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Learn how to integrate principles of business, statistics and engineering to achieve
Master the use of Six Sigma to quantify the critical quality issues in your company.
Once the issues have been quantified, statistics can be applied to provide
probabilities of success and failure.
Six Sigma methods increase productivity and enhance quality.
As a Six Sigma green belt, you will be equipped to support and champion Six Sigma
implementation in your organization.
Who should attend?
Managers, supervisors, and employees and who want to apply quality control
process, efficiency, and methodologies learned in class to a project within their own
Quality system managers
Production and materials managers
Finance and commercial managers
High potential employees
Consultants who want to incorporate Six Sigma Green Belt in their service offerings
and help their clients implement it.
What will I learn?
Upon completion of this course, participant should be able to learn:
History of Six Sigma
Basic statistics and displays of data
Process mapping and measurement techniques
Six sigma tools
DMAIC process improvement roadmap
How to establish customer requirements
How to measure and quantify process performance
Statistical and other analytical methods for identifying and understanding sources of
What is Six Sigma?
History of Six Sigma?
What is Sigma and why is it Six Sigma?
How does Six Sigma DMAIC process works?
Six sigma Roles and responsibilities.
Six sigma Vs. Business Process Re-engineering.
What is Statistics?
What is Descriptive Statistics?
What is Inferential Statistics?
Accuracy v/s Precision.
Capturing Voice of customer
CTQ drill down tree.
P-Map and Process flow diagram.
Cause and Effect matrix
7 types of wastes.
Value added and non-value added activities.
Concept of Value stream mapping.
Identifying project output.
Types of data.
Data collection strategy - Sampling.
Sample size calculation.
Measurement system analysis - Continuous data and discrete data.
Introduction to Normal Distribution.
Process Sigma calculation.
Calculation of Z value.
Data analysis (Graphical representation).
Ishikawa Diagram, Pareto diagram, Histogram
Statistical process control.
Types of control charts.
What is Hypothesis?
Hypothesis Testing Errors.
Hypothesis testing (T test and Annova), Regression analysis, Chi-square analysis.
Examples of hypothesis testing.
Introduction to DOE.
Pilot solution implementation.
Mistake proofing (Poka Yoke).
Note - Participants should bring their own Laptop for learning Minitab
Mock test and examination will be conducted on last day.
The training includes
4 day classroom training at a 3 star hotel
Interactive demo sessions on statistical tools using Minitab software
Comprehensive course material
Group Exercises based on scenarios
Review and preliminary discussion on real projects undertaken by participants
Assistance in selecting an improvement project
Certification from IITD
IITD Sr. Expert Faculty: DME, B.E. Production
22 years of experience in world class manufacturing industry
Six sigma certified Master Black belt.
Conducted Six sigma trainings in Europe, Russia, USA.
ISO/TS-16949 internal auditor.
Medium: English, Marathi