Application of AI and Its Limitations in Product Design Engineering

1. Clear understanding of where AI adds value in design

2. Awareness of AI limitations and risks

3. Strong emphasis on human judgment and engineering fundamentals

4. Practical guidance for using AI responsibly in product design

1. Introduction to AI in Engineering Design

• What AI is (and what it is not) in the engineering context

• Evolution of AI in product design

2. Applications of AI in Product Design Engineering

• AI-driven concept generation and design optimization

• Generative design and topology optimization

• AI in CAD automation and parametric modeling

• AI-assisted CAE, simulation, and design validation

3. Role of AI Across the Product Development Cycle

• Concept → Design → Analysis → Manufacturing → Quality

4. Limitations of AI in Product Design Engineering

• Dependence on data quality and historical bias

• Lack of contextual, functional, and ethical judgment

• Challenges in understanding real-world manufacturing constraints

• Inability to replace creativity, intuition, and engineering experience

5. Human–AI Collaboration in Design

• AI as a design assistant, not a decision-maker

• Importance of engineering fundamentals.

• Role of critical thinking and validation

6. Case Studies & Real-World Examples

• Successful AI-assisted design applications

• Failures and risks caused by blind AI dependence

7. Future of Product Design Engineering