The need for large-area cross-sectional analysis with nanometer precision is rapidly growing in various advanced manufacturing sectors. Traditional focused ion beam (FIB) techniques are too slow for milling millimeter-scale volumes. They often introduce ion implantation, redeposition, and curtaining effect, which ultimately prevent effective large-area processing and analysis. To overcome these limitations, we developed a hybrid machining process integrating femtosecond laser micromachining for rapid roughing with FIB milling for precision finishing. Angle of incidence (AOI) control during laser machining was employed to minimize the taper angle of laser-ablated sidewalls, thereby significantly reducing subsequent FIB milling volume. Using a 1030 nm, 350 fs laser, we achieved nearly vertical sidewalls (taper angle: ~2.5° vs. ~28° without AOI control) in silicon. Raman spectroscopy revealed a laser-affected zone extending about 2 μm perpendicular to the sidewall, indicating the need for further FIB milling besides laser-tapered regions to remove laser-induced damage. On multilayer ceramic capacitors and micropillar fabrication, the hybrid laser-FIB method achieved efficient large-area cross sections with preserved microscale details. We present the development of an integrated triple-beam system combining laser, plasma FIB, and SEM, capable of fast volume removal and nanoscale imaging in one equipment. This approach can markedly improve throughput for large-area cross-sectional analysis.
This study analyzed acoustic emission (AE) signals generated during ultrasonic machining of SiC cathodes and evaluated classification performances of various machine learning models. AE data were collected in both waveform and hit formats, enabling signal characterization through statistical analysis and frequency domain examination. Various machine learning models, including XGBoost, KNN, Logistic Regression, SVM, and MLP, were applied to classify machining states. Results showed that XGBoost achieved the highest classification accuracy across all sensor positions, particularly at the upper part of the worktable with an accuracy of 98.35%. Additional experiments confirmed the consistency of these findings, highlighting the influence of sensor placement on classification performance. This study demonstrates the feasibility of monitoring AE-based machining state using machine learning and emphasizes the importance of sensor placement and signal analysis in improving classification accuracy. Future research should incorporate defect data and deep learning approaches to further enhance classification performance and process monitoring capabilities.
This study aimed to develop a regression-based model for predicting tool life in manufacturing environments, with goals of enhancing productivity and reducing costs. In machining operations, particularly roughing processes, high cutting forces can accelerate tool wear, often leading to process interruptions and increased defect rates. Previous research on tool life prediction has frequently relied on empirical models and statistical methods, which face limitations in reliability across diverse machining conditions. To address this issue, we proposed a data-driven approach that could collects tool wear data under varying machining conditions (such as cutting speed, feed rate, and depth of cut) and applied regression models to predict tool life effectively. The model’s performance was validated under multiple conditions to assess its predictive accuracy. This study offers a practical tool life management solution for manufacturing settings, optimizing tool usage and enhancing operational efficiency.
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
In the optical systems field, key components such as spectroscopic elements often require the use of optical materials with high-refractive indices to achieve miniaturization and lightweight characteristics. However, high-refractive index optical materials have low machinability due to their brittle characteristic. In this study, we investigated the changes in surface characteristics during precision pattern machining of high-refractive index materials; specifically, a low fracture toughness, for use in grating spectroscopic elements. The experiment involved diamond turning for the primary machining, and for the secondary pattern machining, the tool rake angle, tool feed rate, and depth of cut were set as variable conditions. Surface roughness measurements and surface quality analyses were carried out using a white-light interferometer and tool microscopy. The results provide insights into the influence of conditions on the surface properties during the machining of high-refractive index materials for grating spectroscopic components. Under the machining conditions with a tool rake angle of -65o, tool feed rate of 5,000 mm/min, and a depth of cut 10 nm, the surface roughness of Ra 8.0 nm was achieved. Based on these findings, we plan to conduct further research on the mechanical fabrication of the blaze angle for grating spectroscopic components.
Here in, a high-quality automotive camera lens was developed based on an ultra-precision diamond turning core and cyclic olefin polymer (COP) injection molding process. To improve surface roughness and achieve the accuracy of plastic injection molding lens, systematic mold core machining process was developed and demonstrated using the diamond turning machine. The cutting tool path was generated by using NanoCAM 2D, and it was partly revised to prevent interference between the cutting tool and the workpiece. After the initial machining using the generated tool path, the compensation-cutting process was conducted based on the measured surface profile of an initially machined surface. After two times of compensation machining, the fabricated core mold showed a shape error of 100 nm between peak to valley (PV) and Arithmetic mean roughness (Ra) of 3.9 nm. The performance of the fabricated core was evaluated using an injection molding test. Injection molded aspheric plastic lens showed contrasts that were higher than 55% at 0.0 F, 30% at 0.3 F, and 20% at 0.7 F without any moiré phenomenon that meets the specification for automotive vision module with 1MP and 140° field of view.
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Research progress on grinding contact theory of axisymmetric aspheric optical elements Wenzhang Yang, Bing Chen, Bing Guo, Qingliang Zhao, Juchuan Dai, Guangye Qing Precision Engineering.2026; 97: 24. CrossRef
Performance enhancement of material removal using a surface-refinement model based on spatial frequency–response characteristics in magnetorheological finishing Minwoo Jeon, Seok-Kyeong Jeong, Woo-Jong Yeo, Hwan-Jin Choi, Mincheol Kim, Min-Gab Bog, Wonkyun Lee The International Journal of Advanced Manufacturing Technology.2024; 135(11-12): 5391. CrossRef
Advanced engineering ceramics have been highlighted mainly owing to their superior hardness, corrosion/wear resistance, and thermal insulation performances. However, they are usually very difficult-to-cut because of their high brittleness. In light of this, ultra-precision machining has been studied to perform ductile-regime cutting in the machining of ceramics. Ductile-regime cutting can feature a smoother surface, and lower subsurface damage as the dominant material response during cutting showed ductile behavior. Researchers have investigated promoting ductileregime cutting to improve the machinability of ceramics. In this study, various coating materials were applied to the workpiece surface, and their effects on machinability improvements were explored. A total of 6 surface coatings and lubricants were applied to soda-lime glass. The critical depth of cut (CDC), the depth where the ductile-brittle transition (DBT) occurred, was increased in all coatings and lubricants, with an improved ductile cutting regime. Experimental results showed that solid coatings were more effective than liquid lubricants in enhancing the ductile cutting regime. It was thought that solid coatings induced an additional downward force by resisting material deformation and chip evacuation, thus contributing to suppression of crack opening. It is expected that this research can contribute to the machinability improvements of brittle materials.
There are various micromachining processes available for manufacturing highly integrated and precise parts, each having its own characteristics and limitations. The degree to which micromachining processes meet the requirements depends on characteristics of parts that are different, making it difficult to determine the most appropriate process. In this context, the present study presents an algorithm for determining the optimal micromachining process by applying the Fuzzy AHP-TOPSIS technique frequently used for multi-criteria decision-making. Fuzzy AHP was employed for calculating weights of requirements for a given part. Fuzzy TOPSIS was employed for determining ranks of candidate processes based on weights of requirements and evaluation of processes. Fuzzy logic was applied to handle ambiguous and inaccurate information encountered in evaluating the relative importance of requirements and performances of processes. The case study in which the optimal process for micro-hole drilling of a fuel injection nozzle was determined showed that the proposed method was effective. It could be extended to micromachining of various shapes.
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Cutting of Chemically Strengthened Glass Using the Combination of Electrochemical Discharge and Grinding Processes Jonghwan Kim, Jihong Hwang Journal of the Korean Society for Precision Engineering.2024; 41(12): 957. CrossRef
Germanium, an optical material, has high transmittance and refractive index and low light scattering in the infrared region, and research is being conducted to utilize it in various industrial fields. Various forms of optical lenses can be subjected to ultra-precision machining with high quality surface roughness, and they form accuracy through single point diamond turning (SPDT). In particular, the diamond tool with a negative rake angle and the u-LAM process that applies a 1,064 nm laser to the material have been studied to fabricate brittle materials into optical lenses. In this study, the effects of process parameters, such as laser power (W), spindle speed (RPM), feed rate (mm/min), and depth of cut (μm), on the surface roughness of a sub-nanometer scale and the occurrence of defects during the machining process were analyzed for Germanium materials. The process of removing these defects was also analyzed.
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A Study on Pattern Machining Technology for Germanium Materials Using Grooving Machining Process Joong Kyu Ham, Jong Gyun Kang, Hwan Ho Maeng, Seong Hyeon Park, Jin Yong Heo, Young Durk Park, Geon Hee Kim Journal of the Korean Society for Precision Engineering.2024; 41(2): 111. CrossRef
Fabrication and Characterization of Automotive Aspheric Camera Lens Mold based on Ultra-precision Diamond Turning Process Ji-Young Jeong, Hwan-Jin Choi, Jong Sung Park, Jong-Keun Sim, Young-Jae Kim, Eun-Ji Gwak, Doo-Sun Choi, Tae-Jin Je, Jun Sae Han Journal of the Korean Society for Precision Engineering.2024; 41(2): 101. CrossRef
A hairpin motor is a type of motor that is used for driving an eco-friendly car. Unlike a conventional coil-winding motor, hundreds of hairpins formed by an enameled copper wire with a rectangular cross section comprise a stator to improve the driving efficiency by maximizing a coil drip rate. With the increased use of the hairpin motor, there has been an increased interest in manufacturing techniques and automated systems of the hairpin motor. Enamel coating removal is one of the major processes of hairpin motor production; enamel coating at the end of the hairpin should be removed to connect the hundreds of hairpins by using the welding process. Grinding is one of the machining processes used for removing the enamel coating. This study proposed an adaptive control method for the grinding process to improve the efficiency and quality of the enamel coating removal process. Grinding depth is maintained during machining by controlling the vertical position of the spindle based on driving torque. A lab-scale grinding machine including a sensory system for adaptive control is developed and used to verify the performance of the proposed method.
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A Review of Intelligent Machining Process in CNC Machine Tool Systems Joo Sung Yoon, Il-ha Park, Dong Yoon Lee International Journal of Precision Engineering and Manufacturing.2025; 26(9): 2243. CrossRef
Currently digital transformation has a huge impact on human lives. Digital transformation does not just mean a transformation of a (non-) physical element to a digitally identifiable element. It focuses on the utilization of digital technology for transforming (improving) procedures or routines of business and operation. The manufacturing industry has been adopting the most recent digital technology, and lots of digital data are being created. To utilize the stored data, data analysis is essential. Because the manufacturing data is created in a different format at every manufacturing step, the integration of the data is always the bottleneck of the data analysis. Querying of the right data at the proper time is fundamental for high-level data analysis. The digital thread is introduced to provide the inter-reference of digital data based on a context. This paper proposes a digital thread framework for the machining process. The context of the proposed framework consists of the questions of how the product will be machined, how it is (was) being produced, and how it was made. A prototype software was developed to verify the proposed framework by implementing the creating, storing, and querying modules for simulation, monitoring, and inspection data.
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A Review of Intelligent Machining Process in CNC Machine Tool Systems Joo Sung Yoon, Il-ha Park, Dong Yoon Lee International Journal of Precision Engineering and Manufacturing.2025; 26(9): 2243. CrossRef
Titanium alloys are used in various industries due to their superior mechanical strength and corrosion resistance. However, titanium is classified as a difficult-to-machine material due to its low thermal conductivity that consequently causes poor tool life. In this study, cryogenic+MQL milling was performed to improve the machinability of Ti-6Al-4V; a cryogenic coolant and a minimum quantity fluid were sprayed simultaneously. The machinability was analyzed according to the cooling and lubrication conditions, focusing on the cutting force and tool wear. When the minimum quantity fluid was injected using two nozzles during cryogenic machining, the cutting force remained low despite the increase in machining distance due to the effective lubrication. The average cutting force at the long machining distances (82-86 passes) was 14.8% lower than that under the wet condition. The tool wear progressed without chipping, and the flank wear length was 55.5% lower than that of the wet machining because the cryogenic cooling and minimum quantity lubrication reduced the tool temperature, friction, and thermal shock.
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Design and Development of a Real-Time AI-Based Tool Failure Prediction System for Machining Difficult-to-Cut Materials Mi-Ru Kim, Hoon-Hee Lee, Min-Suk Park, Wang-Ho Yun Journal of the Korean Society of Manufacturing Technology Engineers.2025; 34(4): 225. CrossRef
In a pilot natural super-hydrophobic surfaces study, a super-hydrophobic surface was made by coating, etching, laser ablation, chemical vapor deposition and lithography. In this study, cone-shaped periodic micro and nano-structures were constructed on a silica surface with femtosecond and picosecond laser, and the period of micro-structures between cone shape patterns was increased with 10 μm intervals. The contact angle and image of the super-hydrophobic surface were analysed and the cone (Aspect-ratio 1.27) shape model with micro-protrusion structure similar to the surface of the lotus leaf was made to measure the contact angle. To analyse the differences in the contact angles between the cone shapes and heights of the micro-protrusion, different samples with cone (Aspect-ratio 1.27), sphere (Aspect-ratio 1.00) shapes were made through laser micro-machining technology. To mimick the natural lotus leaves, the optimum condition was a cone shape. Samples of PDMS with different shapes and mixed micro/nano-structures were fabricated with a PDMS mold insert. The largest contact angle was measured at 170.42° which is similar to the contact angle of the lotus leaf. This mold insert could be used repeatedly. The molding process is advantageous for large areas and mass production.
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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
CFRP (Carbon Fiber Reinforced Plastic) is a composite material formed using carbon fibers and epoxy resin matrices. It has low productivity and suffers from machining defects during precision machining. Laser machining of CFRP is associated with the problem of heat damage to the epoxy resin. EDM of CFRP can process various shapes with a shaped tool, however it has a lower material removal rate compared to laser, and the non-conductive epoxy resin layer on the surface must be removed before EDM processing. In this study, we have proposed a laser EDM hybrid machining in which CFRP was pre-processed with a laser and then post-processed by EDM. The laser pre-processing conditions were selected by adjusting the laser power and the number of repetitions to minimize thermal damage. According to EDM conditions, the size of the thermal damage area occurring in the epoxy resin, the change in the side gap, and the change in the processing time were investigated. Using the hybrid processing, micro-holes with a diameter of 150 μm were machined, and square-shaped micro-holes were also machined. To improve productivity, a multi-tool capable of processing four square shapes was manufactured, and multi-processing was performed.
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Fabrication of micro holes with confined pitting corrosion by laser and electrochemical machining: Pitting corrosion formation mechanisms and protection method Jian Yang, Yufeng Wang, Yong Yang, Yunfeng Liu, Wenwu Zhang Journal of Materials Processing Technology.2025; 335: 118677. CrossRef
Laser Drilling of Micro-Hole Array on CFRP Using Nanosecond Pulsed Fiber Laser Do Kwan Chung Journal of the Korean Society of Manufacturing Process Engineers.2024; 23(5): 92. CrossRef
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