09:00 AM – 10:00 AM
Introduction
- Fundamentals of AI and Machine Learning (ML)
- Overview of relevant AI techniques: Regression, Classification, Neural Networks
- Introduction to data-driven corrosion analysis
10:00 AM – 10:45 AM
Data Acquisition and Preprocessing for Corrosion Analysis
- Sensor technologies for corrosion monitoring (electrochemical, ultrasonic, visual)
- Data acquisition strategies and challenges
- Data cleaning and preprocessing techniques
10:45 AM - 11:00 AM
Networking/Refreshments
11:00 AM - 12:00 PM
AI-Driven Corrosion Detection and Monitoring
- Image processing and computer vision for visual corrosion detection.
- Signal processing and pattern recognition for electrochemical and ultrasonic data.
- Anomaly detection and real-time corrosion monitoring.
12:00 PM - 1:00 PM
Lunch Break
1:00 PM - 2:00 PM
Predictive Modeling of Corrosion Rates and Lifespan
- Regression models for predicting corrosion rates.
- Time-series analysis and forecasting of corrosion progression.
- Remaining Useful Life (RUL) prediction using ML.
2:00 PM - 3:00 PM
AI-Enabled Corrosion Prevention and Mitigation
- Material selection and optimization using AI.
- Predictive maintenance and proactive corrosion control.
- AI-driven coating and inhibitor development.
3:00 PM - 3:15 PM
Networking/Refreshments
3:15 PM - 4:30 PM
Case Studies and Industry Applications
- Real-world examples of AI implementation in various industries.
- Discussion of challenges and best practices.
- Discussion on future trends – Digital Twins, IIoTs, Simulations.
- Roadmap for implementing AI the right way.
- Q&A session.
