Design of Experiment and Intelligent Optimization Techniques

                 Mathematical Modeling for Engineers

Course objective:  Introduction to mathematical modeling and applied mathematics, more generally. The main objective will be to learn how to take phenomena arising in physics and statistical methods, Introduction to the Science of Mathematical Modeling;

1. Mathematical Modeling Procedure in Engineering

2. Dimensional Analysis - Rayleigh's Method

3. Dimensional Analysis - Buckingham pi theorem

        Probability and statistics for Engineers

Course objective: Understand the different statistical methods to solve problems in the engineering field containing data analysis. 

1. Data Science in Manufacturing Industries

2. Design of Experiment concept with factorial design for conducting project work

3. How do we calculate the experimental data with ANOVA Table

4. Data Normalization for reducing data variation errors

5. Linear Regression Model

6. Multiple Linear Regression Model

7. Experimental data analysis with Design of Experiment concept through Design Expert

Intelligent Optimization Techniques

Course objective: The course aims at building capabilities in the students for analyzing different situations in the industrial/ business scenario involving limited resources and finding the optimal solution within constraints by using advanced optimization tools

1. Genetic Algorithm

2. Tabu Search

3. Ant Colony Optimization

4. Particle Swarm Optimization

5. Simulated Annealing

6. Firefly Algorithm

7. The whale optimization

8. Fuzzy Logic Modelling

9. Neural network modeling 

10. Matlab coding for Genetic Algorithm