AI Prediction of Properties in Friction Stir Welding Internship

About Internship

Assistant Professor from Government College of Engineering, India, is accepting interns interested in the field of Computer Science Engineering, in the research area of Artificial intelligence and Machine learning.

This internship focuses on applying Artificial Intelligence and Machine Learning techniques to predict key mechanical properties—tensile strength and hardness—in friction stir welding (FSW) of dissimilar aluminum alloys AA6061 and AA8011. The project integrates materials science with data-driven modeling to improve mechanical performance and optimize welding parameters through computational intelligence. During the internship, students will: 1. Develop Python-based machine learning models to predict tensile strength and hardness of friction stir welded AA6061–AA8011 joints. 2. Work with experimental or provided datasets related to welding parameters and mechanical properties. 3. Perform data preprocessing, feature selection, model training, testing, and performance evaluation. 4. Apply regression and predictive analytics techniques relevant to materials engineering problems. 5. Analyze model outputs to understand the influence of process parameters on mechanical performance. 6. Interpret results scientifically and assist in drawing conclusions aligned with superior mechanical performance objectives. 7. Contribute to documentation, result visualization, and research-style reporting. By the end of the internship, interns will gain: 1. Hands-on experience in applying machine learning to real-world engineering and manufacturing problems. 2. Strong skills in Python-based data analysis, predictive modeling, and result interpretation. 3. Exposure to interdisciplinary research at the intersection of AI, materials science, and welding technology. 4. Experience in technical reporting and research-oriented problem solving relevant to both academia and industry.