These lecture materials are openly available to everyone.
For students: You are encouraged to use these materials to support your studies.
For instructors: You are welcome to use, modify, and distribute these materials in your teaching.
No credit or reference to us is required.
This course introduces core concepts and practical applications of artificial intelligence for smart manufacturing. It covers a wide range of topics including vision AI, time series analysis, signal based learning, predictive maintenance, explainable AI, and physics-informed AI. By the end of the course, students will be able to understand and apply AI methods to real world manufacturing problems in a data driven and engineering aware manner.
Topics HTML Colab Slides PowerPoints PS Solution
[Part 1: Foundations of Manufacturing AI & Data Strategies]
Introduction to Manufacturing AI and AX Trends
Fundamentals of AI and Machine Learning
Small Data Strategies for Manufacturing
Domain Adaptation and Transfer Learning
[Part 2: Intelligent Manufacturing by Data Type]
Vision AI for Quality Inspection
Sensor-based Time Series Analysis
Signal Processing and AI Integration
[Part 3: Engineering Design & Reliability Assurance]
Generative AI for Engineering Design
Active Learning for Process Optimization
Prognostics and Health Management
eXplainable AI for Manufacturing
[Part 4: Intelligent Systems & Emerging Trends]
Physics-Informed AI
Agentic AI and LLMs for Manufacturing
Agent-based Autonomous Manufacturing Operations