Utilization of Data Driven Techniques for Detection of Process- Structure- Property Relationships for Additive Manufacturing of Metallic Components
Additive manufacturing is a process that not only make end use product of any desired shape but it also has properties to alter the material composition as well the microstructure properties. Since the internal working of any mechanism involves in a process cannot be normally measured through experiment, so the modeling based on the empirical data can be used for the successful completion of this problem. This article review and depicts the modeling and various data driven techniques to derivate the relationship between properties, structure and processes for any metallic product through Additive manufacturing. Article also emphasis on all the factors that influence the rapid designing and various optimization techniques used including the data mining techniques. This article will be helpful in the understanding the Additive manufacturing material alteration methods and various data driven techniques for the model formation.
Keywords - Additive Manufacturing, Thermal Fluid Flow, Data Mining, Material Modeling.