Simulating the Electrical and Thermal Conductivity in EDM Die Sinking of Cu-TaC Compact Electrodes Using Neural Network

Electrical and thermal conductivity of electrode materials in Electrical Discharge Machining (EDM) is the main factors that determine the suitability of these electrodes. These electrodes are usually made from graphite, copper and copper alloys because these materials have high electrical and thermal conductivity in additional to high melting temperature. The objective of this paper is to simulate the electrical conductivity and thermal conductivity for new compact electrodes made from Cupper-Tantalum Carbide (Cu-TaC). This simulation based on experimental work. Materials have been used in the experiment were Cupper and Tantalum Carbide powders. The compositions of the Cu-TaC are made of 30 % and 55 % wt of TaC, while the compacting pressures are 1, 500 psi and 3,000 psi. The thermal and electrical conductivities have been measured. The Neural Network (NN) technique has been used to simulate the electrical conductivity and thermal conductivity of the green compacted electrodes. They were subjected to sintering at temperatures of 450°C and 850°C.