Study on tool steel machining with ZNC EDM by RSM, GREY and NSGA

An effort over the process of increasing the Material Removal Rate (MRR) and minimizing the Tool Wear Rate (TWR) is made while machining of Tool steel as work material with copper as the tool electrode with Z -Axis Numerical Control - Electrical Discharge Machine (ZNC-EDM) by maintaining positive polarity. Basically Tool steel by its intrinsic property falls under the hard to cut material type. Moreover where ever precision is the very need, we move from conventional to non conventional machining. Analysis is made by making use of the CCD of Response Surface Methodology. V-in-Spark Voltage, I-in-Spark Current and T-on-Pulse on Time is considered out of many influencing factor for the experimentation purpose as input parameters based on literature support. The most predominant output factor which comes to play in machining process is Metal Removal Rate (MRR), Tool Wear Rate (TWR). In order to expel from the stochastic phenomenon the MRR and TWR factors are concentrated to the extreme level of operating factors domain. A quadratic equation among the output and input factor is acquired with the help of Response Surface Methodology (RSM). For the considered range of domain of experimental values, the equation developed reveals that at 95% confidence level, the peak current inputs makes a major role in deciding the MRR, whereas for the TWR the main impact is produced by input voltage and then spark-on time. For the expected optimal output, the corresponding input setting lies around Voltage level of 1 V, Current value of 15 Amps and On -Time of 60 mu sec. By keeping the maximum the best for Material Removal Rate, desirability is 0.367 and by keeping the minimum the best a desirability of 0.693 is obtained for TWR. The experimentally observed set of values well coincides along with the optimization with the help of GREY and Pareto Analysis of NSGA. Fig.7 & Fig. 8 depicts an image for the above mentioned parameter settings and its factor measurement shows (C) 2020 Published by Elsevier B.V.