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Six Sigma


The course on Six-Sigma will focus on detailed strategic and operational issues of process improvement and variation reduction. Six-sigma is a measure of quality that strives for near perfection. It is a disciplined, data-driven approach for eliminating defects (driving towards six standard deviations between the mean and the nearest specification limit) in any process-from manufacturing to transactional and from product to service. 
A Six-sigma defect is anything outside of customer specifications. To be tagged Six Sigma, a process must not produce more than 3.4 defects per million opportunities. 
Six-sigma employs a systematic approach of DMAIC (Define, Measure, Analyze, Improve and Control) for the process improvement. This course will provide a detailed understanding on various issues specific to each phase of DMAIC. 
The course is designed with a practical orientation and includes cases, industry examples and MINITAB software applications.  
The course is designed to satisfy the need of both industry professionals and University students.
The content is beneficial to both manufacturing and service industry.

Mechanical Engineering, MBA, Industrial Engineering




INDUSTRY SUPPORT: Manufacturing and Service Industry

3466 students have enrolled already!!


Dr. Jitesh J. Thakkar is an Associate Professor at the Department of Industrial and Systems Engineering, Indian Institute of Technology Kharagpur, India. He received Ph.D in Supply Chain Management from IIT Delhi, Masters in Technology in Industrial Engineering from IIT Delhi and Bachelors in Mechanical Engineering with Gold Medal from the oldest Government Engineering College Birla Vishvakarma Mahavidyalaya, Sardar Patel University, Gujarat.He has 18 years of teaching, research and industry experience. He has been invited as a faculty expert by various reputed institutes such as IIT Kanpur, IIT Madras, IIM Indore, NITIE Mumbai, NIT Surat, NIT Trichy, Institute of Rural Management Anand (IRMA), Ahmedabad Management Association (AMA), BCCI Kolkata, Adani Institute of Infrastructure Management (AIIM), L&T Project Management Institute, Chennai. He has guided four PhD at IIT Kharagpur in the areas of Sustainable Supply Chain Management and Lean Manufacturing. He has supervised more than 50 M.Tech and B.Tech projects at IIT Kharagpur. He has published 53 research papers in the leading International Journals in the areas of Lean & Sustainable manufacturing, Supply Chain Management, Quality Management, Small and Medium Enterprises and Performance Measurement. The publications have appeared in the leading journals – International Journal of Production Economics, Journal of Cleaner Production, Production Planning and Control, Computers & Industrial Engineering, Expert System with Applications, International Journal of Advanced Manufacturing Technology, Resources Policy, International Journal of Quality and Reliability Management, Journal of Manufacturing Technology Management and International Journal of Productivity and Performance Measurement. He is an Editorial Board member for three journals: i) International Journal of Productivity and Performance Management; ii) International Journal of Quality and Reliability Management and iii) International Journal of Lean Six Sigma. He has trained Corporate Managers in Lean Manufacturing, Process Excellence, Six Sigma, Value Engineering, Project Management, Quality Management, Supply Chain Management and Statistical Decision Making. He has also trained Teachers in Research & Publication and Teaching & Learning.


Lecture 1: Brief overview of the course
Lecture 2: Quality concepts and definition
Lecture 3: History of continuous improvement
Lecture 4: Six Sigma Principles and Focus Areas (Part 1)
Lecture 5: Six Sigma Principles and Focus Areas (Part 2)
Lecture 6: Six Sigma Applications
Lecture 7: Quality Management: Basics and Key Concepts 
Lecture 8: Fundamentals of Total Quality Management
Lecture 9: Cost of quality
Lecture 10: Voice of customer 
Lecture 11: Quality Function Deployment (QFD)
Lecture 12: Management and Planning Tools (Part 1)
Lecture 13: Management and Planning Tools (Part 2)
Week 3  : DEFINE
Lecture 14: Six Sigma Project Identification, Selection and Definition
Lecture 15: Project Charter and Monitoring
Lecture 16: Process characteristics and analysis
Lecture 17: Process Mapping: SIPOC
Week 4 : MEASURE
Lecture 18: Data Collection and Summarization (Part 1)
Lecture 19: Data Collection and Summarization (Part 2)
Lecture 20: Measurement systems: Fundamentals
Lecture 21: Measurement systems analysis: Gage R&R study
Lecture 22: Fundamentals of statistics
Lecture 23: Probability theory
Lecture 24: Process capability analysis: Key Concepts
Lecture 25: Process capability analysis: Measures and Indices 
Lecture 26: Process capability analysis: Minitab Application
Lecture 27: Non-normal process capability analysis
Lecture 28: Hypothesis testing: Fundamentals
Lecture 29: Hypothesis Testing: Single Population Test
Lecture 30: Hypothesis Testing: Two Population Test
Lecture 31: Hypothesis Testing: Two Population: Minitab Application
Lecture 32: Correlation and Regression Analysis
Lecture 33: Regression Analysis: Model Validation
Week 7  :   ANALYZE
Lecture 34: One-Way ANOVA
Lecture 35: Two-Way ANOVA
Lecture 36: Multi-vari Analysis
Lecture 37: Failure Mode Effect Analysis (FMEA)
Lecture 38: Introduction to Design of Experiment
Lecture 39: Randomized Block Design
Lecture 40: Randomized Block Design: Minitab Application
Lecture 41: Factorial Design
Lecture 42: Factorial Design: Minitab Application
Lecture 43: Fractional Factorial Design
Lecture 44: Fractional Factorial Design: Minitab Application
Lecture 45: Taguchi Method: Key Concepts
Lecture 46: Taguchi Method: Illustrative Application
Lecture 47: Seven QC Tools
Lecture 48: Statistical Process Control: Key Concepts
Lecture 49: Statistical Process Control: Control Charts for Variables
Lecture 50: Operating Characteristic (OC) Curve for Variable Control charts
Lecture 51: Statistical Process Control: Control Charts for Attributes
Lecture 52: Operating Characteristic (OC) Curve for Attribute Control charts
Lecture 53: Statistical Process Control: Minitab Application
Lecture 54: Acceptance Sampling: Key Concepts
Lecture 55: Design of Acceptance Sampling Plans for Attributes (Part 1)
Lecture 56: Design of Acceptance Sampling Plans for Attributes (Part 2)
Lecture 57: Design of Acceptance Sampling Plans for Variables 
Lecture 58: Acceptance Sampling: Minitab Application
Lecture 59: Design for Six Sigma (DFSS): DMADV, DMADOV
Lecture 60: Design for Six Sigma (DFSS): DFX
Lecture 61: Team Management
Lecture 62: Six Sigma: Case study
Lecture 63: Six Sigma: Summary of key concepts 


1. Roderick A. Munro and Govindarajan Ramu and Daniel J. Zrymiak, The certified six sigma Green Belt Handbook, ASQ Quality Press and Infotech Standards India Pvt. Ltd. 
2. T. M. Kubiak and Donald W. Benbow, The Certified Six Sigma Black Belt Handbook, Pearson Publication.
3. Forrest W. Breyfogle III, Implementing Six Sigma, John Wiley & Sons, INC. 
4. Evans, J R and W M Lindsay, An Introduction to Six Sigma and Process Improvement, CENGAGE Learning.   
5. Howard S. Gitlow and David M. Levine, Six Sigma for Green Belts and Champions, Pearson Education, Inc. 
6. Montgomery, D C. Design and Analysis of Experiments, Wiley.
7. Mitra, Amitava. Fundamentals of Quality Control and Improvement, Wiley India Pvt Ltd.
8. Montgomery, D C. Statistical Quality Control: A modern introduction, Wiley.
  • The exam is optional for a fee.
  • Date and Time of Exams: April 28 2019(Sunday)  Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
  • Registration url: Announcements will be made when the registration form is open for registrations.
  • The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published.


  • Final score will be calculated as : 25% assignment score + 75% final exam score
  • 25% assignment score is calculated as 25% of average of  Best 8 out of 12 assignments
  • E-Certificate will be given to those who register and write the exam and score greater than or equal to 40% final score. Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kharagpur.It will be e-verifiable at nptel.ac.in/noc.