E-PashuHaat Transportal

GPMS TRANSPORTAL APPLIED AI COURSES

AI

Course 42 - AI-Driven Innovation in Mechanical Engineering

Duration: 36 Hours (6 Hours per week - 2 Hrs x 3)

Week 1 - Smart Design & Simulation with AI
Learning Outcome

Leverage AI to enhance mechanical design and simulations.

1.1 AI in generative design for mechanical components.
1.2 Machine learning for material selection and optimization.
1.3 AI for simulating mechanical behaviors under different conditions.

Practical Component
Use AI tools to design and simulate a mechanical component.
Week 2 - AI-Powered Manufacturing Excellence
Learning Outcome

Learn how AI improves and optimizes manufacturing processes.

2.1 Machine learning for predictive quality control in manufacturing.
2.2 AI for streamlining assembly line operations.
2.3 AI-driven supply chain and inventory management.

Practical Component
Develop an AI model to optimize production workflows in a factory.
Week 3 - Predictive Maintenance: AI in Action
Learning Outcome

Explore AI applications in predicting and preventing mechanical failures.

3.1 AI for condition monitoring and fault detection in machinery.
3.2 Machine learning models for predicting failure in mechanical components.
3.3 AI-driven maintenance scheduling for mechanical systems.

Practical Component
Build an AI-based predictive maintenance system for mechanical equipment.
Week 4 - Robotics & Automation with AI
Learning Outcome

Dive into the use of AI in robotics and automation within mechanical engineering.

4.1 AI-driven motion planning for robots.
4.2 Machine learning for robot vision and sensory processing.
4.3 AI for optimizing robotic assembly and operations.

Practical Component
Build an AI model for robotic motion planning.
Week 5 - Smart Thermal & Fluid Systems with AI
Learning Outcome

Discover how AI optimizes thermal and fluid systems in mechanical engineering

5.1 AI for heat transfer analysis and optimization.
5.2 Machine learning models for fluid flow prediction.
5.3 AI-driven solutions for HVAC and cooling systems.

Practical Component
Develop an AI tool for optimizing thermal efficiency in mechanical systems.
Week 6 - Capstone Project and Assessment
Learning Outcome

Apply AI to a real-world mechanical engineering challenge.

6.1 Develop an AI-based solution for mechanical design, production, or maintenance.
6.2 Peer assessment and feedback.
6.3 Final project presentation and evaluation.

Practical Component
Present an AI-powered solution for a mechanical engineering challenge.