The Role of Machine Learning Algorithms in Materials Science: A State of Art Review on Industry 4.0

The 21st century has witnessed a rapid convergence of manufacturing technology, computer science and information technology. This has led to a paradigm of 4.0. The hitherto known developments in metallurgical and materials practices are largely driven by application of fundamental knowledge through experiments and experiences. However, the mounting demands of high performance products and environmental security calls for the 'right first time' manufacturing in contrast to the traditional trial and error approach. In this context, a priori capability, for prediction and optimization of materials, process and product variables, is becoming the enabling factor. In recent time, research in material science is increasingly embarrassing the computational techniques in development of exotic materials with greater reliability and precision. The present study is aimed at exploring the computer vision and machine learning techniques in different application areas in materials science.