Lean Six Sigma Green Belt (LSSGB) is catered to a professional, who is well trained in the Lean Six Sigma methodology who both leads or supports improvement projects, typically as a part-time role. A Lean Six Sigma Green Belt possesses a detailed knowledge about how to use Six Sigma tools and how to use standard principles of Lean.
IASSC (International Association of Six Sigma Certification) is a Professional Association dedicated to growing and enhancing the standards within the Lean Six Sigma community.
This 4-day classroom-led course is based in IASSC LSSGB body of knowledge that is the
basis of the IASSC Certified Green Belt Exam. The exam’s questions may test up to the complexity level of “Apply” as defined by Levels of Cognition based on Bloom’s
Taxonomy – Revised (2001).
Course Outline
1.0 Define Phase
- The Basics of Six Sigma
- Meaning of Six Sigma
- General History of Six Sigma & Continuous Improvement
- Deliverables of a Lean Six Sigma Project
- The Problem-Solving Strategy Y = f(x)
- Voice of the Customer, Business and Employee
- Six Sigma Roles & Responsibilities
- The Fundamentals of Six Sigma
- Defining a Business Process
- Critical to Quality Characteristics (CTQ’s)
- Cost of Poor Quality (COPQ)
- Pareto Analysis (80:20 rule)
- Basic Six Sigma Metrics
- Selecting Lean Six Sigma Projects
- Building a Business Case & Project Charter
- Developing Project Metrics
- Financial Evaluation & Benefits Capture
- The Lean Enterprise
- Understanding Lean
- The History of Lean
- Lean & Six Sigma
- The Seven Elements of Waste
- 5S
2.0 Measure Phase
- Process Definition
- Cause & Effect/ Fishbone Diagrams
- Process Mapping, SIPOC, Value Stream Map X-Y Diagram
- Failure Modes & Effects Analysis (FMEA)
- Six Sigma Statistics
- Basic Statistics
- Descriptive Statistics
- Normal Distributions & Normality
- Graphical Analysis
- Measurement System Analysis
- Precision & Accuracy
- Bias, Linearity & Stability
- Gage Repeatability & Reproducibility
- Variable & Attribute MSA
- Process Capability
- Capability Analysis
- Concept of Stability
- Attribute & Discrete Capability
- Monitoring Techniques
3.0 Analyze Phase
- Patterns of Variation
- Multi-Vari Analysis
- Classes of Distributions
- Inferential Statistics
- Understanding Inference
- Sampling Techniques & Uses
- Central Limit Theorem
- Hypothesis Testing
- General Concepts & Goals of Hypothesis Testing
- Significance; Practical vs. Statistical
- Risk; Alpha & Beta
- Types of Hypothesis Test
- Hypothesis Testing with Normal Data
- 1 & 2 sample t-tests
- 1 sample variance
- One Way ANOVA
- Hypothesis Testing with Non-Normal Data
- Mann-Whitney
- Kruskal-Wallis
- Mood’s Median Friedman
- 1 Sample Sign
- 1 Sample Wilcoxon
- One and Two Sample Proportion
- Chi-Squared (Contingency Tables)
4.0 Improve Phase
- Simple Linear Regression
- Correlation
- Regression Equations
- Residuals Analysis
- Multiple Regression Analysis
- Non-Linear Regression
- Multiple Linear Regression
- Confidence & Prediction Intervals
- Residuals Analysis
- Data Transformation, Box Cox
5.0 Control Phase
- Lean Controls
- Controls Methods 5S
- Kanban
- Poka-Yoke (Mistake Proofing)
- Statistical Process Control (SPC)
- Data Collection for SPC
- I-MR Chart
- Xbar-R Chart
- U Chart
- P Chart
- NP Chart
- X-S chart
- CumSum Chart
- EWMA Chart
- Control Chart Anatomy
- Six Sigma Control Plans
- Cost Benefit Analysis
- Elements of the Control Plan
- Elements of the Response Plan
