Evaluation and monitoring study on the surface roughness of workpiece after micro-electrical discharge machining is very difficult for complex material removal mechanism. Signal processing for monitoring machining process have been one of the focuses of research on process reliability.
In this paper, surface roughness monitoring system was developed by statistical energy methodology in micro-electrical discharge milling of Ti2AlN and Ti2AlC materials. Preferentially, Ti2AlN and Ti2AlC powder was sealed in steel container under argon atmosphere and mixed by 3-dimensional high energy ball milling. Spark plasma sintering process was used to fabricate Ti2AlN and Ti2AlC bulk material. Crystall structure and microstructure were investigated by X-ray diffraction and Field Emission Scanning Electron Microscopy on Ti2AlN and Ti2AlC bulk material. Also, relative density, vickers hardness, electrical conductivity, thermal conductivity were evaluated for each ceramic materials. Relative density of Ti2AlN and Ti2AlC materials was 99.21% and 98.78%. Vickers hardness was measured 8.82GPa and 5.06GPa. Electrical conductivity was 5.865×106S/m and 4.170×106S/m. Thermal conductivity was 56.00W/m?k and 34.4W/m?k respectively. Machining characteristics such as material removal rate, electrode wear length and surface quality of micro-channel machined by micro-electrical discharge milling, compared to that of Ti-6Al-4V alloy. Material removal rate, electrode wear length, surface integrity and average surface roughness are affected by Electrical conductivity and thermal conductivity. Particularly, electrode wear length and average surface roughness of Ti2AlN and Ti2AlC ceramic materials drastically decreased at 100V of voltage and 10nF of capacitance. Also micropore, microcrack and globules found in Ti2AlN and Ti2AlC ceramic materials while superposition found in Ti-6Al-4V alloy. It increase surface roughness of Ti-6Al-4V alloy regardless of machining condition. Besides, acoustic emission raw signal was transformed from time domain to frequency domain by shock response spectrum and analyzed by weight moving average among statistical energy analysis method.
Consequently, shock response spectrum and statistical energy analysis with voltage, current and acoustic emission raw signal were very useful method for surface roughness monitoring during micro electrical discharge milling of Ti2AlN and Ti2AlC ceramic material.