Lean Six Sigma Green Belt Training & Certification

Course Curriculum

Chapter 1: Introduction to Quality and Lean Six Sigma

Lecture 1: Introduction to Quality and it's importance

Lecture 2: Introduction to Lean and Six Sigma

Lecture 3: Lean Six Sigma Project Selection Methods

Chapter 2: Introduction to Define Phase

Lecture 1: Project charter

Lecture 2: How to identify business problems

Lecture 3: How to identify stakeholders and their position

Lecture 4: How to find out the scope of the project

Chapter 3: Measure Phase

Lecture 1: Introduction to Measure

Lecture 2: Process map & it's relevance to KPIV / KPOV

Lecture 3: Data types – Continuous and Discrete

Lecture 4: Sampling and Data Collection plan

Lecture 5: Data Collection plan

Lecture 6: Measurement System analysis

Lecture 7: Attribute Gauge R&R analysis

Lecture 8: Descriptive statistics – Measure of Central tendency

Lecture 9: Descriptive statistics in Minitab

Lecture 10: Introduction to Variation

Lecture 11: Descriptive statistics – Measures of Variation

Lecture 12: Basic data diagnosis – Time series

Lecture 13: Basic Data diagnosis & stratification- Run chart , Bar & Pie chart

Lecture 14: How to Baseline your project

Lecture 15: Process capability analysis

Lecture 16: Process capability indices

Lecture 17: Calculation of Z score from various tables

Lecture 18: Cause and Effect analysis

Lecture 19: Pareto analysis for prioritization

Lecture 20: Control Impact analysis for prioritizing X's

Lecture 21: 5 Why analysis for finding the root cause

Lecture 22: FMEA for identifying the risk & root causes

Chapter 4: Introduction to Analyze phase

Lecture 1: Recap of Define and Measure

Lecture 2: Analyze phase learning objectives and deliverables

Lecture 3: Introduction & 5 principles of Lean

Lecture 4: 8 wastes in Lean

Lecture 5: Introduction to Value Stream mapping

Lecture 6: How to draw a VSM – An Example

Lecture 7: Tools and techniques to analyze X's&Y's

Lecture 8: Tools used for correlation studies

Lecture 9: Properties of Normal distribution

Lecture 10: Introduction to Hypothesis testing

Lecture 11: Formulation of Null and Alternate hypothesis

Lecture 12: Connection between hypothesis testing and 5 why analysis

Lecture 13: Introduction to Type I and Type 2 errors

Lecture 14: Introduction to P value

Lecture 15: Hypothesis testing of means- Z test

Lecture 16: Hypothesis testing of means – 1 sample t test

Lecture 17: Hypothesis testing of means – 2 sample t test

Lecture 18: Hypothesis testing of means – F test & Anova

Lecture 19: Hypothesis testing of proportions – Chi Square test

Lecture 20: Introduction to Regression – Simple Linear regression

Lecture 21: Non parametric hypothesis testing – Man- Whitney test

Chapter 5: Introduction to Improve phase

Lecture 1: Recap of Analyze phase

Lecture 2: Learning objectives and deliverable of improve phase

Lecture 3: Brainstorming techniques ground rules for solution generation

Lecture 4: Criteria based matrix for solution priritization

Lecture 5: Pugh Matrix for solution prioritization

Lecture 6: Introduction to Poka Yoke

Lecture 7: Introduction to 5S

Lecture 8: Cost benefit analysis

Lecture 9: Implementation plan

Lecture 10: Pilot implementation

Lecture 11: Verification of pilot results

Lecture 12: Improve roadmap

Chapter 6: Introduction to Control phase

Lecture 1: Improve Recap

Lecture 2: Control phase learning objectives and deliverable

Lecture 3: Control road map and Objectives

Lecture 4: Process control and control plan

Lecture 5: Introduction to control charts

Lecture 6: Interpreting control charts

Lecture 7: Control limits and specification limits

Lecture 8: Types of control charts and selection of control charts

Lecture 9: P and NP chart

Lecture 10: U chart

Lecture 11: IMR chart

Lecture 12: X bar R chart

Lecture 13: Steps for implementing control charts and response plan

Lecture 14: Before and after display and project closure