Lean Six Sigma Black Belt Certification Training Online Course

Course Content

Section 1: Course Introduction

• Lesson 0: Course Introduction
  • 0.01 Course Introduction

Section 2: Define Phase

• Lesson 01: The Basics of Six Sigma
  • 1.01 Introduction to Define Phase
  • 1.02 Learning Objectives
  • 1.03 Six Sigma
  • 1.04 Lean
  • 1.05 Sigma Shift
  • 1.06 Yield
  • 1.07 Continuous Improvement Process Evolution
  • 1.08 Six Sigma Deliverables
  • 1.09 Problem Solving Strategy
  • 1.10 VOC Campaign
  • 1.11 VOC Tools
  • 1.12 KANO Analysis
  • 1.13 Six Sigma Roles and Responsibilities
  • 1.14 Project Champion and Master Black Belt
  • 1.15 Black Belt and Yellow Belt
  • 1.16 Drivers of Six Sigma
  • 1.17 Quick Recap
  • Knowledge Check
• Lesson 02: The Fundamentals of Six Sigma
  • 2.01 Introduction
  • 2.02 Process
  • 2.03 Project Charter
  • 2.04 Critical to Quality
  • 2.05 Cost of Poor Quality
  • 2.06 Calculating CoPQ
  • 2.07 Pareto Analysis
  • 2.08 Basic Six Sigma Metrics
  • 2.09 Quick Recap
  • Knowledge Check
• Lesson 03: Lean Six Sigma Projects
  • 3.01 Introduction
  • 3.02 Selecting Lean Six Sigma Projects
  • 3.03 Project Selection Roadmap
  • 3.04 Project Charter Elements
  • 3.05 Project Charter Business Case
  • 3.06 Project Charter Problem Statement
  • 3.07 Project Charter Goal Statement
  • 3.08 Project Charter Scope
  • 3.09 Project Charter Key Milestones
  • 3.10 Project Charter Team Selection
  • 3.11 Tuckmans Stages of Formation
  • 3.12 The RACI Matrix
  • 3.13 Expected Financial Benefits
  • 3.14 Developing Project Metrics
  • 3.15 Key Performance Indicator
  • 3.16 Financial Evaluation and Benefits Capture
  • 3.17 Net Present Value
  • 3.18 Quick Recap
  • Knowledge Check
• Lesson 04: The Lean Enterprise
  • 4.01 Introduction
  • 4.02 Lean
  • 4.03 Principles of Lean
  • 4.04 Lean Methodology
  • 4.05 Lean and Six Sigma
  • 4.06 Three Ms of Lean
  • 4.07 Categories of Waste TIMWOOD
  • 4.08 Category of Waste DOWNTIME
  • 4.09 Five S
  • 4.10 Steps in Five S: Part One
  • 4.11 Steps in Five S: Part Two
  • 4.12 Quick Recap
  • 4.14 Activity
  • 4.15 Solution
  • Knowledge Check

Section 3: Measure Phase

• Lesson 01: Process Definition
  • 1.01 Introduction to Measure Phase
  • 1.02 Learning Objectives
  • 1.03 Process
  • 1.04 Cause and Effect Diagram
  • 1.05 Drawing a Fishbone diagram
  • 1.06 Root Cause
  • 1.07 Process Mapping
  • 1.08 Creating a Process Map
  • 1.09 Process Mapping Levels
  • 1.10 Four Types of Process Maps
  • 1.11 SIPOC Process Map
  • 1.12 Value Stream Maps
  • 1.13 Value Stream Maps Key Metrics
  • 1.14 X Y Diagram or Scatter Plots
  • 1.15 Failure Mode and Effects Analysis
  • 1.16 FMEA Process
  • 1.17 FMEA Template
  • 1.18 Severity Occurrence and Detection Table
  • 1.19 Risk Priority Number
  • 1.20 Quick Recap
  • Knowledge Check
• Lesson 02: Six Sigma Statistics
  • 2.01 Introduction
  • 2.02 Data
  • 2.03 Measuring Data
  • 2.04 Basic Statistics
  • 2.05 Measures of Central Tendency
  • 2.06 Measures of Dispersion
  • 2.07 Data Collection Plan
  • 2.08 Data Collection Plan Steps
  • 2.09 Develop a Measurement Plan
  • 2.10 Collect Data
  • 2.11 Sampling
  • 2.12 Sampling Methods
  • 2.13 Graphical Analysis
  • 2.14 Graphical Analysis Tools
  • 2.15 Introduction to Minitab
  • 2.16 Demo: Box Plot One Variable
  • 2.17 Demo: Box Plot with Three Variables
  • 2.18 Demo: Time Series Plot
  • 2.19 Normal Distribution
  • 2.20 Standard Normal Distribution
  • 2.21 Demo: Normality Test
  • 2.22 Quick Recap
  • Knowledge Check
• Lesson 03: Measurement System Analysis
  • 3.01 Introduction
  • 3.02 Measurement System Analysis: Overview
  • 3.03 Good and Poor Measurement System Analysis
  • 3.04 Measurement Error Categories
  • 3.05 MSA Sources of Variation
  • 3.06 Repeatability
  • 3.07 Reproducibility
  • 3.08 Accuracy and Precision
  • 3.09 Bias
  • 3.10 Stability
  • 3.11 Linearity
  • 3.12 MSA Types
  • 3.13 Gage R R Guidance in MINITAB
  • 3.14 Gage R R Ground Rules
  • 3.15 Demo: Gage R R Continuous Data
  • 3.16 Attribute Gage Study
  • 3.17 Demo: Gage R R Attribute Data
  • 3.18 Quick Recap
  • Knowledge Check
• Lesson 04: Process Capability
  • 4.01 Introduction
  • 4.02 Process Capability Overview
  • 4.03 RUMBA Analysis
  • 4.04 Process Capabilities
  • 4.05 Data Types
  • 4.06 Baseline Performance: Part One
  • 4.07 Baseline Performance: Part Two
  • 4.08 Components of Variation
  • 4.09 Process Stability
  • 4.10 Process Capability Indices
  • 4.11 Demo: Capability Analysis Continuous Data
  • 4.12 Process Capability Indices: Example
  • 4.13 Demo: Capability Analysis Continuous Data Sigma Level
  • 4.14 Z Score
  • 4.15 Process Baseline
  • 4.16 Defects Per Unit
  • 4.17 Defects Per Million Opportunities
  • 4.18 Attribute Data: Example
  • 4.19 Short-term and long-term Process Capability
  • 4.20 Quick Recap
  • 4.22 Activity
  • Knowledge Check
  • 4.23 Solution

Section 4: Analyze Phase

• Lesson 01: Classes of Distribution
  • 1.01 Introduction to Analyze Phase
  • 1.02 Learning Objectives
  • 1.03 Frequency Distribution
  • 1.04 Demo: Frequency Distribution
  • 1.05 Probability Distribution
  • 1.06 Types of Probability Distributions
  • 1.07 Types of Discrete Probability Distribution
  • 1.08 Types of Continuous Probability Distribution
  • 1.09 Quick Recap
  • Knowledge Check
• Lesson 02: Inferential Statistics
  • 2.01 Introduction
  • 2.02 Inferential Statistics
  • 2.03 Branches of Inferential Statistics
  • 2.04 Central Limit Theorem
  • 2.05 Quick Recap
  • Knowledge Check
• Lesson 03: Hypothesis Testing
  • 3.01 Introduction
  • 3.02 Basics of Hypothesis Testing
  • 3.03 Confidence Interval
  • 3.04 Significant Difference
  • 3.05 Detecting Significance
  • 3.06 Statistical Hypothesis Test
  • 3.07 Hypothesis Testing Risks
  • 3.08 Beta Risk
  • 3.09 Power of a Hypothesis Test
  • 3.10 Sample Size
  • 3.11 Hypothesis Testing Roadmap
  • 3.12 Quick Recap
  • Knowledge Check
• Lesson 04: Hypothesis Testing with Normal Data
  • 4.01 Introduction
  • 4.02 Normal Data
  • 4.03 One-Sample T-Test
  • 4.04 One-Sample T-Test - Sample Size
  • 4.05 Demo One Sample t-Test
  • 4.06 Two-Sample T-Test
  • 4.07 Two-Sample T-Test Example
  • 4.08 Demo Two : Sample t Test
  • 4.09 Demo: Bartlett Test
  • 4.10 Paired T-Test
  • 4.11 Demo: Paired T Test
  • 4.12 ANOVA
  • 4.13 Demo: ANOVA
  • 4.14 Residual Plots
  • 4.15 Quick Recap
  • Knowledge Check
• Lesson 05: Hypothesis Testing with Non Normal Data
  • 5.01 Introduction
  • 5.02 Non Parametric tests
  • 5.03 Mann Whitney Test
  • 5.04 Demo: Mann Whitney Test
  • 5.05 Kruskal Wallis Test
  • 5.06 Demo: Kruskal Wallis Test
  • 5.07 Mood' Median Test
  • 5.08 Demo: Moods Median Test
  • 5.09 Friedman Test
  • 5.10 Demo: Friedman Test
  • 5.11 One Sample Sign Test
  • 5.12 Demo: One Sample Sign Test
  • 5.13 One Sample Wilcoxon Test
  • 5.14 Demo: One Sample Wilcoxon Test
  • 5.15 One-Sample Proportion Tests
  • 5.16 Demo: one Sample Proportion Test
  • 5.17 Two Sample Proportion Tests
  • 5.18 Demo: Two Sample Proportion Test
  • 5.19 Chi Square Tests
  • 5.20 Demo: Chi-Square Test of Independence
  • 5.21 Chi-Square Goodness-of-Fit Test
  • 5.22 Demo: Chi-Square Goodness of Fit
  • 5.23 Chi-Square Cross Tabulation
  • 5.24 Demo: Chi-Square Cross Tabulation
  • 5.25 Levene F Test
  • 5.26 Quick Recap
  • 5.28 Exercise One
  • 5.29 Exercise Two
  • Knowledge Check

Section 5: Improve Phase

• Lesson 01: Simple Linear Regression
  • 1.01 Introduction to Improve Phase
  • 1.02 Learning Objectives
  • 1.03 Correlation
  • 1.04 Demo: Correlation
  • 1.05 Demo Correlation Test using Scatter Plot
  • 1.06 Correlation and Causation
  • 1.07 Predictor Measures and Results
  • 1.08 Correlation Coefficients
  • 1.09 Regression Analysis
  • 1.10 Demo: Regression
  • 1.11 Residual Analysis
  • 1.12 Quick Recap
  • Knowledge Check
• Lesson 02: Multiple Regression Analysis
  • 2.01 Introduction
  • 2.02 Multi-Vari Analysis
  • 2.03 Demo: MultiVari Analysis
  • 2.04 Non Linear Regression
  • 2.05 Multiple Linear Regression
  • 2.06 Demo: Multiple Linear Regression
  • 2.07 Variance Inflation Factor VIF
  • 2.08 Variance Inflation Factor VIF Example
  • 2.09 Confidence Interval in Multiple Linear Regression
  • 2.10 Box-Cox Transformation
  • 2.11 Demo: Box-Cox Transformation
  • 2.12 Quick Recap
  • Knowledge Check
• Lesson 03: Designed Experiments
  • 3.01 Introduction
  • 3.02 Designed Experiments
  • 3.03 Phases of DOE Process
  • 3.04 Optimization and Confirmation
  • 3.05 Types of DOE Strategies
  • 3.06 Full Factorial and Fractional Factorial Approaches
  • 3.07 Experimental Design Considerations
  • 3.08 Quick recap
  • Knowledge Check
• Lesson 04: Factorial Experiments
  • 4.01 Introduction
  • 4.02 Factorial Designs
  • 4.03 Full Factorial Experiments
  • 4.04 Demo: Full Factorial Experiments
  • 4.05 Quadratic Models
  • 4.06 Types of Response Surface Designs
  • 4.07 Balanced and Orthogonal Designs
  • 4.08 Center Points
  • 4.09 Fractional Factorial Experiment
  • 4.10 Confounding
  • 4.11 Quick Recap
  • Knowledge Check

Section 6: Control Phase

• Lesson 01: Lean Controls
  • 1.01 Introduction to Control Phase
  • 1.02 Learning Objectives
  • 1.03 Control Methods of Five S
  • 1.04 Sort
  • 1.05 Set in Order
  • 1.06 Shine Standardize and Sustain
  • 1.07 Kanban
  • 1.08 Kanban Principles
  • 1.09 Six Steps to Implement Kanban
  • 1.10 Poka Yoke or Mistake Proofing
  • 1.11 Mistake Proofing Examples
  • 1.12 Quick Recap
  • Knowledge Check
• Lesson 02: Statistical Process Control
  • 2.01 Introduction
  • 2.02 Statistical Process Control Purpose
  • 2.03 Control Charts
  • 2.04 Control Charts: Objectives
  • 2.05 Control Charts: Uses
  • 2.06 Control Charts: Types
  • 2.07 Control Charts: Steps
  • 2.08 Subgroup
  • 2.09 Consideration for Rational Subgrouping
  • 2.10 Charts for Attribute Data
  • 2.11 Tests for Special Causes
  • 2.12 Demo: I-MR Chart
  • 2.13 Demo: X-Bar R Chart
  • 2.14 Demo: XBar-S Chart
  • 2.15 Demo: P-Chart
  • 2.16 Demo: NP-Chart
  • 2.17 Demo: U-Chart
  • 2.18 Demo: C-Chart
  • 2.19 Demo: CUSUM-Chart
  • 2.20 Demo: EWMA-Chart
  • 2.21 Quick Recap
  • Knowledge Check
• Lesson 03: Six Sigma Control Plans
  • 3.01 Introduction
  • 3.02 Project Cost Benefit Analysis
  • 3.03 Return on Investment
  • 3.04 Cost Benefit Analysis
  • 3.05 Cost Benefit Analysis: Steps
  • 3.06 NPV and IRR
  • 3.07 Selecting the Right Solutions
  • 3.08 Implementation of Proposed Solutions Roadmap
  • 3.09 Control Plan
  • 3.10 Elements of a Control Plan
  • 3.11 Control Plan Training
  • 3.12 Response Plan
  • 3.13 Project Closure
  • 3.14 Quick Recap
  • Knowledge Check
  • 3.16 Activity

Do I get a IASSC certification?

The candidate can get certified from IASSC in Lean Six Sigma Black Belt by appearing for the IASSC Certified Lean Six Sigma Black Belt exam and achieving a minimum score of 70%. Upon achieving this, the candidate will receive a Certificate, suitable for framing, issued by the IASSC.

FAQs

• What is the recommended learning path after completing Lean Six Sigma Black Belt Certification?

  For your career growth, you can consider taking a Post Graduate Program in Lean Six Sigma that will make you an expert in this field.

• How do I enrol in this online training?

  You can enrol in this training on our website and make an online payment using any of the following option

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  Once payment is received, you will automatically receive a payment receipt and access information via email.