Quality Control and Improvement with MINITAB free videos and free material uploaded by Indian Institute of Technology Bombay (IIT Bombay). This session contains about Quality Control and Improvement with MINITAB Updated syllabus , Lecture notes , videos , MCQ , Privious Question papers and Toppers Training Provided Training of this course. If Material not uploaded check another subject
Week 1: Introduction to Quality, Voice of the Customer, Kano Model, Quality Function Deployment, and Data Visualization with MINITAB
Week 2: Pareto Chart, Cause and Effect Diagram, Failure Mode and Effect Analysis, and Statistical Process Control using MINITAB
Week 3: Attribute Control Charts, Process Capability Index, Process Performance, and Sigma Level using MINITAB
Week 4: Basic Statistics, Hypothesis Testing, and ANOVA Analysis using MINITAB
Week 5: One-way ANOVA , Linear Regression, and Multiple Regression using MINITAB
Week 6: Multiple Regression (Continued), Basics on Design of Experiment, and Two-way ANOVA using MINITAB
Week 7: Measurement System Analysis, and Factorial Design of Experiments using MINITAB
Week 8: Blocking in Factorial Design, Response Surface Methodology, Multiple response Optimization, Fractional Factorial Design, and Taguchi Method using MINITAB
This course will emphasize on application of different theories, tools, and techniques for Quality Control and Improvement. Most of the topics will be discussed with relevant problems and solutions in MINITAB 19 software interface. The course will emphasize two broad areas (e.g., Quality of Design and Quality of Conformance). In Quality of Design, relevant topics, such as VOC, Kano model, QFD, and FMEA, will be discussed with examples. Subsequently, the Quality of Conformance topics, such as quality control (e.g., statistical process control) and various topics related to process capability analysis, are discussed. With an objective to discuss topics related to the design of experiments, few important statistical techniques, such as hypothesis testing, ANOVA, regression analysis, and MSA are covered in this course. Finally, various Design of Experiment (DOE) techniques for factor screening and quality improvement are elaborated with examples. These techniques include factorial designs, fractional factorial design, multiple response optimization, and the Taguchi method.
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
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