This course will provide a holistic view (with simultaneous emphasis on theory and illustrations/examples/cases) on various topics of Quality Control and Improvement using MINITAB software interface. The first half of the course will discuss and illustrate (with examples) on varied concepts of Quality Control (e.g. QC tools, statistical process control, process capability, sigma level, hypothesis testing, ANOVA, and MSA). Every concept will be linked with examples/cases. Analysis and solution for each example/case will be demonstrated using MINITAB software.The second part of course will discuss on process modelling (e.g. Multiple Regression) and Design of Experiments (DOE) for quality improvement. Varied business and industrial problems/scenarios/cases will be discussed, analyzed, and solved using MINITAB software. The course will also discuss multiple regression modelling (e.g. model development and model adequacy) approach with examples before elaborating applications of design of experiment techniques. The various design of experiment topics to be covered with examples/illustration in MINITAB are factorial designs, fractional factorial design, Taguchi method, and multiple response optimization. INTENDED AUDIENCE :Operations Management, Mechanical Engineering, Production Engineering, Metallurgical Engineering, Industrial Engineering, Chemical Engineering, Chemistry, Pharmaceutical Sciences PREREQUISITES : Basic Course on Statistics and Quality Management (Web or Video)INDUSTRIES SUPPORT :Tata Motors Limited; Mahindra & Mahindra Limited; Maruti Suzuki Limited; Tata Steel Limited; Sundaram Clayton Limited; Ceat Limited; Glenmark Pharmaceuticals Limited; GE Global Research; General Motors Limited; Ford Motors Limited, Cummins Limited
Week 1:Introduction to Quality Control and Improvement Quality Control Tools with Examples in MINITAB Week 2:Statistical Process Control Techniques with Examples in MINITAB Process Capability, and Sigma Level with Examples in MINITAB Week 3:Hypothesis Testing and ANOVA Analysis in MINITAB Measurement System Analysis (MSA) using MINITAB Week 4:: Multiple Regression for Process Modelling using MINITAB Week 5:Introduction to Design and Analysis of Experiments for Quality Improvement with MINITAB Week 6:Factorial Design (2k) with Examples in MINITABWeek 7:Response Surface Methodology (RSM) and CCD Design with Examples in MINITAB Multiple Response Optimization using MINITAB Week 8:Fractional Factorial Design with Examples in MINITAB Taguchi’s Experimental Design and Analysis using MINITAB
TEACHING ASSISTANT Abhinav Kumar Sharma
Abhinav Kumar Sharma completed his Bachelor’s in Mechanical Engineering (with Honours) from HPU Shimla, Himachal Pradesh, and Master’s degree in Mechanical Systems Design from the Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram, Tamil Nadu. Presently he is a research scholar at Shailesh J. Mehta School of Management, IIT Bombay, and his primary area of research interest is quality engineering and management. Arijit Maji
Arijit Maji completed B.Tech from National Power Training Institute, Durgapur and M.Tech in Quality, Reliability and Operations Research from Indian Statistical Institute, Kolkata. Presently he is a research scholar at Shailesh J. Mehta School of Management, IIT Bombay, and his primary area of research interest is statistical multivariate quality control and optimization.