EDM Parameters Optimization on Tool Wear Rate using Advanced Optimization of Titanium Alloy

Electrical Discharge Machining (EDM) is the most popular unconventional machining processes (UMP) in modern industries. EDM requires a low initial investment and used to machine difficult-to-cut and to machine complex shapes. There is sparking takes place between workpiece and tool, and the machined surface has an exact replica of tools. Due to sparking, material is removed from workpiece and some material is also removed from the tool surface, thus resulting distortion of the tool there. This further leads to affect the quality of machined surface, hence it is required to minimize tool wear rate (TWR). This paper is based on parameter optimization to minimized TWR. Thirty experiments were carried out as per the design of experiments using response surface methodology, within the selected range of various input variables. The regression model is developed for TWR. An advanced optimization Jaya Algorithm used to optimize TWR model. A predictable ANN model is also developed to validate the optimum result.