Optimization of Machining Parameters of Niobium C-103 Using Taguchi and ANN Techniques

The work presented here is on optimizing parameters in CNC turning operations on the superalloy Niobium C103. The study used multi-response criteria while utilizing the Taguchi orthogonal array in combination with artificial neural networks (ANN). Niobium C103 has good mechanical and physical properties. To optimize operational parameters of cutting speed, feed rate, and depth of cut, experiments were conducted using L27 orthogonal array by considering the performance characteristics of surface finish, cutting force, and cutting temperature. The outcomes indicate that feed rate has the major effect on surface roughness (Ra), cutting force (Fz), and cutting temperature (CT), with corresponding R2 values of 93.75%, 98.5%, and 99.33%, respectively.