Resource Person/ Facilitator:
Mrs. Surbhi Kakkad,
Director,
NeuAI Labs,

Summary:

1. Key Takeaways:

1. Industry 4.0 is transforming the mechanical engineering landscape, requiring new skills and competencies.
2. AI is transforming mechanical engineering, enabling innovative solutions and improving efficiency.
3. Applications of AI in mechanical engineering include:
   – Predictive maintenance
   – Quality control
   – Design optimization
   – Robotics and automation
   – Machine learning algorithms, including supervised, unsupervised are used
4. In AI applications.
   – AI requires interdisciplinary skills, including programming, data analysis, and
   Domain expertise.

2. Expert Insights:

1. AI can enhance mechanical engineering design, simulation, and analysis.
2. AI-driven predictive maintenance can reduce downtime and increase productivity.
3. Mechanical engineers must develop AI skills to remain relevant in the industry.

Objective/Purpose:

1. To introduce the fundamentals of Artificial Intelligence (AI) and its relevance to
   Mechanical engineering.
2. To explore the applications of AI in mechanical engineering, including design,
   Simulation and Optimization.
3. To understand the role of machine learning in predictive maintenance, quality control, and fault detection.
4. To learn about the use of deep learning in computer vision for mechanical engineering applications.
5. To discuss the integration of AI with IoT and robotics in mechanical engineering.
6. To understand the ethical considerations and future directions of AI in mechanical engineering.
7. To provide hands-on experience with AI tools and techniques used in mechanical engineering.
8. To inspire and motivate students to pursue AI-related projects and research in mechanical engineering.