Glassy carbon (GC) has superior properties such as high corrosion resistance, heat resistance, and low adhesion to glass materials in a glass molding process (GMP). In addition, the demand for GC molds is increasing in various industries that require high precision of glass parts. However, GC is a difficult-to-machine material with high hardness and brittleness. Electrical discharge machining (EDM) can machine GC regardless of its strength or hardness. In this study, tungsten carbide (WC-Co) electrode was fabricated by wire electrical discharge grinding (WEDG). Characteristics of EDM of micro holes on GC were then analyzed. As capacitance and voltage increased, material removal rate (MRR) increased while machining time tended to decrease. However, at low voltages, short circuit and secondary discharge occurred, which increased the electrode wear rate (EWR). As a result, a D-shaped electrode that could prevent short circuit and debris accumulation was fabricated and a micro hole array was machined.

CNN is one of the deep learning technologies useful for image-based pattern recognition and classification. For machining processes, this technique can be used to predict machining parameters and surface roughness. In electrical discharge machining (EDM), the machined surface is covered with many craters, the shape of which depends on the workpiece material and pulse parameters. In this study, CNN was applied to predict EDM parameters including capacitor, workpiece material, and surface roughness. After machining three metals (brass, stainless steel, and cemented carbide) with different discharge energies, images of machined surfaces were collected using a scanning electron microscope (SEM) and a digital microscope. Surface roughness of each surface was then measured. The CNN model was used to predict machining parameters and surface roughness.

Recently, the demand for micromachining of hard materials has been increasing. Machining microholes, grooves, and structures in hard materials such as tungsten carbide is very difficult. In this study, the machining characteristics of a microdisk tool for microgroove machining of tungsten carbide were studied. Microtools made of polycrystalline diamond (PCD) were fabricated using wire electrical discharge grinding (WEDG) to machine high-hardness tungsten carbide. Rectangular and V-shaped disk tools were fabricated by WEDG with controlled wire paths. In the micro grooving of tungsten carbide, the effects of capacitance and feedrate on the surface roughness of microgrooves and the wear of disk tools were studied. As the capacitance and feed rate decreased, the surface roughness decreased and no significant wear was observed in the PCD tool. However, an increase in tool edge radius of several micrometers was observed.