Curriculum Green Belt

Define Phase
1.1 The Basics of Six Sigma  1.1.1 Meanings of Six Sigma
1.1.2 General History of Six Sigma & Continuous Improvement
1.1.3 Deliverables of a Lean Six Sigma Project
1.1.4 The Problem Solving Strategy Y = f(x)
1.1.5 Voice of the Customer, Business and Employee
1.1.6 Six Sigma Roles & Responsibilities
1.2 The Fundamentals of Six Sigma     1.2.1 Defining a Process
1.2.2 Critical to Quality Characteristics (CTQ’s)
1.2.3 Cost of Poor Quality (COPQ)
1.2.4 Pareto Analysis (80:20 rule)
1.2.5 Basic Six Sigma Metrics
1.3 Selecting Lean Six Sigma Projects 1.3.1 Building a Business Case & Project Charter
1.3.2 Developing Project Metrics
1.3.3 Financial Evaluation & Benefits Capture
1.4 The Lean Enterprise 1.4.1 Basics of Lean
1.4.2 History of Lean
1.4.3 Lean & Six Sigma Integration
1.4.4 The Seven Elements of Waste
1.4.5 5S - Straighten, Shine, Standardize, Self-Discipline, Sort
Measure Phase
2.1 Process Definition 2.1.1 Cause & Effect / Fishbone Diagrams
2.1.2 Process Mapping, SIPOC, Value Stream Map
2.1.3 X-Y Diagram
2.1.4 Failure Modes & Effects Analysis (FMEA)
2.2 Lean Six Sigma Statistics 2.2.1 Basic Applied Statistics
2.2.2 Descriptive Statistics
2.2.3 Distributions
2.2.4 Graphical Analysis
2.3 Measurement System Analysis 2.3.1 Precision & Accuracy
2.3.2 Bias, Linearity & Stability
2.3.3 Gage Repeatability & Reproducibility
2.3.4 Variable & Attribute MSA
2.4 Process Capability 2.4.1 Capability Analysis
2.4.2 Concept of Stability
2.4.3 Attribute & Discrete Capability
2.4.4 Monitoring Techniques
Analyze Phase
3.1 Patterns of Variation 3.1.1 Multi-Vari Analysis
3.1.2 Classes of Distributions
3.2 Inferential Statistics 3.2.1 Understanding Inference
3.2.2 Sampling Techniques & Uses
3.2.3 Central Limit Theorem
 3.3 Hypothesis Testing 3.3.1 General Concepts & Goals of Hypothesis Testing
3.3.2 Significance; Practical vs. Statistical
3.3.3 Risk; Alpha & Beta
3.4 Hypothesis Testing with Normal Data 3.4.1 1-sample & 2 sample t-tests
3.4.2 One-Way ANOVA
3.4.3 Two-Way ANOVA
3.5 Hypothesis Testing with Non-Normal Data 3.5.1 Mann-Whitney
3.5.2 Kruskal-Wallis
3.5.3 Mood’s Median
3.5.4 Friedman
3.5.5 1 Sample Sign
3.5.6 1 Sample Wilcoxon
3.5.7 One and Two Sample Proportion
3.5.8 Chi-Squared (Contingency Tables)
Improve Phase
4.1 Simple Linear Regression 4.1.1 Correlation
4.1.2 Regression Equations
4.1.3 Residuals Diagnostics Analysis
4.2 Multiple Regression Analysis 4.2.1 Non-Linear Regression
4.2.2 Multiple Linear Regression
4.2.3 Confidence & Prediction Intervals
4.2.4 Residuals Diagnostics Analysis
4.2.5 Data Transformation, Box Cox Technique
Control Phase
5.1 Lean Controls 5.3.1 Control Methods for 5S
5.3.2 Kanban (Pull Systems)
5.3.3 Poka-Yoke (Mistake Proofing)
5.2 Statistical Process Control (SPC) 5.4.1 Data Collection for SPC
5.4.2 I-MR Chart
5.4.3 Xbar-R Chart
5.4.4 U Chart
5.4.5 P Chart
5.4.6 NP Chart
5.4.7 Xbar-S Chart
5.4.8 CumSum Chart
5.4.9 EWMA Chart
5.4.10 Control Methods
5.3 Six Sigma Control Plans 5.6.1 Cost Benefit Analysis
5.6.2 Elements of the Control Plan
5.6.3 Elements of the Response Plan
Cron Job Starts