NPTEL : NOC:Quality Control and Improvement with MINITAB (Management)

Co-ordinators : Prof. Indrajit Mukherjee


Lecture 1 - Introduction of Quality

Lecture 2 - Voice of the Customer and Kano Model

Lecture 3 - Quality Function Deployment

Lecture 4 - Critical to Quality Characteristics

Lecture 5 - Data Visualization for Quality Control and Improvement

Lecture 6 - Importance of Pareto Chart and Cause and Effect Diagram

Lecture 7 - Design Failure Mode and Effect Analysis

Lecture 8 - Introduction to Statistical Process Control

Lecture 9 - 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 and 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 (Continued...)

Lecture 33 - Measurement System Analysis (Continued...), Introduction to Factorial Experiments

Lecture 34 - Factorial Experiments

Lecture 35 - Factorial Experiments (Continued...)

Lecture 36 - Factorial Experiments (Continued...)

Lecture 37 - Blocking in Factorial Design.

Lecture 38 - Multiple response Optimization and RSM

Lecture 39 - Fractional Factorial Design

Lecture 40 - Taguchi Method