On the Influence of Electrical Discharge Drilling Parameters and Per-formance Measures of Inconel 718 Superalloy - a Study
Keywords:Inconel 718, Electrical Discharge Drilling, ANOVA, Material Removal, Tool Wear, Surface Roughness, Artificial Neural Networks, and Scanning Electron Microscope
In order to achieve higher productivity and product quality, the investigation of machining parameters on Electrical Discharge Drilling and surface characteristic analysis are most critical for manufacturing industries. The intention of this article is to assess the impact on performance matrices including Material Removal Rate, and Surface Roughness of input factors of peak current, pulse-on and off duration while drilling with a rotary hollow copper tool on Inconel 718 under Tungsten powder suspended kerosene. Analysis of Variance has been implemented using MINITAB release 18 software to identify the most significant input factors. An Artificial Neural Network was used for validating the experimental results of the drilling process. The additional intention of this research is to discover the significance of influencing input parameters and analyze the quality surface of the workpiece were observed by microscope tests. The experimental results indicated that the peak current and pulse-on period have an effect on the performance of the drilling process considerably.