A Review on Optimization of Process Parameters for Improving Performance in Electrical Discharge Machining
The correct selection of manufacturing conditions is one of the most important aspects to take into consideration in the majority of manufacturing processes and, particularly, in processes related to Electrical Discharge Machining (EDM). It is a capable of machining geometrically complex or hard material components, that are precise and difficult-to-machine such as heat treated tool steels, composites, super alloys, ceramics, carbides, heat resistant steels etc. being widely used in die and mold making industries, aerospace, aeronautics and nuclear industries. From the point of view of industrial applications, SS 410 is a very important material and that’s why for the purpose of experimentation SS 410 with copper electrode and EDM oil as dielectric has been used In the present work. I will take input parameter discharge current, pulse on time and pulse off time. Design of Experiment (DOE) with full factorial design has been explored to produce 27 specimens on SS 410 by edm operation. MRR will be calculated from MRR equation and software available for it and then compare it. Collected data related to surface roughness have been utilized for optimization.
A study on the electrical discharge machining of conductive ceramics
Abstract In this work, a comparative study of the electrical discharge machining (EDM) of three different conductive ceramics has been carried out. The ceramics used in the experiments were cobalt-bonded tungsten carbide (WCCo), hot-pressed boron carbide (B 4 C) and reaction-bonded silicon carbide (SiSiC). This study has been done only for the finishing stages and the selection of the above-mentioned conductive ceramics was motivated by their wide range of applications: machining and mining for WCCo, thermal-neutron absorber and nozzles for B 4 C and wear parts and heat exchangers for SiSiC, among others. The comparative study has been carried out on the influence of the design factors of intensity ( I ), pulse time ( t i ) and duty cycle ( η ) over response variables such as surface roughness (evaluated through the R a parameter), volumetric electrode wear (EW) and material removal rate (MRR). This was accomplished through the technique of design of experiments (DOE), along with multiple linear regression techniques, which allowed us to carry out the analysis with only a small number of experiments.
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