# Six 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

1.2. 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

2.2. 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

3.2. 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

# DEFINE PHASE

## 4. Six Sigma – Project Identification

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

5.2. 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

6.2. 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

7.2. 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

8.2. 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

9.2. 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

# MEASURE PHASE

## 10. Process Analysis and Documentation

10.2. Process Mapping

10.3. Process of Documentation

## 11. Probability and Statistical Distribution

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

12.2. Data Sampling Methods

12.3. Six Sigma Data Collection Methods

12.4. Strategies of Data Collection

## 13. Statistical and Graphical Presentation

13.2. Measures of Central Tendency and Dispersion

13.3. Frequency Distribution

13.4. Graphical Methods

## 14. 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

15.2. Process Capability Studies

15.3. Indices of Process Capability and Performance

15.4. Long-term Capability and Sigma Level

## ANALYZE PHASE

## 16. Six Sigma – Hypothesis Tests for Variances and Proportions

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

17.2. 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

18.2. Variation in Six Sigma

18.3. Correlation and Correlation Coefficient

18.4. Causation and Statistical Significance

18.5. Linear Regression

## IMPROVE PHASE

## 19. Six Sigma – Root Cause Analysis and Waste Elimination

19.2. Waste Reduction

19.3. Tools of Waste Reduction

## 20. 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

## CONTROL PHASE

## 22. Six Sigma – 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

23.2. Visual Factory

23.3. Process of Applying Control Tools in Service

## 24. Six Sigma – Statistical Process Control and Control Plans

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)

## Define

Process Management

Project Management

Management and Planning Tools

Team Dynamics and Performance

## Measure

Process Analysis and Documentation

Statistics and Probability

Collecting and Summarizing Data

Probability Distributions

Measurement System Analysis

Control Chart

Process Capability and Performance

## Analyze

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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