Learn · Quality Control and Improvement with MINITAB
Lecture 28 of 40Week 6
Lecture 28: Design of Experiment, One-factor-at-a-time experiment
Prof. Indrajit Mukherjee · IIT Bombay
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- Quality Control and Improvement with MINITAB, IIT Bombay (at NPTEL)
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All the lectures
- Lecture 01: Introduction of Quality
- Lecture 02: Voice of the Customer and Kano Model
- Lecture 03: Quality Function Deployment
- Lecture 04: Critical to Quality Characteristics
- Lecture 05: Data Visualization for Quality Control and Improvement
- Lecture 06: Importance of Pareto Chart and Cause and Effect Diagram
- Lecture 07: Design Failure Mode and Effect Analysis
- Lecture 08: Introduction to Statistical Process Control
- Lecture 09: X-bar and R Chart
- Lecture 10: X-bar and S Chart
- Lecture 11: Individual Moving Range Chart and Attribute Chart
- Lecture 12: Attribute Control Charts and Process Capability
- Lecture 13: Process Capability Index
- Lecture 14: Process Performance and Sigma Level
- Lecture 15: Process Capability for Attribute data
- Lecture 16: Basic Statistics & Confidence Interval
- Lecture 17: Hypothesis Testing
- Lecture 18: One-sample t Test
- Lecture 19: Two-sample t Test
- Lecture 20: Paired t Test and ANOVA
- Lecture 21: One-way ANOVA
- Lecture 22: One-way ANOVA (Continued)
- Lecture 23: ANCOVA and Nonparametric Test
- Lecture 24: Linear Regression
- Lecture 25: Linear Regression(Continued) and Multiple Regression
- Lecture 26: Best Subset Regression , Multicollinearity
- Lecture 27: Multicollinearity, Best Subset Regression, Multiple Regression, Basics on Design of Experiment
- Lecture 28: Design of Experiment, One-factor-at-a-time experiment
- Lecture 29: Two-factor asymmetric Design, Symmetric Factorial Design, Two-way ANOVA
- Lecture 30: Two-factor symmetric Design, Robust setting, Two-way ANOVA
- Lecture 31: Measurement System Analysis
- Lecture 32: Measurement System Analysis (Contd.)
- Lecture 33: Measurement System Analysis (Contd.), Introduction to Factorial Experiments
- Lecture 34: Factorial Experiments
- Lecture 35: Factorial Experiments (Contd.)
- Lecture 36: Factorial Experiments (Contd.)
- Lecture 37: Blocking in Factorial Design
- Lecture 38: Multiple response Optimization & RSM
- Lecture 39: Fractional Factorial Design
- Lecture 40: Taguchi Method