Deep Learning techniques like image processing are used in Friction Stir Welding Process for the optimization of mechanical properties like Ultimate Tensile Strength, Fracture Strength and elongation % and microstructure properties like grain size and understanding defects formation.

Deep Learning helps automated risk analysis of corrosion and SCC related problems.

Deep materials informatics applicable on a variety of materials data like elemental composition, crystal structure, and 2-D/3-D microstructures images.

ML can accelerate the solution of intricate chemical problems and even solve problems that otherwise would not be tractable. However, the potential benefts of ML come at the cost of big data production; that is, the algorithms demand large volumes of data of various natures and from diferent sources, from material properties to sensor data.

Deep Learning provides quantitative data necessary to make a diagnosis.

ML can accelerate the solution of intricate chemical problems and even solve problems that otherwise would not be tractable. However, the potential benefts of ML come at the cost of big data production; that is, the algorithms demand large volumes of data of various natures and from diferent sources, from material properties to sensor data.