Course abstract
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
Course Instructor
Prof. Jitesh J Thakkar
Prof. 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 ?¢â‚¬â€œ 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 & LearningMore info
Teaching Assistant(s)
No teaching assistant data available for this course yetCourse Duration : Jan-Apr 2021
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Syllabus
Enrollment : 18-Nov-2020 to 25-Jan-2021
Exam registration : 15-Jan-2021 to 12-Mar-2021
Exam Date : 25-Apr-2021
Enrolled
4432
Registered
240
Certificate Eligible
91
Certified Category Count
Gold
0
Silver
7
Elite
30
Successfully completed
54
Participation
41
Success
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Category : Successfully Completed
Elite
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Category : Elite
Silver
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Category : Silver
Gold
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Category : Gold
Legend
AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75 AND FINAL SCORE >=40BASED ON THE FINAL SCORE, Certificate criteria will be as below:
>=90 - Elite + Gold
75-89 -Elite + Silver
>=60 - Elite
40-59 - Successfully Completed
Final Score Calculation Logic
- Assignment Score = Average of best 8 out of 12 assignments.
- Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
We have taken best assignment score from both Jan 2020 and Jan2021 course
Enrollment Statistics
Total Enrollment: 4432
Registration Statistics
Total Registration : 240
Assignment Statistics
Exam score
Final score