Six Sigma Green Belt TutorialSix Sigma Green Belt Tutorial

Six Sigma Green Belt tutorial covers various areas in lean and six sigma principles, DMEA, QFD, collecting and summarizing data, statistical analysis and process control.

Vskills certification for Six Sigma – Green Belt Professional assesses the candidate as per the company’s need for deploying, managing and maintaining quality systems. The certification tests the candidates on various areas in lean and six sigma principles, DMEA, QFD, collecting and summarizing data, statistical analysis and process control.

Six Sigma (6σ) is a set of techniques and tools for process improvement.It seeks to improve the quality of the output of a process by identifying and removing the causes of defects and minimizing variability in manufacturing and business processes. It uses a set of quality management methods, mainly empirical, statistical methods, and creates a special infrastructure of people within the organization who are experts in these methods.

Table of Contents

​1. Six Sigma and Organizational Goals

1.1. History and Evolution of Six Sigma
1.2. Introduction to Six Sigma
1.3. Characteristics of Six Sigma
1.4. Improvement Process and Transfer Function
1.5. Contributions to Six Sigma
1.6. Six Sigma Projects
1.7. Six Sigma Business Processes
1.8. Organizational Drivers
1.9. Organizational Metrics and Process Improvement

2. Lean Principles and Six Sigma Projects

2.1. Introduction to Lean Principles
2.2. Lean Principles and Concepts
2.3. Application of Lean Six Sigma
2.4. Theory of Constraints (TOC)
2.5. Valuable and Non-Valuable Activities
2.6. Value Stream Mapping

3. Design for Six Sigma and FMEA

3.1. Design for Six Sigma (DFSS)
3.2. DFSS and Six Sigma Methodology
3.3. DFSS Methodologies
3.4. Failure Modes and Effects and Analysis (FMEA)
3.5. Risk Priority Number (RPN)
3.6. Design FMEA and Process FMEA


4. Six Sigma  – Project Identification

4.1. Six Sigma Project and Methodology
4.2. Six Sigma Benchmarking
4.3. Components of a Process
4.4. Input and Output – Process Variables
4.5. Project Stakeholder in Six Sigma

5. Voice of the Customer in Six Sigma

5.1. Voice of the Business and Voice of the Customer
5.2. Process of Collecting Customer Data
5.3. Effective Data Collection Techniques
5.4. Customer Requirements and QFD
5.5. House of Quality (HOQ)
5.6. HOQ Matrix

6. Six Sigma and Project Management

6.1. Six Sigma – Project Charter
6.2. Six Sigma – Project Scope
6.3. Project Metrics – Six Sigma
6.4. Project Planning Tools
6.5. Project Documentation in Six Sigma
6.6. Project Risk Analysis

7. Six Sigma Management and Planning Tools

7.1. Affinity Diagrams
7.2. Interrelationship Digraph
7.3. Tree Diagram
7.4. Prioritization Matrices
7.5. Matrix Diagrams
7.6. Process Decision Program Charts (PDPC)
7.7. Activity Network Diagrams

8. Six Sigma Performance Metrics

8.1. Performance Metrics
8.2. Defects Per Unit (DPU)
8.3. Defects Per Million Opportunity (DPMO)
8.4. Rolled Throughput Yield (RTY)
8.5. Process Capability Indices
8.6. Cost of Poor Quality (COPQ)

9. Project Team Dynamics and Performance

9.1. Six Sigma Teams
9.2. Roles and Responsibilities of Six Sigma Team
9.3. Six Sigma Team  – Roles and Responsibilities
9.4. Challenges of a Team
9.5. Tools of Six Sigma
9.6. Team Communication in Six Sigma


10. Process Analysis and Documentation

10.1. Measuring Processes
10.2. Process Mapping
10.3. Process of Documentation

11. Probability and Statistical Distribution

11.1. Probability and Events
11.2. Rules of Addition and Multiplication
11.3. Permutation and Combinations
11.4. Statistical Distributions
11.5. Binomial and Poisson Distribution

12. Data Classification, Sampling and Collection

12.1. Data Types and Measurement
12.2. Data Sampling Methods
12.3. Six Sigma Data Collection Methods
12.4. Strategies of Data Collection

13. Statistical and Graphical Presentation

13.1. Fundamentals of Statistics
13.2. Measures of Central Tendency and Dispersion
13.3. Frequency Distribution
13.4. Graphical Methods

14. Measurement System Analysis

14.1. Measurement System Analysis
14.2. Precision in Measurement Systems
14.3. Measurement Accuracy – Bias Study
14.4. Measurement Accuracy – Linearity Study
14.5. Percent Agreement

15. Performance and Process Capability Measurement

15.1. Measuring Process Performance
15.2. Process Capability Studies
15.3. Indices of Process Capability and Performance
15.4. Long-term Capability and Sigma Level


16. Six Sigma – Hypothesis Tests for Variances and Proportions

16.1. Paired Comparison T-Test
16.2. Test for Variance
16.3. Hypothesis Tests for Proportions
16.4. ANOVA
16.5. Chi-square Test

17. Six Sigma – Hypothesis Testing and Tests for Means

17.1. Introduction to Hypothesis Testing
17.2. Confidence Interval and Error Types
17.3. Power and Sample Sizes
17.4. Process – Hypothesis Testing
17.5. One Sample Tests for Means
17.6. Two-sample t-test for Means (Pooled)

18. Six Sigma – Multi-vari Studies, Correlation, and Linear Regression

18.1. Multi – Variation Analysis
18.2. Variation in Six Sigma
18.3. Correlation and Correlation Coefficient
18.4. Causation and Statistical Significance
18.5. Linear Regression


19. Six Sigma – Root Cause Analysis and Waste Elimination

19.1. Root Cause Analysis
19.2. Waste Reduction
19.3. Tools of Waste Reduction

20. Design of Experiments

20.1. Introduction to Design of Experiments
20.2. Important Concepts in DOE
20.3. Types of Effects
21. Six Sigma – Cycle Time Reduction and Kaizen Blitz
21.1. Cycle Time Reduction
21.2. Methods of Cycle Time Reduction
21.3. Kaizen and Kaizen Blitz


22. Six Sigma – Control Charts

22.1. Key Elements and Types of Control Charts
22.2. Handling Control Charts
22.3. Standard Control Charting Process
22.4. Variable Data and Control Charts
22.5. Attributes of Data and Control Charts

23. Six Sigma  – Lean Tools for Process Control

23.1. Total Productive Maintenance(TPM)
23.2. Visual Factory
23.3. Process of Applying Control Tools in Service

24. Six Sigma – Statistical Process Control and Control Plans

24.1. Introduction to Statistical Process Control (SPC)
24.2. Control Charts and Variations
24.3. Selecting Variables for SPC
24.4. Rational Subgrouping
24.5. Developing and Implementing Control Plan

Other References

Six Sigma and Organization

Six Sigma and Organizational Goal
Lean Principles
Design for Six Sigma (DFSS)


Process Management
Project Management
Management and Planning Tools
Team Dynamics and Performance


Process Analysis and Documentation
Statistics and Probability
Collecting and Summarizing Data
Probability Distributions
Measurement System Analysis
Control Chart
Process Capability and Performance


Exploratory Data Analysis
Hypothesis Testing

Improve and Control

Design of Experiments (DOE)
Statistical Process Control (SPC)
Implement and Validate
Control Plan


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