One of the technical developments is a shift towards the use of the finite element method (FEM) simulation and artificial intelligence and digital twins to improve die-design applications. It is a huge discussion of how the traditional methodologies of the empirical designs are being complemented by the new computational methodologies, in which there is high production efficiency and quality products. By a combination of computational modeling, materials characterization, nondestructive testing validation, and machine learning algorithms, the performance will significantly increase; experiments on industrial applications show that the design period can be cut down to 4-6 weeks with a 90-95 percent productivity increase. The given article is a deep examination of the FEM modeling methods that may be applied to the process of drawing optimization, the synthesis of the non-destructive testing tools that may be used to guarantee the validity of the process, and the rising uses of machine learning and Industry 4.0. The integration of technologies presents important possibilities to enhance the production efficiency, level the environmental sustainability, and gain competitive advantages in metal forming operations. The implementation process would be done appropriately based on the computing requirements, validation, and interface with the existing production systems.