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The most important cost element of electric discharge machining (EDM) is the production of tool electrode (shortly electrode). In the EDM process, copper and its alloys are often used as electrode materials. The machining with EDM without increasing the costs can be achieved by selecting the proper electrode with low production and material costs as well as high workpiece material removal rate (MRR), low electrode wear rate (EWR), and relative wear (RW = MRR/EWR). In this study, the EDM performance outputs, namely, MRR and RW were experimentally investigated for electrolytic copper, CuCr1Zr (with and without aging treatment) and CuCo2Be alloy electrode materials for varying machining parameters. The performance outputs were affected by the electrode material and the applied aging treatment. The aged CuCr1Zr alloy electrodes had higher electrical conductivity and better machining performance than the as-received alloy. The CuCo2Be alloy electrodes exhibited moderate to high MRR; however, their RW was the highest. Although the electrolytic copper has moderate MRR performance compared to the investigated alloys, its low cost increased its performance index, making it a more suitable electrode material for EDM applications. [ABSTRACT FROM AUTHOR]

In this paper, an inexpensive auxiliary tool vibration device is described that improves the efficiency of deep groove electrical discharge machining (EDM). Titanium alloy samples (Ti-6Al-4V) were machined using two different methods: unassisted normal EDM and vibration-assisted EDM, using copper, copper-tungsten, and graphite tool electrode materials. The vibration-assisted EDM machining was done at 40, 90, and 140 Hz, and the material removal rate, tool electrode wear rate, and surface roughness of the specimens were compared. Experimental results revealed that the material removal rate with vibration-assisted EDM was better than that obtained using unassisted EDM with copper and copper-tungsten electrodes. In this study, the vibration frequency was found to have an optimum value of 90 Hz with respect to surface roughness. It was found that the machining time for a groove 10 mm deep with vibration-assisted EDM was reduced by 200% compared to unassisted EDM. This new vibration device can help in the development of a more efficient deep groove EDM. [ABSTRACT FROM AUTHOR]

Electrical discharge machining is a non-conventional machining method that is used for machining of hard-to-machine materials, components in which length to diameter ratio is very high or products with a very complicated shape. The process is commonly used in automobile, biomedical, chemical, aerospace, tool and die industries etc. It is very essential to select optimum values of input process parameters to maximize the machining performance. In this paper an attempt has been made to carry out multiobjective optimization of the surface roughness (SR) and material removal rate (MRR) for the EDM process of EN 19 on a CNC EDM machine using copper electrode through evolutionary optimization techniques like teaching Learning Based Optimization (TLBO) technique and biogeography-based optimization (BBO) technique. The input parameter considered for the optimization are Current (A), Voltage (V), Pulse off time (µs), and Pulse on time (µs). TLBO and BBO technique wereused to obtain maximum MRR and minimize the SR. It was found that SR and MRR increased linearly when discharge current was in mid-range however non-linear increment of MRR and SR was found when the current was too small or too large. Scanning Electron Microscope (SEM) images also indicated a decreased SR. In addition, obtained optimized values were validated for testing the significance of the TLBO and BBO technique and a very small error value of MRR and SR was found. BBO outperformed TLBO in every aspect like less percentage error and better-optimized values, however, TLBO took less computation time than the BBO. [ABSTRACT FROM AUTHOR]