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.
In this study, we propose a deep learning-based method for large-area inspection aimed at the high-speed detection of micro hole diameters. Micro holes are detected and stored in large images using YOLOv8, an object detection model. A super-resolution technique utilizing ESRGAN, an adversarial neural network, is applied to images of small micro holes, enhancing them to high resolution before measuring their diameters through image processing. When comparing the diameters measured after 8x super-resolution with the results from existing inspection equipment, the average error rate is remarkably low at 0.504%. The time taken to measure an image of one micro hole is 0.470 seconds, which is ten times faster than previous inspection methods. These results can significantly contribute to high-speed measurement and quality improvement through deep learning.
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CFRP (Carbon fiber reinforced plastic) has been widely used in different industries such as aerospace, automobile, sports and medical. Laser processing of CFRP has a great potential for industrial applications. In this paper researched the micro cutting and drilling of CFRP with 0.5 mm thickness using 1064 nm ytterbium nanosecond pulsed fiber laser. It also investigated machining characteristics of micro cutting and drilling according to laser power, frequency, scan speed and number of scan (or irradiation). Complete cutting and through-hole drilling were achieved with low frequency when the laser power was low and with low and middle frequency when the laser power increased. However, those were not achieved a frequency of 100 kHz. The cutting width increased when the power increased and decreased when the frequency and the scan speed increased. The hole size increased when the power and the number of irradiation increased and decreased when the frequency increased. In the case of micro hole array, the hole was blocked during the next hole machining when the hole spacing was narrow. The resin was melted by the heat thus blocking the pre-drilled hole. We devised the laser scan method, and the micro hole array with narrow hole spacing was fabricated successfully.
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Micro hole drilling in precision production industries requires smaller holes, higher aspect ratios, and higher working speeds. However, the undesirable characteristics of micro drilling are small signal to noise ratios, wandering drill motion, high aspect ratio, and increasing cutting quality as cutting depth increases. In this study, two different types of experiments are performed on single crystal silicon to decrease crack formation. The first experiment compares the efficiency of various micro hole machining processes using ultrasonic impact grinding and micro drilling. The second experiment suggests optimum conditions for the micro drilling process. The experimental results show that micro drilling technology can be effectively used for drilling single crystal silicon.
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