Optimal solution of parameters for machining of INCONEL 718

Abstract

It is a desirable need to evaluate the machining parameters for effective utilization of a process and the material such as Inconel-718. Selection of an appropriate optimal range of cutting parameters is quite essential to achieve high-quality cut and is a challenging task within this domain of study. The aim of this research is to develop a robust prediction model which can suggest the desired range of cutting parameters for accomplishing better cutting quality, precision and geometrical accuracy. Experiments have been performed on a 300W (CNC-PCT 300) pulsed Nd: YAG laser cutting system at various levels of input cutting parameters viz.: gas pressure, standoff distance, cutting speed and laser power. Thereafter, regression analysis, response surface methodology (RSM) and artificial neural network (ANN) techniques have been adopted to develop mathematical models in terms of aforementioned input cutting parameters for geometrical quality characteristics: Top Kerf Width (TKW), Bottom Kerf Width (BKW) and Kerf Taper (KT). These developed models have been validated by comparing the predicted values with the experimental ones. Further, these models have been optimized using multi-objective genetic algorithm and particle swarm optimization techniques, in order to ascertain the optimal range of cutting parameters pertaining to better quality cut with high precision and geometrical accuracy. newline newline