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Certified Lean Six Sigma Green Belt with IASSC Exam Voucher

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What you'll learn on the course

Six Sigma

Course programme

Course Preview
  • Lean Six Sigma Green Belt
    • Lesson 00 - Course Overview
      • 0.1 Course Overview
      • 0.2 Objectives
      • 0.3 About Simplilearn's LSSGB Course
      • 0.4 Course Overview
      • 0.5 Target Audience and Course Prerequisites
      • 0.6 Value Of LSSGB For Professionals
      • 0.7 Value Of LSSGB For Organization
      • 0.8 Lessons Covered
      • 0.9 Exam Pattern
      • 0.10 About Simplilearn's LSSGB Exam
      • 0.11 Lean Six Sigma Green Belt Certification
      • 0.12 Sources Of Information
      • 0.13 Thank You
    • Lesson 01 - Overview of Lean Six Sigma
      • 1.1 Overview of Lean Six Sigma
      • 1.2 Objectives
      • 1.3 Topic 1 - Six Sigma
      • 1.4 Introduction to Six Sigma
      • 1.5 Process
      • 1.6 Process of Six Sigma
      • 1.7 List of DMAIC Tools
      • 1.8 How does Six Sigma Work
      • 1.9 Six Sigma Terms
      • 1.10 Sigma Level Chart
      • 1.11 Benefits of Six Sigma
      • 1.12 Six Sigma and Quality
      • 1.13 History of Six Sigma
      • 1.14 Six Sigma Team
      • 1.15 Topic 2 - Lean Principles
      • 1.16 Overview of Lean
      • 1.17 History of Lean
      • 1.18 Lean Six Sigma
      • 1.19 Lean vs. Six Sigma
      • 1.20 Lean Concepts
      • 1.21 Lean Concepts - Process Issues
      • 1.22 Seven Types of Waste
      • 1.23 Other Lean Wastes
      • 1.24 Identifying the Waste Type Exercise
      • 1.25 Lean Process
      • 1.26 Lean Process - Identify Value
      • 1.27 Lean Process Value Stream Mapping
      • 1.28 Lean Process Flow Pull and Perfection
      • 1.29 Pull vs. Push
      • 1.30 Theory of Constraints
      • 1.31 Theory of Constraints - Example
      • 1.32 Theory of Constraints - Example
      • 1.33 Topic 3 - Design for Six Sigma
      • 1.34 Design for Six Sigma
      • 1.35 DFSS Tools - Quality Function Deployment
      • 1.36 DFSS Tools - Failure Modes and Effects Analysis
      • 1.37 PFMEA and DFMEA
      • 1.38 FMEA Risk Priority Number
      • 1.39 FMEA Table
      • 1.40 RPN and Scale Criteria - Severity
      • 1.41 RPN and Scale Criteria - Occurrence
      • 1.42 RPN and Scale Criteria - Detection
      • 1.43 Example of FMEA and RPN
      • 1.44 Quiz
      • 1.45 Summary
      • 1.46 Thank You
    • 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
      • 2.56 Interrelationship 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 Mood’s 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
      • 5.1 Improve
      • 5.2 Objectives
      • 5.3 Topic 1 Design of Experiments
      • 5.4 Design of Experiments An Introduction
      • 5.5 DOE Plastic Molding Example
      • 5.6 Components of DOE in the Molding Example
      • 5.7 Full Factorial Experiment An Example
      • 5.8 Full Factorial Experiment An Example
      • 5.9 Full Factorial Experiment An Example
      • 5.10 Full Factorial Experiment An Example
      • 5.11 Design of Experiments Runs
      • 5.12 Topic 2 Root Cause Analysis
      • 5.13 Residuals Analysis
      • 5.14 Residuals Analysis (contd.)
      • 5.15 Data Transformation using Box Cox
      • 5.16 Data Transformation using Box Cox (contd.)
      • 5.17 Process Input and Output Variables
      • 5.18 Cause and Effect Matrix Steps to Update
      • 5.19 Cause and Effect Diagram
      • 5.20 Cause and Effect Diagram Example
      • 5.21 The 5 Why Technique
      • 5.22 The 5 Why Process
      • 5.23 5 Why Example
      • 5.24 Topic 3 Lean Tools
      • 5.25 Lean Techniques
      • 5.26 Cycle Time Reduction
      • 5.27 Cycle Time Reduction Example
      • 5.28 Kaizen and Kaizen Blitz Introduction
      • 5.29 Kaizen and Kaizen Blitz Differences
      • 5.30 Kaizen and Kaizen Blitz Examples
      • 5.31 Quiz
      • 5.32 Summary
      • 5.33 Thank you
    • Lesson 06 - Control
      • 6.1 Control
      • 6.2 Objectives
      • 6.3 Topic 1 Statistical Process Control
      • 6.4 Introduction to Statistical Process Control
      • 6.5 Common Cause Variation and Special Cause Variation
      • 6.6 Common Cause Variation vs Special Cause Variation
      • 6.7 Rational Subgrouping
      • 6.8 Data Collection for SPC
      • 6.9 Data Collection for SPC Techniques
      • 6.10 Control Chart Anatomy
      • 6.11 Control Chart Anatomy Sample
      • 6.12 Control Charts and Analysis
      • 6.13 Setting the Control Limits
      • 6.14 Common Rules for Control Chart Analysis
      • 6.15 Choosing an Appropriate Control Chart Continuous Data
      • 6.16 Choosing an Appropriate Control Chart Discrete Data
      • 6.17 X bar Chart Principles
      • 6.18 Defining UCL and LCL in X bar and R Chart
      • 6.19 Defining UCL and LCL in X bar and s Chart
      • 6.20 X̄ and R and Subgroup Data Example
      • 6.21 X bar and s and Subgroup Data Example
      • 6.22 ImR Chart Principles
      • 6.23 ImR and Individual Data Example
      • 6.24 ImR Chart IT ITES Example
      • 6.25 Control Charts for Attribute Data
      • 6.26 np Chart Principles
      • 6.27 np Charts and Uniform Subgroup Size Example
      • 6.28 p Chart Principles
      • 6.29 p Charts and Varying Subgroup Size Example
      • 6.30 c Chart Principles
      • 6.31 c Chart Example
      • 6.32 u Chart Principles
      • 6.33 u Chart Example
      • 6.34 Topic 2 Control Plan
      • 6.35 Control Plan and its Uses
      • 6.36 Control Plan Strategy
      • 6.37 Elements of the Control Plan
      • 6.38 Elements of the Response Plan
      • 6.39 Corrective and Preventive Actions
      • 6.40 Cost Benefit Analysis
      • 6.41 What to Control
      • 6.42 Identifying KPIVs
      • 6.43 Control Plan Tools
      • 6.44 Developing a Control Plan
      • 6.45 Developing a Control Plan (contd.)
      • 6.46 Choosing the Right Level of Control
      • 6.47 Transactional Control Plan Example
      • 6.48 Transactional Control Plan Sections
      • 6.49 Manufacturing Control Plan Sample
      • 6.50 IT ITES Control Plan Sample
      • 6.51 CuSum Chart
      • 6.52 CuSum Chart Sample
      • 6.53 EWMA Chart
      • 6.54 EWMA Chart Design Parameters
      • 6.55 EWMA Chart Sample
      • 6.56 EWMA Chart Highlights
      • 6.57 Topic 3 Lean Tools for Process Control
      • 6.58 Visual Controls
      • 6.59 Control Methods for 5S
      • 6.60 Quiz
      • 6.61 Summary
      • 6.62 Thank You

Additional information

  • What this course is about?

    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.

    Simplilearn’s 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.

  • What is this certification about?

    The Lean Six Sigma Green Belt Certification from the International Association for Six Sigma Certification (IASSC), is a valuable certification for every aspiring professional who wants to make his/her career in the quality sector. 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.

    IASSC’s Lean Six Sigma Green Belt Certification demonstrates a professional’s thorough understanding of all aspects of D-M-A-I-C and efficiency to execute and interpret Six Sigma tools and use Lean principles. The IASSC Certified Lean Six Sigma Green Belt (ICGB) is capable of leading and supporting improvement projects from start-to-finish.