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.
Engineering and Math courses in undergraduate (B Tech) program
Industries that will recognize this course
Manufacturing and Service Industry.
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.
Jitesh Thakkar is an Associate Professor at the Department of Industrial and Systems Engineering, Indian Institute of Technology (IIT) 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 published research 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 – Journal of Cleaner Production, Production Planning and Control, Computers & Industrial Engineering, International Journal of Advanced Manufacturing Technology, Journal of Manufacturing Technology Management, and International Journal of Productivity and Performance Measurement.
He is an Editorial Board member and Guest Editor for International Journal of Lean Six Sigma, Emerald. He is a Guest Editor for Electronics Commerce Research and Applications, Elsevier. He extends his services as a reviewer to the reputed international journals like International Journal of Production Economics, International Journal of Production Research, Production Planning and Control, and International Journal of Productivity and Performance Management.
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.
The Six Sigma course was developed by Prof. Tapan P Bagchi and has been repurposed for MOOC by Prof. Jitesh J Thakkar.
Week 1: Lecture 1: Quality concepts and definition
Lecture 2: Key concepts in quality management
Lecture 3: Fundamentals of Total Quality Management (TQM)
Week 2: Lecture 4: Cost of quality and Six Sigma
Lecture 5: Fundamentals of statistics
Lecture 6: Probability theory and concepts
Week 3: Lecture 7: Probability rules and events
Lecture 8: Sampling distribution and test of hypothesis
Week 4: Lecture 9: Quality philosophies and standards
Lecture 10: Tools for TQM and continuous improvement
Lecture 11: Quality Function Deployment (QFD) and Design failure mode effects analysis (DFMEA)
Week 5: Lecture 12: Quality awards, benchmarking and service quality
Lecture 13: Service quality and process control
Week 6: Lecture 14: Project management: Complexities and examples
Lecture 15: Project management: Key decisions, Work breakdown structure, schedule development and cost estimation
Lecture 16: Project planning and scheduling: Network, critical path method, PERT, crashing
Week 7: Lecture 17: Measurement accuracy and process variations
Lecture 18: Acceptance sampling
Lecture 19: Operating characteristic curve
Week 8: Lecture 20: Design of sampling plan
Lecture 21: Basics of Statistical Process Control
Lecture 22: Statistical Process Control for services
Week 9: Lecture 23: Control charts for variables and attributes
Lecture 24: Process capability: Fundamentals and measures
Lecture 25: Quality Function Deployment (QFD) and Kano Model
Week 10: Lecture 26: Design of experiment (DOE)
Lecture 27: Experimental analysis in product realization
Lecture 28: Experimental setups and strategies
Week 11: Lecture 29: Factorial experiment, ANOVA and Response surface
Lecture 30: Benchmarking: Customer-service and Product-service performance
Lecture 31: Benchmarks and performance measurement: Critical success factors and case study
Week 12: Lecture 32: Supply Chain Management, TQM and quality chain
Lecture 33: Taguchi Product Design Approach
Lecture 34: Taguchi’s Robust Design
Week 13: Lecture 35: DMAIC, Zero defect and Six Sigma
Lecture 36: Six Sigma: Case study and Tools
Lecture 37: Design for Manufacturing (DFM), Design for Assemble (DFA) and Reliability Analysis
• The exam is optional for a fee. Exams will be on 23 April 2017.
• Time: Shift 1: 9am-12 noons; Shift 2: 2pm-5pm
• Any one shift can be chosen to write the exam for a course.
• 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 12 weeks course: 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