Investigation on Kerf Taper and Effect of Process Parameters on Micromachining of Nickel-Base Super Alloy

It is desirable to analyse machining settings in order to get the most out of a process and a material like Inconel-718. The choice of an acceptable ideal range of cutting parameters is critical for achieving a high-quality cut and is a difficult issue in this field. The goal of this study is to create a reliable prediction model that can recommend the appropriate range of cutting variables. Experiments were carried out on a CNC-PCT 300 W pulsed laser cutting system. Then, using an artificial neural network (ANN), mathematical models for the input cutting parameters for geometrical quality features. The projected values were compared to the experimental values to validate the proposed models. These models have also been refined using a multi-objective genetic algorithm to determine the best range of cutting parameters for a better quality cut with high precision and geometrical correctness.