Abstract:
Abstract:
Micro-electrical discharge machining (μEDM) suffers from the problem of low material removal rate (MRR) and poor surface finish, especially when there are recurring abnormal sparks. Such sparks are mainly due to the accumulation of unflushed debris in the discharge zone resulting in a frequent arcing phenomenon. Vibration assistance to μEDM has proven contributions to the MRR and surface finish enhancement, but the intrinsic information on discharge pulse modification due to the vibration is unclear. The present work proposes a pulse categorization strategy to understand the nature of discharge pulses during the conventional and ultrasonic vibration assisted μEDM. The discharge pulses were acquired at a sufficiently high sampling rate using NI LABVIEW-based data acquisition through an in-house developed pulse discrimination system (PDS). The developed PDS is simultaneously used to estimate the real-time discharge energies of individual pulses and their histograms with the machining progress. The acquired information from the developed PDS is used to justify the variations in discharge energy, discharge frequency, surface roughness and accuracy with increasing machining depth. Vibration assistance to the μEDM process was found beneficial, with an 18% increase in the discharge energy, and a 7.14% reduction in the percentage error in depth. The surface roughness at high-energy settings reduces from 3.2 μm to 0.45 μm because of ultrasonic vibration assistance.
