Multi-objective optimization of Nd:YAG laser cutting of nickel-based superalloy sheet using orthogonal array with principal component analysis

Laser cutting of nickel-based superalloy sheets, having wide applications in aircraft and rocket industries, is important from the quality of cut point of view. Keeping this in view, a hybrid approach of Taguchi method (TM) and principal component analysis (PCA) has been applied for multi-objective optimization (MOO) of pulsed Nd:YAG laser beam cutting (LBC) of nickel-based superalloy (SUPERNI 718) sheet to achieve better cut qualities within existing resources. The three-quality characteristics kerf width, kerf deviation (along the length of cut), and kerf taper have been considered for simultaneous optimization. The input parameters considered are assist gas pressure, pulse width, pulse frequency, and cutting speed. Initially, single-objective optimization has been performed using TM and then the signal-to-noise (S/N) ratios obtained from TM have been further used in PCA for multi-objective optimization. The results of MOO include the prediction of optimum input parameter level and their relative significance on multiple quality characteristics (MQC). The responses at predicted optimum parameter level are in good agreement with the results of confirmation experiments conducted for verification tests.