The Six Sigma Handbook

Descripción

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Descripción:
The most important reference to Lean Six Sigma fully updated for the latest advances This thoroughly revised, industry standard guide delivers all the information you need to apply Lean Six Sigma techniques and dramatically improve processes, profitability, sustainability, and long-term growth. Written by two of the foremost authorities in the field, the book contains full explanations of the latest lean, problem solving and change management principles and methods. You will discover how to build the best teams and foster effective leadership while maximizing customer satisfaction and boosting profits.

Tabla de contenidos:

Title Page
Copyright Page
Contents
Preface
PART I Six Sigma Implementation and Management
   CHAPTER 1 Building the Responsive Six Sigma Organization
   What Is Six Sigma?
   Why Six Sigma?
   The Six Sigma Philosophy
   Six Sigma Versus Traditional Three Sigma Performance
   The Change Imperative
   Implementing Six Sigma
   Timetable
   Infrastructure
   Integrating Six Sigma and Related Initiatives
   Deployment to the Supply Chain
   Communications and Awareness
   CHAPTER 2 Recognizing and Capitalizing on Opportunity
   Methods for Collecting Customer Data
   Surveys
   Focus Groups
   Operational Feedback Systems
   Cost of Poor Quality
   Cost of Quality Examples
   Quality Cost Bases
   Benchmarking
   The Benchmarking Process
   Getting Started with Benchmarking
   Why Benchmarking Efforts Fail
   The Benefits of Benchmarking
   Some Dangers of Benchmarking
   Innovation
   Kano Model
   Quality Function Deployment
   Translating Customer Demands
   Creative Destruction
   Strategic Planning
   Organizational Vision
   Strategy Development
   Strategic Styles
   Possibilities-Based Strategic Decisions
   Strategic Development Using Constraint Theory
   The Systems Approach
   Basic Constraint Management Principles and Concepts
   Tools of Constraint Management
   Constraint Management Measurements
   Summary and Conclusion
   CHAPTER 3 Data-Driven Management
   Attributes of Good Metrics
   Measuring Causes and Effects
   The Balanced Scorecard
   Translating the Vision
   Communicating and Linking
   Business Planning
   Feedback and Learning
   CHAPTER 4 Maximizing Resources
   Choosing the Right Projects
   Types of Projects
   Analyzing Project Candidates
   Using Pareto Analysis to Identify Six Sigma Project Candidates
   Throughput-Based Project Selection
   Ongoing Management Support
   Internal Roadblocks
   External Roadblocks
   Individual Barriers to Change
   Ineffective Management Support Strategies
   Effective Management Support Strategies
   Cross-Functional Collaboration
   Tracking Six Sigma Project Results
   Financial Results Validation
   Team Performance Evaluation
   Team Recognition and Reward
   Lessons-Learned Capture and Replication
PART II Six Sigma Tools and Techniques
   CHAPTER 5 Project Management Using DMAIC and DMADV
   DMAIC and DMADV Deployment Models
   Project Scheduling
   Project Reporting
   Project Budgets
   Project Records
   Six Sigma Teams
   Team Membership
   Team Dynamics Management, Including Conflict Resolution
   Stages in Group Development
   Member Roles and Responsibilities
   Management’s Role
   Facilitation Techniques
   CHAPTER 6 The Define Phase
   Project Charters
   Project Decomposition
   Work Breakdown Structures
   Pareto Analysis
   Deliverables
   Critical to Quality Metrics
   Critical to Schedule Metrics
   Critical to Cost Metrics
   Top-Level Process Definition
   Process Maps
   Assembling the Team
   CHAPTER 7 The Measure Phase
   Process Definition
   Flowcharts
   SIPOC
   Metric Definition
   Measurement Scales
   Discrete and Continuous Data
   Process Baseline Estimates
   Enumerative and Analytic Studies
   Principles of Statistical Process Control
   Estimating Process Baselines Using Process Capability Analysis
   CHAPTER 8 Process Behavior Charts
   Distributions
   Methods of Enumeration
   Frequency and Cumulative Distributions
   Sampling Distributions
   Binomial Distribution
   Poisson Distribution
   Hypergeometric Distribution
   Normal Distribution
   Lognormal Distribution
   Exponential Distribution
   Weibull Distribution
   Control Charts for Variables Data
   Averages and Ranges Control Charts
   Averages and Standard Deviation (Sigma) Control Charts
   Control Charts for Individual Measurements (X Charts)
   Control Charts for Attributes Data
   Control Charts for Proportion (p Charts)
   Control Charts for Count of Items (np Charts)
   Control Charts for Average Occurrences-Per-Unit (u Charts)
   Control Charts for Counts of Occurrences-Per-Unit (c Charts)
   Control Chart Selection
   Rational Subgroup Sampling
   Control Chart Interpretation
   Run Tests
   Short-Run Statistical Process Control Techniques
   Variables Data
   Attribute SPC for Small and Short Runs
   Summary of Short-Run SPC
   SPC Techniques for Automated Manufacturing
   Problems with Traditional SPC Techniques
   Special and Common Cause Charts
   EWMA Common Cause Charts
   EWMA Control Charts Versus Individuals Charts
   Process Capability Indices
   Example of Non-Normal Capability Analysis Using Minitab
   CHAPTER 9 Measurement Systems Evaluation
   Definitions
   Measurement System Discrimination
   Stability
   Bias
   Repeatability
   Reproducibility
   Part-to-Part Variation
   Summary Reporting
   Gage R&R Analysis Using Minitab
   Linearity
   Linearity Analysis Using Minitab
   Attribute Measurement Error Analysis
   Operational Definitions
   How to Conduct Attribute Inspection Studies
   Minitab Attribute Gage R&R Example
   CHAPTER 10 Analyze Phase
   Value Stream Analysis
   Value Stream Mapping
   Spaghetti Charts
   Analyzing the Sources of Variation
   Cause and Effect Diagrams
   Boxplots
   Statistical Inference
   Chi-Square, Student’s t, and f Distributions
   Point and Interval Estimation
   Hypothesis Testing
   Resampling (Bootstrapping)
   Regression and Correlation Analysis
   Linear Models
   Least-Squares Fit
   Correlation Analysis
   Designed Experiments
   The Traditional Approach Versus Statistically Designed Experiments
   Terminology
   Design Characteristics
   Types of Design
   One-Factor ANOVA
   Two-Way ANOVA with No Replicates
   Two-Way ANOVA with Replicates
   Full and Fractional Factorial
   Power and Sample Size
   Testing Common Assumptions
   Analysis of Categorical Data
   Making Comparisons Using Chi-Square Tests
   Logistic Regression
   Binary Logistic Regression
   Ordinal Logistic Regression
   Nominal Logistic Regression
   Non-Parametric Methods
   CHAPTER 11 The Improve/Design Phase
   Using Customer Demands to Make Design and Improvement Decisions
   Pugh Concept Selection Method
   Lean Techniques for Optimizing Flow
   Unnecessary Process Steps
   Excessive Movement of Material or Personnel
   Bottleneck or Constraint
   Process Errors Requiring Rework
   Excess In-process Inventory
   Understanding Queues to Balance Processes
   Using Empirical Model Building to Optimize
   Phase 0: Getting Your Bearings
   Phase I: The Screening Experiment
   Phase II: Steepest Ascent (Descent)
   Phase III: The Factorial Experiment
   Phase IV: The Composite Design
   Phase V: Robust Product and Process Design
   Data Mining, Artificial Neural Networks, and Virtual Process Mapping
   Example of Neural Net Models
   Optimization Using Simulation
   Predicting CTQ Performance
   Simulation Tools
   Random Number Generators
   Model Development
   Virtual DOE Using Simulation Software
   Risk Assessment Tools
   Design Review
   Fault-Tree Analysis
   Safety Analysis
   Failure Mode and Effect Analysis
   Defining New Performance Standards Using Statistical Tolerancing
   Assumptions of Formula
   Tolerance Intervals
   CHAPTER 12 Control/Verify Phase
   Validating the New Process or Product Design
   Business Process Control Planning
   Maintaining Gains
   Tools and Techniques Useful for Control Planning
   Preparing the Process Control Plan
   Process Control Planning for Short and Small Runs
   Process Audits
   Selecting Process Control Elements
   Other Elements of the Process Control Plan
   Multivariate Control Charts
   Principal Component Analysis
APPENDIX 1 Glossary of Basic Statistical Terms
APPENDIX 2 Area Under the Standard Normal Curve
APPENDIX 3 Critical Values of the t-Distribution
APPENDIX 4 Chi-Square Distribution
APPENDIX 5 F Distribution (α = 1%)
APPENDIX 6 F Distribution (α = 5%)
APPENDIX 7 Poisson Probability Sums
APPENDIX 8 Tolerance Interval Factors
APPENDIX 9 Control Chart Constants
APPENDIX 10 Control Chart Equations
APPENDIX 11 Table of d2* Values
APPENDIX 12 Factors for Short Run Control Charts for Individuals, X, and R Charts
APPENDIX 13 Sample Customer Survey
APPENDIX 14 Process s Levels and Equivalent PPM Quality Levels
APPENDIX 15 Black Belt Effectiveness Certification
APPENDIX 16 Green Belt Effectiveness Certification
APPENDIX 17 AHP Using Microsoft Excel
Notes
References
Index
   A
   B
   C
   D
   E
   F
   G
   H
   I
   J
   K
   L
   M
   N
   O
   P
   Q
   R
   S
   T
   U
   V
   W
   X
   Y
   Z