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.
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Micro Hole Machining Characteristics of Glassy Carbon Using Electrical Discharge Machining (EDM) Jae Yeon Kim, Ji Hyo Lee, Bo Hyun Kim Journal of the Korean Society for Precision Engineering.2025; 42(4): 325. CrossRef
Prediction of Machining Conditions from EDMed Surface Using CNN Ji Hyo Lee, Jae Yeon Kim, Dae Bo Sim, Bo Hyun Kim Journal of the Korean Society for Precision Engineering.2024; 41(11): 865. CrossRef
Microchannels machining can be used to make micro molds for microfluidic chips. The fluid flow in the channel can be controlled, by changing the cross sectional shape of the channel. V-shaped channels with a specific angle are not easily made with the etching process. This study presents the mechanical machining of microchannels of V-shaped cross section, on cemented carbide (WC-Co). In this study, to reduce tool wear in the process of machining, the micro conical tool was fabricated using polycrystalline diamond (PCD). The tool wear of the conical tool and form accuracy of channels, were investigated during V-shaped microchannel machining.
Citations
Citations to this article as recorded by
Micro Hole Machining Characteristics of Glassy Carbon Using Electrical Discharge Machining (EDM) Jae Yeon Kim, Ji Hyo Lee, Bo Hyun Kim Journal of the Korean Society for Precision Engineering.2025; 42(4): 325. CrossRef
Machining Characteristics of Micro EDM of Silicon Carbide Ju Hyeon Lee, Chan Young Yang, Bo Hyun Kim Journal of the Korean Society for Precision Engineering.2024; 41(2): 131. CrossRef
Study on Micro Grooving of Tungsten Carbide Using Disk Tool Min Ki Kim, Chan Young Yang, Dae Bo Sim, Ji Hyo Lee, Bo Hyun Kim Journal of the Korean Society for Precision Engineering.2024; 41(2): 123. CrossRef
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