Certified Lean Six Sigma Green Belt

Certified Lean Six Sigma Green Belt Course :

Online Self Learning

30 Days Access Duration

Online Self Learning

180 Days Access Duration

Certified Lean Six Sigma Green Belt :

Lean Six Sigma is an improvement methodology that combines the best of Lean concepts and Six Sigma tools. Lean Six Sigma emphasizes taking advantage of the value generation focus offered by the lean method, while maintaining the statistical rigors of the Six Sigma methodology.

Our training in Lean Six Sigma Green Belt (LSSGB) is an ideal course package for every aspiring professional who wants to make his/her career in the quality sector. The Lean Six Sigma Green Belt professional will be capable of developing and assisting project teams and leading Lean Six Sigma projects from start-to-finish.

The LSSGB training focuses on all the aspects of DMAIC. Further, it helps you execute and interpret Six Sigma tools and use Lean principles. The LSSGB training also focuses on the statistical tools and Lean tools.

Key Features :

25 Hrs of High Quality e-Learning content
106 real world examples from various industries
4 Lean Six Sigma Green Belt Simulation Exams
Collection of 47 six sigma tools for hands-on practice
Lean Six Sigma Green Belt Exam fees included

72 Chapter-end Quizzes
30 PDUs Offered
2 Glossaries for difficult terms & acronyms
3 case studies
IASSC Exam Fee NOT Included

Course Structure :

Lesson 00 - Course Overview

Lesson 01 - Overview of Lean Six Sigma

Lesson 02 - Define

2.1 Define
2.2 Objectives
2.3 Topic 1 – Project Identification
2.4 Project Selection
2.5 Process Elements
2.6 SIP – Output Interaction
2.7 Owners and Stakeholders
2.8 Identify Customer
2.9 Internal Customers
2.10 External Customers
2.11 Building a Business Case
2.12 Building a Business Case – Details
2.13 Financial Evaluation and Benefits Capture
2.14 Financial Evaluation and Benefits Capture – Sample
2.15 Positive Effects of Project on Customers
2.16 Topic 2 – Voice of the Customer
2.17 Collect Customer Data
2.18 Questionnaire
2.19 Advantages and Disadvantages of Questionnaire
2.20 Telephone Survey vs. Web Survey
2.21 Focus Group
2.22 Advantages and Disadvantages of Focus Group
2.23 Interview
2.24 Advantages and Disadvantages of Interview
2.25 Importance and Urgency of Various Inputs
2.26 Customer Complaints
2.27 Product Complaint vs. Expedited Service Request
2.28 Importance and Urgency of Various Inputs
2.29 Key Elements of Data Collection Tools
2.30 Review of Collected Data
2.31 Voice of Customer
2.32 Importance of Translating Customer Requirements
2.33 Critical to Quality
2.34 Quality Function Deployment
2.35 Phases of QFD
2.36 Structure of QFD
2.37 Post – HOQ Matrix
2.38 Topic 3 – Project Management Basics
2.39 Problem Statement
2.40 Project Charter
2.41 Project Charter Sections
2.42 Project Plan
2.43 Deliverables of a Lean Six Sigma Project
2.44 Deliverables of a Lean Six Sigma (contd.)
2.45 Pareto Chart
2.46 Pareto Charts – Example
2.47 Risk
2.48 Risk Analysis and Management
2.49 Elements of Risk Analysis
2.50 Benefits of Risk Analysis
2.51 Risk Assessment Matrix
2.52 Six Sigma Team and their Responsibilities
2.53 Project Closure
2.54 Goals of Project Closure Report
2.55 Affinity Diagram
2.57 Tree Diagram
2.58 Topic 4 – Management and Planning Tools
2.59 Matrix Diagram
2.60 Types of Matrices
2.61 Defect per Unit
2.62 Throughput Yield
2.63 Rolled Throughput Yield
2.64 FPY and RTY Example
2.65 Topic 5 – Business Results for Projects
2.66 Defect per Million Opportunities
2.67 Cost of Quality
2.68 Quiz
2.69 Summary
2.70 Summary
2.71 Thank You

Lesson 03 - Measure

3.1 Measure
3.2 Objectives
3.3 Topic 1 – Process Definition
3.4 Introduction to Measure Phase
3.5 Process Mapping
3.6 X-Y Diagram
3.7 X-Y Diagram Template
3.8 Topic 2 – Descriptive and Inferential Statistics
3.9 Types of Statistics
3.10 Analytical Statistics
3.11 Central Limit Theorem
3.12 Central Limit Theorem – Graph
3.13 Central Limit Theorem – Conclusions
3.14 Topic 3 – Collecting and Summarizing Data
3.15 Types of Data
3.16 Selecting Data Type
3.17 Simple Random Sampling vs. Stratified Sampling
3.18 Descriptive Statistics Measures of Central Tendency
3.19 Mean Median and Mode – Example
3.20 Mean Median and Mode – Outliers
3.21 Descriptive – Statistics Measures of Dispersion
3.22 Measures of Dispersion – Range
3.23 Measures of Dispersion – Variance
3.24 Measures of Dispersion Standard Deviation
3.25 Descriptive Statistics – Frequency Distribution
3.26 Cumulative Frequency Distribution
3.27 Graphical Methods – Stem and Leaf Plots
3.28 Graphical Methods – Box and Whisker Plots
3.29 Graphical Methods – Scatter Diagrams
3.30 Scatter Diagrams – Types of Correlation
3.31 Graphical Methods – Histogram
3.32 Graphical Methods – Normal Probability Plots
3.33 Topic 4 – Measurement System Analysis
3.34 Measurement System Analysis
3.35 Measurement System Analysis – Objectives
3.36 Precision and Accuracy
3.37 Precision vs. Accuracy
3.38 Combinations of Accuracy and Precision
3.39 Bias Linearity and Stability
3.40 Comparison of Variable and Attribute R and R
3.41 Gage Repeatability and Reproducibility
3.42 Components of GRR Study
3.43 Guidelines for GRR Studies
3.44 Other GRR Concepts
3.45 Measurement Resolution
3.46 Repeatability and Reproducibility
3.47 Data Collection in GRR
3.48 ANOVA Method of Analyzing GRR Studies
3.49 Interpretation of Measurement System Analysis
3.50 Gage RR Template
3.51 Gage RR Results Summary
3.52 Gage RR Interpretation
3.53 Topic 5 – Process Capability
3.54 Process Capability Analysis
3.55 Natural Process Limits vs. Specification Limits
3.56 Process Capability
3.57 Process Capability Indices
3.58 Process Capability Indices Example
3.59 Capability Analysis – Cpk and Cp Interpretations
3.60 Process Capability Studies
3.61 Objectives of Process Capability Studies
3.62 Process Capability Studies – Identifying Characteristics
3.63 Process Capability for Attribute or Discrete Data
3.64 Process Stability Studies
3.65 Process Stability Studies Causes of Variation
3.66 Process Stability Studies – Run Charts in Minitab
3.67 Verifying Process Stability and Normality
3.68 Monitoring Techniques
3.69 Quiz
3.70 Summary
3.71 Summary (contd.)
3.72 Thank You

Lesson 04 - Analyze

4.1 Analyze
4.2 Objectives
4.3 Topic 1 – Patterns of variation
4.4 Classes of Distributions
4.5 Types of Distribution
4.6 Discrete Probability Distribution
4.7 Binomial Distribution
4.8 Binomial Distribution (contd.)
4.9 Calculating Binomial Distribution Example
4.10 Poisson Distribution
4.11 Poisson Distribution – Formula
4.12 Calculating Poisson Distribution Example
4.13 Continuous Probability Distribution
4.14 Normal Distribution
4.15 Normal Distribution (contd.)
4.16 Calculating Normal Distribution Example
4.17 Z-Table Usage
4.18 Z-Table
4.19 Using Z-Table – Example
4.20 Chi Square Distribution
4.21 t-Distribution
4.22 F-Distribution
4.23 Topic 2 – Exploratory Data Analysis
4.24 Multi-Vari Studies
4.25 Create Multi-Vari Chart
4.26 Create Multi-Vari Chart (contd.)
4.27 Simple Linear Correlation
4.28 Correlation Levels
4.29 Regression
4.30 Key Concepts of Regression
4.31 Simple Linear Regression (SLR)
4.32 Least Squares Method in SLR
4.33 SLR – Example
4.34 SLR – Example
4.35 SLR – Example
4.36 Multiple Linear Regression
4.37 Key Concepts of Multiple Linear Regression
4.38 Difference between Correlation and Causation
4.39 Topic 3 – Hypothesis Testing
4.40 Statistical and Practical Significance of Hypothesis Test
4.41 Null Hypothesis vs. Alternate Hypothesis
4.42 Type I and Type II Error
4.43 Important Points to remember about Type I and Type II Errors
4.44 Power of Test
4.45 Determinants of Sample Size – Continuous Data
4.46 Standard Sample Size Formula Continuous Data
4.47 Standard Sample Size Formula Discrete Data
4.48 Hypothesis Testing Roadmap
4.49 Hypothesis Test for Means (Theoretical) – Example
4.50 Hypothesis Test for Variance Example
4.51 Hypothesis Test for Proportions Example
4.52 Comparison of Means of Two Processes
4.53 Paired Comparison Hypothesis Test for Means (Theoretical)
4.54 Paired Comparison Hypothesis Test for Variance F-Test Example
4.55 Hypothesis Test for Equality of Variance – F-Test Example
4.56 Hypothesis Tests F-Test for Independent Groups
4.57 F-Test Assumptions
4.58 F-Test Interpretations
4.59 Hypothesis Tests – t-Test for Independent Groups
4.60 2-Sample t-Test
4.61 Assumptions of 2-Sample Independent t-Test
4.62 2-Tailed vs. 1-Tailed Probability
4.63 2-Sample Independent t-Test – Results and Interpretations
4.64 Paired t-Test
4.65 Sample Variance
4.66 Sample Variance – Example
4.67 ANOVA – Comparison of More Than Two Means
4.68 ANOVA Example
4.69 ANOVA Example
4.70 ANOVA Example
4.71 ANOVA Example
4.72 ANOVA Example
4.73 Chi-Square Distribution
4.74 Chi-Square Test – An Example
4.75 Chi-Square Test – An Example
4.76 Chi-Square Test – An Example
4.77 Topic 4 – Hypothesis Testing with Non Normal Data
4.78 Mann-Whitney Test
4.79 Mann-Whitney Test – Example
4.80 Kruskal-Wallis Test
4.81 Moodís Median Test
4.82 Friedman Test
4.83 1 Sample Sign Test
4.84 1 Sample Wilcoxon Test
4.85 Characteristics of 1 Sample Wilcoxon Test
4.86 Quiz
4.87 Summary
4.88 Summary (contd.)
4.89 Thank you

Lesson 05 - Improve

Lesson 06 - Control

Learning Objectives :

“The Lean Six Sigma Green Belt training we offer will introduce you to the concept of Lean Six Sigma. The course extensively focuses on both Lean and Six Sigma methodologies. It provides greater emphasis on all the aspects of DMAIC.

At the end of training in Lean Six Sigma Green Belt, participants will be able to:

Discuss the basics of Lean Six Sigma
Describe how to identify an improvement project in the Define phase
Explain how to measure process and product in the Measure phase
Perform data analysis and hypothesis testing in the Analyze phase
Identify the possible improvement actions for the performance of variations in the Improve phase
Define efficient operating levels for inputs and outputs in the Control phase
Use DFSS Tools such as Quality Function Deployment (QFD), Failure Mode and Effects Analysis (FMEA), and Risk Priority Number (RPN)
Perform hypothesis testing with normal and non-normal data
Describe Design of Experiments (DOE)
Use Lean tools for process control

Target Audience :

This Lean Six Sigma Green Belt training is suitable for:

Quality System Managers, Supervisors, Operations Managers, Finance and Commercial Managers, and professionals who want to apply the methodologies and quality control process within an organization.

Certified Lean Six Sigma Green Belt

Certified Lean Six Sigma Green Belt Course :

Online Self Learning

30 Days Access Duration

Online Self Learning

180 Days Access Duration

Certified Lean Six Sigma Green Belt :

Key Features :

25 Hrs of High Quality e-Learning content

106 real world examples from various industries

4 Lean Six Sigma Green Belt Simulation Exams

Collection of 47 six sigma tools for hands-on practice

Lean Six Sigma Green Belt Exam fees included

72 Chapter-end Quizzes

30 PDUs Offered

2 Glossaries for difficult terms & acronyms

3 case studies

IASSC Exam Fee NOT Included

Course Structure :

Learning Objectives :

Target Audience :

Exam Format :

FAQs :

Course Duration

30 Days

25 Hrs of High Quality e-Learning content

4 LSSGB Simulation Exams

30 PDUs offered

30 Access Days

Course Duration

180 Days

25 Hrs of High Quality e-Learning content

4 LSSGB Simulation Exams

30 PDUs offered

180 Access Days

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