Application of Artificial Intelligence To Enhance Student Learning of Metallography

South Dakota School Of Mines And Technology, Rapid City SD

Investigators

Abstract

This project is creating a learning environment for teaching metallography and is developing techniques for automated microstructure recognition. In the first phase of this project, it is developing a database of micrographs. This database provides a gallery of micrographs and all of the required information to produce the micrograph. In addition, it provides a description of the microstructure and instructions for identifying the significant features and is being used as a learning tool for students and scientists. The second phase of this project is leveraging the information collected from the micrograph database to develop methods for automatic characterization of micrographs through the use of image analysis and processing, texture analysis, neural networks, and artificial intelligence algorithms. This project is also leading to improved pedagogical activities for teaching faculty in both Materials Science and Computer Science. The work is fostering interdisciplinary cooperation and providing student mentoring to both graduate and undergraduate students. The modules developed are being disseminated to similar institutions to help foster learning of metallography skills that are required in industry.