5. Design for Six Sigma5.1 Design for Six Sigma (DFSS) Principles5.2 Design for Six Sigma Steps5.3 Tools and Techniques5.4 Process ManagementChapter 6. Design for Lean/Kaizen Six Sigma6.1 Lean Six Sigma and Principles6.1.1 Elements of Lean Manufacturing/Production6.1.2 Waste Types in the Lean Manufacturing6.1.3 The Five Lean Themes and Steps 6.2 The Elements of Measurements 6.2.1 Strategic Measurement Model6.2.2 Key Elements that Make a Product Successful in the Market Place 6.3 Competitive Product Benchmarking Concepts6.4 Integration of Six Sigma, Lean and Kaizen6.4.1 Six Sigma, Lean and Kaizen Principles6.4.2 Prolong Production Performance (PPP)6.4.3 A Lean Concept in Reduction of Lead-Time6.5 Lean/Kaizen Six Sigma Infrastructure Evolution Tools and highlights in Summary6.5.1 Corporate Commitment6.5.2 Steps to Achieve the Six Sigma Goals6.6 Mathematical Modeling of Lean Six Sigma Relations6.6.1 Lean Six Sigma Experimental DesignChapter 7. The Roles and Responsibilities to Six Sigma Philosophy and Strategy7.1 The Roadmap to Six Sigma Philosophy and Strategy7.2 Creation of Six Sigma Infrastructure7.2.1 Executive Sponsor 7.2.2 Champion7.2.3 Master Black Belt 7.2.4 Black Belt (Team Leader)7.2.5 Green Belt (Team Participant)7.2.6 Team Recognition/ CompensationChapter 8. The Road Map to Lean Six Sigma Continuous Improvement Engineering Strategies8.1 Six-Sigma Continuous Improvement Engineering8.2 Definition and Measurement8.2.1 Phase 0: Process Definition/ Project Selection8.2.1.1 Project Objectives and strategies8.2.1.2 Process Definition Tools and Techniques8.2.2 Phase I: Process Measurement8.2.2.1 Process Measurement Objectives8.2.2.2 Measurement Tools and Techniques8.2.2.3 Key Basic Statistical Backgrounds8.3 Evaluation of Existing Process Sigma/Base Line Sigma8.4 Data Analysis8.4.1 Phase II: Process Analysis8.4.1.1 Process Analysis Objectives8.4.1.2 Analysis Tools and Techniques8.5 Optimization and Improvement8.5.1 Phase III: Process Improvement8.5.1.1 Process Improvement Objectives8.5.1.2 Improvement Tools and Techniques8.6 Evaluation of New Sigma8.7 Process Control8.7.1 Phase IV: Process Control and Maintain Process Control Objectives Control Tools and TechniquesPART III: Case StudiesChapter 9Case Study 9.1: Methodology for Machine DowntimeReduction. A Green Belt methodology9.1.1 Phase 0: Problem Statement9.1.2 Phase 1: Data collection and measurement9.1.3 Phase 2: Analysis of measurement9.1.4 Phase 3: Improvement and verify the analyzed data 9.1.5 Phase 4: Control and maintainCase Study 9.2: Methodology for Defect Reduction in Injection Molding Tools Life time. A Black Belt methodology.9.2.1 Phase 0: Statement of Issues9.2.2 Phase 1: Data collection and measurement9.2.3 Phase 2: Analysis of collected data9.2.4 Phase 3: The process of improvement9.2.5 Phase 4: The process of control and maintainChapter 10. Case Study: Methodology for Defect Reduction in Injection Molding a Multi-Factor Central Composite Design Approach. A Master Black Belt methodology10.1 Scope of Injection Molded Parts10.2 Composite Design Methodology (Design Of Experiment)10.3 Modeling (Prediction Equations)10.4 Simulation10.5 Conclusion