Electro-discharge machining (EDM) has been extensively employed for machining hard alloys, and its simulations have been widely conducted using finite element analysis (FEA). However, the majority of mesh-based models depended on forecasting the crater profile only based on the temperature gradient, without offering detailed data regarding the machined material properties. It is crucial to understand the behaviour of the machined material in order to accurately assess the flushing efficiency, analyse the wear on the electrode, and examine the interaction between the debris generated during machining and the remaining workpiece. This is done to ensure that no recast material is left behind after the EDM process. For the first time, a meshless smoothed particle hydrodynamics multi-phase model was implemented to gain practical insights and comprehensively understand a very intricate phenomenon that occurs within a very short time. Additionally, this approach is utilised to investigate the characteristics of the materials being machined. We utilised our SPH model to simulate both the capacitance- and transistor-based EDM of Ti–6Al–4V and AISI304 steel. Our simulation considered the temperature-dependent thermal properties and latent heats of the materials. The accuracy of our model was confirmed by comparing its results with experimental, analytical, and finite element analysis (FEA) results. The machined material was observed during its removal from the surface, and the dimensions of the resulting crater, as well as its aspect ratio and the rate at which the material was removed, were predicted with an error ranging from 2 to 22%. This error is far lower than that of the typical finite element (FE) prediction. This model lays the groundwork for a more complex model that will more accurately represent EDM and other similar manufacturing processes.
