Lean Six Sigma Yellow Belts
Module 1: The Basic of Six Sigma
- Meanings 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
Module 2: The Fundamentals of Six Sigma
- Defining a Process
- Critical to Quality Characteristics (CTQ’s)
- Cost of Poor Quality (COPQ)
- Pareto Analysis (80:20 rule)
- Basic Six Sigma Metrics: including DPU, DPMO,
Module 3: Selecting Lean Six Sigma Projects
- Building a Business Case & Project Charter
- Developing Project Metrics
- Financial Evaluation & Benefits Capture
Module 4: The Lean Enterprise
- Understanding Lean
- The History of Lean
- Lean & Six Sigma
- The Seven Elements of Waste: a. Overproduction, Correction, Inventory, Motion, Overprocessing,
- Conveyance, Waiting
- 5S: Straighten, Shine, Standardize, Self-Discipline, Sort
Module 5: Process Definition
- Cause & Effect / Fishbone Diagrams
- Process Mapping, SIPOC, Value Stream Map
- X-Y Diagram
- Failure Modes & Effects Analysis (FMEA)
Module 6: Six Sigma Statistics
- Basic Statistics
- Descriptive Statistics
- Normal Distributions & Normality
- Graphical Analysis
Module 7: Measurement System Analysis
- Precision & Accuracy
- Bias, Linearity & Stability
- Gage Repeatability & Reproducibility
- Variable & Attribute MSA
Module 8: Process Capability
- Capability Analysis
- Concept of Stability
- Attribute & Discrete Capability
- Monitoring Techniques
Module 9: Lean Controls
- Control Methods for 5S
- Kanban
- Poka-Yoke (Mistake Proofing)
Module 10: Six Sigma Control Plans
- Cost Benefit Analysis
- Elements of the Control Plan
- Elements of the Response Plan
Lean Six Sigma Green Belts
Module 1: The Basic of Six Sigma
- Meanings 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
Module 2: The Fundamentals of Six Sigma
- Defining a Process
- Critical to Quality Characteristics (CTQ’s)
- Cost of Poor Quality (COPQ)
- Pareto Analysis (80:20 rule)
- Basic Six Sigma Metrics: including DPU, DPMO, FTY, RTY Cycle Time, deriving these metrics and these metrics
Module 3: Selecting Lean Six Sigma Projects
- Building a Business Case & Project Charter
- Developing Project Metrics
- Financial Evaluation & Benefits Capture
Module 4: The Lean Enterprise
- Understanding Lean
- The History of Lean
- Lean & Six Sigma
- The Seven Elements of Waste: a. Overproduction, Correction, Inventory, Motion, Overprocessing,
- Conveyance, Waiting
- 5S: Straighten, Shine, Standardize, Self-Discipline, Sort
Module 5: Process Definition
- Cause & Effect / Fishbone Diagrams
- Process Mapping, SIPOC, Value Stream Map
- X-Y Diagram
- Failure Modes & Effects Analysis (FMEA)
Module 6: Six Sigma Statistics
- Basic Statistics
- Descriptive Statistics
- Normal Distributions & Normality
- Graphical Analysis
Module 7: Measurement System Analysis
- Precision & Accuracy
- Bias, Linearity & Stability
- Gage Repeatability & Reproducibility
- Variable & Attribute MSA
Module 8: Process Capability
- Capability Analysis
- Concept of Stability
- Attribute & Discrete Capability
- Monitoring Techniques
Module 9: Patterns of Variation
- Multi-Vari Analysis
- Classes of Distributions
Module 10: Inferential Statistics
- Understanding Inference
- Sampling Techniques & Uses
- Central Limit Theorem
Module 11: Hypothesis Testing
- General Concepts & Goals of Hypothesis Testing
- Significance; Practical vs. Statistical
- Types of Hypothesis Test
- Risk; Alpha & Beta
Module 12: Hypothesis Testing with Normal Data
- 1 & 2 sample t-tests
- 1 sample variance
- One Way ANOVA: a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results
Module 13: 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): a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results
Module 14: Simple Linear Regression
- Correlation
- Regression Equations
- Residuals Analysis
Module 15: Multiple Regression Analysis
- Non-Linear Regression
- Multiple Linear Regression
- Confidence & Prediction Intervals
- Residuals Analysis
- Data Transformation, Box Cox
Module 16: Lean Controls
- Control Methods for 5S
- Kanban
- Poka-Yoke (Mistake Proofing)
Module 17: 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
Module 18: Six Sigma Control Plans
- Cost Benefit Analysis
- Elements of the Control Plan
- Elements of the Response Plan
Lean Six Sigma Black Belts
Module 1: The Basic of Six Sigma
- Meanings 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
Module 2: The Fundamentals of Six Sigma
- Defining a Process
- Critical to Quality Characteristics (CTQ’s)
- Cost of Poor Quality (COPQ)
- Pareto Analysis (80:20 rule)
- Basic Six Sigma Metrics: including DPU, DPMO, FTY, RTY Cycle Time, deriving these metrics and these metrics
Module 3: Selecting Lean Six Sigma Projects
- Building a Business Case & Project Charter
- Developing Project Metrics
- Financial Evaluation & Benefits Capture
Module 4: The Lean Enterprise
- Understanding Lean
- The History of Lean
- Lean & Six Sigma
- The Seven Elements of Waste: a. Overproduction, Correction, Inventory, Motion, Overprocessing, Conveyance, Waiting
- 5S: Straighten, Shine, Standardize, Self-Discipline, Sort
Module 5: Process Definition
- Cause & Effect / Fishbone Diagrams
- Process Mapping, SIPOC, Value Stream Map
- X-Y Diagram
- Failure Modes & Effects Analysis (FMEA)
Module 6: Six Sigma Statistics
- Basic Statistics
- Descriptive Statistics
- Normal Distributions & Normality
- Graphical Analysis
Module 7: Measurement System Analysis
- Precision & Accuracy
- Bias, Linearity & Stability
- Gage Repeatability & Reproducibility
- Variable & Attribute MSA
Module 8: Process Capability
- Capability Analysis
- Concept of Stability
- Attribute & Discrete Capability
- Monitoring Techniques
Module 9: Patterns of Variation
- Multi-Vari Analysis
- Classes of Distributions
Module 10: Inferential Statistics
- Understanding Inference
- Sampling Techniques & Uses
- Central Limit Theorem
Module 11: Hypothesis Testing
- General Concepts & Goals of Hypothesis Testing
- Significance; Practical vs. Statistical
- Types of Hypothesis Test
- Risk; Alpha & Beta
Module 12: Hypothesis Testing with Normal Data
- 1 & 2 sample t-tests
- 1 sample variance
- One Way ANOVA: a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results
Module 13: 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): a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results
Module 14: Simple Linear Regression
- Correlation
- Regression Equations
- Residuals Analysis
Module 15: Multiple Regression Analysis
- Non-Linear Regression
- Multiple Linear Regression
- Confidence & Prediction Intervals
- Residuals Analysis
- Data Transformation, Box Cox
Module 16: Designed Experiments
- Experiment Objectives
- Experimental Methods
- Experiment Design Considerations
Module 17: Full Factorial Experiments
- 2k Full Factorial Designs
- Linear & Quadratic Mathematical Models
- Fit, Diagnose Model and Center Points
- Balanced & Orthogonal Designs
Module 18: Fractional Factorial Experiments
- Designs
- Confounding Effects
- Experimental Resolution
Module 19: Lean Controls
- Control Methods for 5S
- Kanban
- Poka-Yoke (Mistake Proofing)
Module 20: 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
- Subgroups, Impact of Variation, Frequency of Sampling
- Center Line & Control Limit Calculations
Module 21: Six Sigma Control Plans
- Cost Benefit Analysis
- Elements of the Control Plan
- Elements of the Response Plan
