Lecture 1 - Introduction to Tribology
Lecture 2 - Tribological Interfaces
Lecture 3 - Fundamentals of Friction and Wear
Lecture 4 - Adhesion, Abrasion, and Surface Fatigue Mechanisms
Lecture 5 - Wear Measurement Techniques
Lecture 6 - Principles of Lubrication, types of Lubricants and their properties
Lecture 7 - Lubrication regimes and film thickness calculations
Lecture 8 - Mixed Lubrication
Lecture 9 - Hydrodynamic Lubrication Theory
Lecture 10 - Design Considerations for Hydrodynamic Lubrication Systems
Lecture 11 - Elastohydrodynamic Lubrication
Lecture 12 - Solid Lubrication
Lecture 13 - Surface modification techniques for tribological applications
Lecture 14 - Thin film coatings and their tribological properties
Lecture 15 - Nanotribology
Lecture 16 - Tribocorrosion
Lecture 17 - Wear testing techniques and standards
Lecture 18 - Measurement and analysis of wear debris
Lecture 19 - Experimental Design and Statistical Analysis
Lecture 20 - Introduction to Data-Enabled Engineering
Lecture 21 - Data Collection and Preprocessing
Lecture 22 - Feature Extraction and Selection
Lecture 23 - Introduction to Machine Learning Algorithms
Lecture 24 - Regression and Classification Algorithms for Tribological Modeling
Lecture 25 - Deep Learning for Tribological Engineering
Lecture 26 - Data-Driven Models for Friction Prediction
Lecture 27 - Data-Driven Models for Wear Prediction
Lecture 28 - Data-Driven Models for Lubricant Optimization
Lecture 29 - Data-Driven Models for Tribofilm Formation
Lecture 30 - Data-Driven Models for Tribocorrosion Prediction
Lecture 31 - Prediction of Coating and Surface Treatment Performance
Lecture 32 - Optimization of Surface Engineering Processes using Machine Learning
Lecture 33 - Uncertainty Quantification and Sensitivity Analysis
Lecture 34 - Data Management and Ethics in Data-Enabled Engineering
Lecture 35 - Case Studies in Data-Enabled Tribological Engineering
Lecture 36 - Future Directions in Data-Enabled Tribological Engineering
