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Lean Sigma Learning Courses

Six Sigma Green Belt Training Workshop

Six Sigma Green Belt Workshop is designed specifically to have a deep root understanding of the six sigma concept and have hands on practise of all tools.

  • All trainings given by experienced trainer with wide industrial experience
  • 3 days training and theory exam on 4th day
  • Group project (5 members each) to complete during course
  • Project review taken in 15 days
  • After training completion, project to be submitted in a month
  • Project Presentation and Certification Ceremony planend together after 1 month
Who is a Six Sigma Green Belt?

The Six Sigma Green Belt operates in support or under the supervision of a Six Sigma Black Belt, analyzes and solves business problems, and is involved in process and quality improvement projects.The course enables a analytical and methodical veiw to solve any problem. Six Sigma Green Belt drives process improvement initiatives to develop robust systems for the business and deliver consistent output to customers. Green Belt training equips individuals with a logical and objective way to identify, measure, and eliminate problems / issues with process within an organization. The training also enhances the way employees approach their day-to-day work and strategically positioned to support improvement initiatives at their workplace.

Who Should do Six Sigma Green Belt ?

Engineers / Professionals / Executives who want to understand Six Sigma as a management tool for process and performance improvement at their work place

Quality and Process Managers, Engineers and Executives who need to gain knowledge of Six Sigma in process / quality improvements

Production Managers, Production Supervisors and Customer Service Managers

Consultants who want to add Six Sigma Green Belt in their service offerings and help their customers implement it

Eligibility Criteria

The Six Sigma Green Belt certification training course is beneficial for engineers, managers, quality professionals and process owners with a minimum of 2 years work experience

Examination Format
  • Exam Type: Multiple choice and scenario-based examination
  • No. of Questions : 75
  • Exam Duration : 2 ½ Hours (150 Minutes)
  • Exam Result : 52 marks required (52 out of 75 available) to pass, equivalent to 70%
Course Fees

Per Candidate - Rs. 16000+18% GST

To be paid by Cheques/NEFT in advance

Contents - Six Sigma Green Belt Training Workshop

1.0 Define Phase
2.0 Measure Phase
3.0 Analyze Phase
4.0 Improve Phase
5.0 Control Phase
  • 1.1 The Basics of Six Sigma
    • 1.1.1 Meanings of Six Sigma
    • 1.1.2 General History of Six Sigma & Continuous Improvement
    • 1.1.3 Deliverables of a Lean Six Sigma Project
    • 1.1.4 The Problem Solving Strategy Y = f(x)
    • 1.1.5 Voice of the Customer, Business and Employee
    • 1.1.6 Six Sigma Roles & Responsibilities
  • 1.2 The Fundamentals of Six Sigma
    • 1.2.1 Defining a Process
    • 1.2.2 Critical to Quality Characteristics (CTQ’s)
    • 1.2.3 Cost of Poor Quality (COPQ)
    • 1.2.4 Pareto Analysis (80:20 rule)
    • 1.2.5 Basic Six Sigma Metrics
    • a. including DPU, DPMO, FTY, RTY Cycle Time, deriving these metrics and these metrics
  • 1.3 Selecting Lean Six Sigma Projects
    • 1.3.1 Building a Business Case & Project Charter
    • 1.3.2 Developing Project Metrics
    • 1.3.3 Financial Evaluation & Benefits Capture
  • 1.4 The Lean Enterprise
    • 1.4.1 Understanding Lean
    • 1.4.2 The History of Lean
    • 1.4.3 Lean & Six Sigma
    • 1.4.4 The Seven Elements of Waste
    • a. Transportation, Inventory, Motion, Waiting, Over Production, Over Processing, Defects
    • 1.4.5 5S
    • a. Sort, Set in Order, Shine, Standardize, Self-Discipline,
  • 2.1 Process Definition
    • 2.1.1 Cause & Effect / Fishbone Diagrams
    • 2.1.2 Process Mapping, SIPOC, Value Stream Map
    • 2.1.3 X-Y Diagram
    • 2.1.4 Failure Modes & Effects Analysis (FMEA)
  • 2.2 Six Sigma Statistics
    • 2.2.1 Basic Statistics
    • 2.2.2 Descriptive Statistics
    • 2.2.3 Normal Distributions & Normality
    • 2.2.4 Graphical Analysis
  • 2.3 Measurement System Analysis
    • 2.3.1 Precision & Accuracy
    • 2.3.2 Bias, Linearity & Stability
    • 2.3.3 Gage Repeatability & Reproducibility
    • 2.3.2 Bias, Linearity & Stability
    • 2.3.4 Variable & Attribute MSA
  • 2.4 Process Capability
    • 2.4.1 Capability Analysis
    • 2.4.2 Concept of Stability
    • 2.4.3 Attribute & Discrete Capability
    • 2.4.4 Monitoring Techniques
  • 3.1 Patterns of Variation
    • 3.1.1 Multi-Vari Analysis
  • 3.2 Inferential Statistics
    • 3.2.1 Understanding Inference
    • 3.2.2 Sampling Techniques & Uses
    • 3.2.3 Central Limit Theorem
    • 3.2.2 Sampling Techniques & Uses
  • 3.3 Hypothesis Testing
    • 3.3.1 General Concepts & Goals of Hypothesis Testing
    • 3.3.2 Significance; Practical vs. Statistical
    • 3.3.3 Risk; Alpha & Beta
    • 3.3.4 Types of Hypothesis Test
  • 3.4 Hypothesis Testing with Normal Data
    • 3.4.1 1 & 2 sample t-tests
    • 3.4.2 1 sample variance
    • 3.4.3 One Way ANOVA
    • a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results.
  • 3.5 Hypothesis Testing with Non-Normal Data
    • 3.5.1 Mann-Whitney
    • 3.5.2 Kruskal-Wallis
    • 3.5.3 Mood’s Median
    • 3.5.4 Friedman
    • 3.5.4 Friedman
    • 3.5.5 1 Sample Sign
    • 3.5.6 1 Sample Wilcoxon
    • 3.5.7 One and Two-Sample Proportion
    • 3.5.8 Chi-Squared (Contingency Tables)
    • a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results.
  • 4.1 Simple Linear Regression
    • 4.1.1 Correlation
    • 4.1.2 Regression Equations
    • 4.1.3 Residuals Analysis
  • 4.2 Multiple Regression Analysis
    • 4.2.1 Non- Linear Regression
    • 4.2.2 Multiple Linear Regression
    • 4.2.3 Confidence & Prediction Intervals
    • 4.2.4 Residuals Analysis
    • 4.2.5 Data Transformation, Box Cox
  • 5.1 Lean Controls
    • 5.1.1 Control Methods for 5S
    • 5.1.2 Kanban
    • 5.1.3 Poka-Yoke (Mistake Proofing)
  • 5.2 Statistical Process Control (SPC)
    • 5.2.1 Data Collection for SPC
    • 5.2.2 I-MR Chart
    • 5.2.3 Xbar-R Chart
    • 5.2.4 U Chart
    • 5.2.5 P Chart
    • 5.2.6 NP Chart
    • 5.2.7 X-S chart
    • 5.2.8 CumSum Chart
    • 5.2.9 EWMA Chart
    • 5.2.10 Control Chart Anatomy
  • 5.3 Six Sigma Control Plans
    • 5.3 Six Sigma Control Plans
    • 5.3.2 Elements of the Control Plan
    • 5.3.3 Elements of the Response Plan