Enrollment End Date
Created byJitesh J Thakkar
About the course
The course on Six Sigma will focus on detailed strategic and operational issues of process improvement and variation reduction called Six Sigma, 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.
The course will provide an exposure to well-established methods of quality assurance and management and advanced statistical methods including design of experiments.
Six Sigma is recognized as modern quality strategy to compete and sustain in the global markets. The philosophy of Six Sigma is built on two frameworks-DMAIC (define, measure, analyze, improve, control) and DMADV (define, measure, analyze, design, verify). This course will provide a detailed understanding on both the methodologies to the students.
The course intends to cover basic concepts in quality management, TQM, Cost of quality, quality engineering and Six Sigma, review of Probability and Statistics, Test of Hypothesis.
Subsequently, the course will focus on DMAIC process for process and design improvement, Acceptance Sampling, SPC (Statistical Process Control), Process Capability, Gage Reproducibility and Repeatability, Quality Function Deployment.
This will be followed by advanced quality control tools like Design of Experiments, ANOVA, EVOP, Fractional, Full and Orthogonal Experiments, Regression model building, Taguchi methods for robust design, and Six Sigma sustainability.
The course is designed with a practical orientation and includes cases and industry applications of the concepts.
For certification, visit and enroll here.
Engineering and Math courses in undergraduate (B Tech) program
Industries that will recognize this course
Manufacturing and Service Industry.
Week 1: Quality concepts and definition
Key concepts in quality management
Fundamentals of Total Quality Management (TQM)
Cost of quality and Six Sigma
Week 2: Fundamentals of statistics
Probability theory and concepts
Probability rules and events
Sampling distribution and test of hypothesis
Week 3: Quality philosophies and standards
Tools for TQM and continuous improvement
Quality Function Deployment (QFD) and Design failure mode effects analysis (DFMEA)
Quality awards, benchmarking and service quality
Week 4: Service quality and process control
Project management: Complexities and examples
Project management: Key decisions, Work breakdown structure, schedule development and cost estimation
Project planning and scheduling: Network, critical path method, PERT, crashing
Week 5: Measurement accuracy and process variations
Operating characteristic curve
Week 6: Design of sampling plan
Basics of Statistical Process Control
Statistical Process Control for services
Week 7: Control charts for variables and attributes
Process capability: Fundamentals and measures
Quality Function Deployment (QFD) and Kano Model
Week 8: Design of experiment (DOE)
Experimental analysis in product realization
Experimental setups and strategies
Week 9: Factorial experiment, ANOVA and Response surface
Benchmarking: Customer-service and Product-service performance
Benchmarks and performance measurement: Critical success factors and case study
Week 10: Supply Chain Management, TQM and quality chain
Taguchi Product Design Approach
Taguchi’s Robust Design
Week 11: DMAIC, Zero defect and Six Sigma
Six Sigma: Case study and Tools
Design for Manufacturing (DFM), Design for Assemble (DFA) and Reliability Analysis
Week 12: Failure Mode and Effect Analysis (FMEA)
Six Sigma: Strategic planning and Implementation
Six Sigma and Operational Excellence: Summary
1. Forrest W. Breyfogle III, Implementing Six Sigma, John Wiley & Sons, INC., 2nd edition.
2. Howard S. Gitlow and David M. Levine, Six Sigma for Green Belts and Champions, Pearson Education, Inc., 10th
Printing, September 2012.
3. Evans, J R and W M Lindsay, An Introduction to Six Sigma and Process Improvement, CENGAGE Learning, 3rd
4. Montgomery, D C. Design and Analysis of Experiments, 5th edition, Wiley.
5. Mitra, Amitava. Fundamentals of Quality Control and Improvement, 3rd edition, Wiley India Pvt Ltd.
To access the content, please enroll in the course.
Course Syllabus & Schedule
Tapan P Bagchi holds a B Tech in Mechanical Engineering from IIT Kanpur, India and MASc and Ph D in Industrial Engineering from the University of Toronto, Canada. He also holds a D Sc in Quality Engineering from IIT Kharagpur, India. He is a Fellow of Institution of Engineers (India) and a Registered Professional Engineer in Ontario, Canada. Author of over 100 papers and six texts on quality engineering, computer science, genetic algorithms, scheduling, ISO 9000 and database management, he has held the positions of Professor and Chair in the IIT System, Dean at SPJIMR Dubai, Director at NITIE, NDS Infoserv Mumbai, and NMIMS University’s Shirpur Campus. Prior returning to academics, Bagchi served the EXXON Corporation holding techno-managerial positions for over sixteen years in Canada, US, Singapore and Europe.