Table of Contents for Six Sigma Handbook : A Complete Guide for Green Belts, Black Belts, and Managers at All Levels


Preface xi
Part I Six Sigma Implementation and Management
Building the Responsive Six Sigma Organization
3(40)
What Is Six Sigma?
3(10)
Why Six Sigma?
4(1)
The Six Sigma Philosophy
5(6)
The Change Imperative
11(2)
Implementing Six Sigma
13(30)
Timetable
14(2)
Infrastructure
16(16)
Integrating Six Sigma and Related Initiatives
32(2)
Deployment to the Supply Chain
34(2)
Communications and Awareness
36(7)
Recognizing Opportunity
43(44)
Becoming a Customer and Market-Driven Enterprise
44(16)
Elements of the Transformed Organization
46(2)
Strategies for Communicating with Customers and Employees
48(4)
Survey Development Case Study
52(6)
Calculating the Value of Customer Retention
58(2)
Customer Expectations, Priorities, Needs, and ``Voice''
60(5)
Quality Function Deployment
61(4)
The Six Sigma Process Enterprise
65(6)
The Source of Conflict
67(1)
A Resolution to the Conflict
67(3)
Six Sigma and the Process Enterprise
70(1)
Linking Six Sigma Projects to Strategies
71(16)
The Strategy Deployment Matrix
71(3)
Deploying Differentiators to Operations
74(1)
Deploying Operations Plans to Projects
75(1)
Interpretation
76(1)
Linking Customer Demands to Budgets
77(1)
Structured Decision-Making
77(10)
Data-Driven Management
87(30)
Attributes of Good Metrics
87(2)
The Balanced Scorecard
89(8)
Measuring Causes and Effects
90(2)
Customer Perspective
92(2)
Internal Process Perspective
94(1)
Innovation and Learning Perspective
95(1)
Financial Perspective
95(2)
Cost of Poor Quality
97(5)
Cost of Quality Examples
99(3)
Strategy Deployment Plan
102(3)
Dashboard Design
105(2)
Information Systems Requirements
107(5)
Integrating Six Sigma with Other Information Systems Technologies
108(1)
Data Warehousing
108(2)
OLAP
110(1)
Data Mining
110(2)
OLAP, Data Mining, and Six Sigma
112(1)
Benchmarking
112(5)
The Benchmarking Process
112(1)
Getting Started with Benchmarking
113(1)
Why Benchmarking Efforts Fail
114(2)
The Benefits of Benchmarking
116(1)
Some Dangers of Benchmarking
116(1)
Maximizing Resources
117(30)
Choosing the Right Projects
117(16)
Types of Projects
117(1)
Analyzing Project Candidates
118(7)
Using Pareto Analysis to Identify Six Sigma Project Candidates
125(2)
Throughput-Based Project Selection
127(6)
Ongoing Management Support
133(4)
Internal Roadblocks
133(1)
External Roadblocks
134(1)
Individual Barriers to Change
134(1)
Ineffective Management Support Strategies
135(1)
Effective Management Support Strategies
136(1)
Cross-Functional Collaboration
136(1)
Tracking Six Sigma Project Results
137(10)
Financial Results Validation
138(1)
Team Performance Evaluation
139(2)
Team Recognition and Reward
141(2)
Lessons-Learned Capture and Replication
143(4)
PART II Six Sigma Tools and Techniques
Project Management Using DMAIC and DMADV
147(18)
DMAIC and DMADV Deployment Models
147(8)
Project Reporting
152(1)
Project Budgets
153(1)
Project Records
154(1)
Six Sigma Teams
155(10)
Team Membership
155(1)
Team Dynamics Management, Including Conflict Resolution
156(1)
Stages in Group Development
157(1)
Member Roles and Responsibilities
157(1)
Management's Role
158(2)
Facilitation Techniques
160(5)
The Define Phase
165(32)
Project Charters
165(2)
Project Decomposition
167(2)
Work Breakdown Structures
167(1)
Pareto Analysis
167(2)
Deliverables
169(17)
Critical to Quality Metrics
170(9)
Critical to Schedule Metrics
179(1)
Critical to Cost Metrics
180(6)
Project Scheduling
186(8)
Gantt Charts
186(2)
PERT-CPM
188(3)
Control and Prevention of Schedule Slippage
191(1)
Cost Considerations in Project Scheduling
192(2)
Top-Level Process Definition
194(1)
Process Maps
194(1)
Assembling the Team
195(2)
The Measure Phase
197(18)
Process Definition
197(4)
Flowcharts
198(1)
SIPOC
198(3)
Metric Definition
201(5)
Measurement Scales
203(2)
Discrete and Continuous Data
205(1)
Process Baseline Estimates
206(7)
Enumerative and Analytic Studies
207(2)
Principles of Statistical Process Control
209(4)
Estimating Process Baselines Using Process Capability Analysis
213(2)
Process Behavior Charts
215(74)
Control Charts for Variables Data
215(9)
Averages and Ranges Control Charts
215(2)
Averages and Standard Deviation (Sigma) Control Charts
217(4)
Control Charts for Individual Measurements (X Charts)
221(3)
Control Charts for Attributes Data
224(9)
Control Charts for Proportion Defective (p Charts)
224(3)
Control Charts for Count of Defectives (np Charts)
227(2)
Control Charts for Average Occurrences-Per-Unit (u Charts)
229(3)
Control Charts for Counts of Occurrences-Per-Unit (c Charts)
232(1)
Control Chart Selection
233(3)
Rational Subgroup Sampling
235(1)
Control Chart Interpretation
236(8)
Run Tests
241(1)
Tampering Effects and Diagnosis
242(2)
Short Run Statistical Process Control Techniques
244(17)
Variables Data
245(10)
Attribute SPC for Small and Short Runs
255(6)
Summary of Short-Run SPC
261(1)
SPC Techniques for Automated Manufacturing
261(10)
Problems with Traditional SPC Techniques
262(1)
Special and Common Cause Charts
262(1)
EWMA Common Cause Charts
263(6)
EWMA Control Charts versus Individuals Charts
269(2)
Distributions
271(18)
Methods of Enumeration
271(2)
Frequency and Cumulative Distributions
273(1)
Sampling Distributions
274(1)
Binomial Distribution
274(1)
Poisson Distribution
275(2)
Hypergeometric Distribution
277(1)
Normal Distribution
278(4)
Exponential Distribution
282(7)
Measurement Systems Evaluation
289(32)
Definitions
289(2)
Measurement System Discrimination
291(2)
Stability
293(2)
Bias
295(1)
Repeatability
295(3)
Reproducibility
298(2)
Part-to-Part Variation
300(1)
Example of Measurement System Analysis Summary
301(5)
Gage R&R Analysis Using Minitab
302(4)
Linearity
306(4)
Linearity Analysis Using Minitab
308(2)
Attribute Measurement Error Analysis
310(11)
Operational Definitions
311(1)
How to Conduct Attribute Inspection Studies
312(1)
Example of Attribute Inspection Error Analysis
312(4)
Minitab Attribute Gage R&R Example
316(5)
Analyze Phase
321(72)
Value Stream Analysis
321(5)
Value Stream Mapping
323(3)
Spaghetti Charts
326(1)
Analyzing the Sources of Variation
326(16)
Cause and Effect Diagrams
327(1)
Boxplots
328(3)
Statistical Inference
331(1)
Chi-Square, Student's T, and F Distributions
332(4)
Point and Interval Estimation
336(3)
Hypothesis Testing
339(2)
Resampling (Bootstrapping)
341(1)
Regression and Correlation Analysis
342(10)
Linear Models
344(2)
Least-Squares Fit
346(5)
Correlation Analysis
351(1)
Designed Experiments
352(24)
Terminology
353(1)
Design Characteristics
354(1)
Types of Design
355(1)
One-Factor ANOVA
356(3)
Two-Way ANOVA with No Replicates
359(1)
Two-Way ANOVA with Replicates
360(1)
Full and Fractional Factorial
361(8)
Power and Sample Size
369(1)
Testing Common Assumptions
369(7)
Analysis of Categorical Data
376(13)
Making Comparisons Using Chi-Square Tests
376(2)
Logistic Regression
378(2)
Binary Logistic Regression
380(3)
Ordinal Logistic Regression
383(2)
Nominal Logistic Regression
385(4)
Non-Parametric Methods
389(4)
The Improve/Design Phase
393(62)
Using Customer Demands to Make Design and Improvement Decisions
393(9)
Category Importance Weights
394(6)
Lean Techniques for Optimizing Flow
400(1)
Tools to Help Improve Flow
400(2)
Using Empirical Model Building to Optimize
402(17)
Phase 0: Getting Your Bearings
403(1)
Phase I: The Screening Experiment
404(4)
Phase II: Steepest Ascent (Descent)
408(1)
Phase III: The Factorial Experiment
408(3)
Phase IV: The Composite Design
411(4)
Phase V: Robust Product and Process Design
415(4)
Data Mining, Artificial Neural Networks, and Virtual Process Mapping
419(1)
Example of Neural Net Models
420(1)
Optimization Using Simulation
420(23)
Predicting CTQ Performance
423(3)
Simulation Tools
426(1)
Random Number Generators
427(4)
Model Development
431(7)
Virtual Doe Using Simulation Software
438(5)
Risk Assessment Tools
443(7)
Design Review
443(1)
Fault-Tree Analysis
443(1)
Safety Analysis
444(3)
Failure Mode and Effect Analysis
447(3)
Defining New Performance Standards Using Statistical Tolerancing
450(5)
Assumptions of Formula
453(1)
Tolerance Intervals
454(1)
Control/Verify Phase
455(78)
Validating the New Process or Product Design
455(1)
Business Process Control Planning
455(14)
Maintaining Gains
456(1)
Tools and Techniques Useful for Control Planning
457(1)
Preparing the Process Control Plan
458(2)
Process Control Planning for Short and Small Runs
460(2)
Process Audits
462(1)
Selecting Process Control Elements
462(3)
Other Elements of the Process Control Plan
465(4)
Appendices
Glossary of Basic Statistical Terms
469(6)
Area Under the Standard Normal Curve
475(4)
Critical Values of the t-Distribution
479(2)
Chi-Square Distribution
481(2)
F Distribution (α = 1%)
483(2)
F Distribution (α = 5%)
485(2)
Poisson Probability Sums
487(4)
Tolerance Interval Factors
491(4)
Control Chart Constants
495(2)
Control Chart Equations
497(2)
Table of d2 Values
499(2)
Factors for Short Run Control Charts for Individuals, x-bar, and R Charts
501(2)
Sample Customer Survey
503(2)
Process σ Levels and Equivalent PPM Quality Levels
505(2)
Black Belt Effectiveness Certification
507(12)
[Company] Black Belt Skill Set Certification Process
507(1)
Introduction
507(1)
Process
507(1)
[Company] Black Belt Effectiveness Certification Criteria
508(1)
[Company] Black Belt Certification Board
509(1)
Effectiveness Questionnaire
509(1)
[Company] Black Belt Notebook and Oral Review
510(9)
Green Belt Effectiveness Certification
519(12)
Green Belt Skill Set Certification Process
519(1)
Introduction
519(1)
Green Belt Effectiveness Certification Criteria
520(1)
Green Belt Certification Board
521(1)
Effectiveness Questionnaire
521(1)
Scoring Guidelines
521(1)
Green Belt Notebook
522(9)
AHP Using Microsoft Excel™
531(2)
Example
531(2)
References 533(4)
Index 537