Evaluation of micro-EDM milling performance using pulse discrimination

In this paper, the pulse discrimination of gap voltage and discharge current waveforms occurring during micro-EDM milling of micro-channels is analyzed in relation to process parameters variation and machining performance. The pulse classification algorithm discriminates voltage and current waveforms into four defined pulse types: short, arc, delayed and normal. The micro-channels are manufactured in hardened steel using an energy level corresponding to the finishing regime and varying pulse width, frequency, gain and gap. The analysis shows that when the erosion process is stable, normal discharges are predominant. Delayed and short pulses are very sporadic. A major number of arcs can be detected when the gap is decreased and gain increased, i.e. erosion speed and feed rate are increased and affect in particular tool wear. Also the increase of the pulse width has an effect on tool wear, though the percentage of the arcs remains small. On the contrary, material removal rate does not seem to be apparently related to the percentage of arcs as the process parameters are varied, since these values are spread in a constant range for all parameter combinations. The evaluation of the depth errors does not provide any significant insights about the erosion process in relation to the considered process parameters.