• Laser Solutions
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• v.6 no.1
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• pp.9-16
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• 2003

Micromachining using the DPSS 3rd Harmonic Laser (355nm) has outstanding advantages as a UV source in comparison with Excimer lasers in various aspects such as maintenance cost, maskless machining, high repetition rate and so on. It also has the greater absorptivity of many materials in contrast to other IR sources. In this paper, the process for micro-drilling of blind hole in Cu/PI/Cu substrate with the DPSS UV laser and the scanning device is investigated by the experimental methods. It is known that there is a large gap between the ablation threshold of copper and that of PI. We use the Archimedes spiral path for the blind hole with different energy densities to ablate the different material. Finally, the blind via hole of diameter 100$\mu\textrm{m}$ and 50$\mu\textrm{m}$ was drilled.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.3
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• pp.133-140
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• 2004

Recently reduction of industrial products in size and weight has been increased by application of micro-drills in gadgets of high precision and a great interest of a micro-drilling has been raised. Due to the lack of tool stiffness and the chip packing, the micro-drilling requires not only the robust tool structure which has not affected by vibration but also effective drilling methods designed to prevent tool fracture from cutting troubles. This paper presents an optimum design shape of a 0.15 mm micro-drill associated with a new manufacturing process to improve the production rate and to lengthen the tool life and suggestions on the micro-drilling characteristic properties associated with the tool life and workpiece quality.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.993-998
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• 2002

watches, air bearings and printed circuit hoards (PCB). However, it is not easy to determine optimum cutting conditions since the micro drilling process is very sensitive to various disturbances. Also, undesirable characteristics to optimize the micro drilling are small signal-to-noise ratios, drill wandering motions and high aspect ratios. Thus, in this study, experimental design methods are applied to determine optimum cutting conditions. Suing the methods, three cutting parameters, fred, step and curving speed are optimized to minimize thrust forces. Obtained conditions are verified through required experimental works. As the results, it is shown that the experimental methods can be applied to micro drilling processes to determine Optimum Cutting Conditions.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.71-78
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• 2003

The exit burrs in the micro-drilling of precision miniature holes are of interest, especially for ductile materials. As burrs from this process can be difficult to remove, it is important to acquire the way of predicting burr types as well as optimal cutting conditions which minimize the burrs. In this paper, an artificial neural network was used for the prediction of burr formation in micro-drilling. First, the influence of cutting conditions including cutting speed, feed and drill diameter on the exit burr characteristics, such as burr size and type, were observed and analyzed. Then. the burr types were classified by using the influential experimental data as input parameters to the neural nets.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.12
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• pp.2475-2482
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• 2002

The measurement of residual stresses by the hole-drilling method has been commonly used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, the error due to the hole eccentricity is compensated using the neural network. The neural network has trained training examples of normalized eccentricity, eccentric direction and direction of maximum stress at eccentric case using backpropagation learning process. The trained neural network could compensated the error of measured residual stress in experiments with hole eccentricity. The proposed neural network is very useful for compensation of the error due to hole eccentricity in hole-drilling method.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.412-418
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• 2001

The measurement of residual stresses by the hole-drilling method has been commonly used to evaluate residual stresses in structural members. In this method, eccentricity can usually occur between the hole center and rosette gage center. In this study, the error due to the hole eccentricity is corrected using the neural network. The neural network has trained training examples of normalized eccentricity, eccentric direction and direction of maximum stress at eccentric case using backpropagation learning process. The trained neural network could corrected the error of measured residual stress in experiments with hole eccentricity. The proposed neural network is very useful for correction of the error due to hole eccentricity in hole-drilling method.

• Laser Solutions
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• v.10 no.3
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• pp.11-14
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• 2007

A trepanning optics is the optical system which makes focus laser beam rotate and incline to the material processing surface. The trepanning optics is used in order to improve the quality of laser drilling process and control the taper of drilling diameter. In order to make trepanning optics, we can use the eccentricity of lens, scanner using two mirror, dove prism, or wedge. Among these method, in this paper wedge is used for trepanning optics. The wedge trepanning optics has advantage on the high speed of rotation. In this paper, we design the wedge trepanning optics using ray tracing. ements and engine design variables of system to satisfy the customer's requirements.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.2
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• pp.103-111
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• 2002

Out of all metal-cutting process, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. There are two systems, Basic system and Online system, to detect the drill wear. Basic system comprised of spindle rotational speed, feed rates, thrust torque and flank wear measured by tool microscope. Outline system comprised of spindle rotational speed feed rates, AE signal, flank wear area measured by computer vision, On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. The output was the drill wear state which was either usable or failure. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.4
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• pp.561-571
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• 2019

Drilling and charging of the blast holes during NATM tunneling works take more than 30% of construction time among the whole tunneling work process. Prediction of ground condition ahead of tunnel face has been studied by several researchers by correlating percussion pressure and drilling speed during tunneling work with the ground condition and/or RMR values. However, most of the previous researches were conducted in the granite rock condition which is the most representative igneous rock in the Korean peninsula. In this study, drilling speeds in igneous rocks were analyzed and compared with those in sedimentary rocks (most dominantly composed of conglomerates, sandstones, and shales) under the similar RMR ranges; it was identified that the drilling speed is pretty much affected by rock types even in a similar RMR range. Under the similar RMR values, the drilling speed was faster in sedimentary rocks compared with that in igneous rock. Moreover, while the drilling speed was not much affected by change of the RMR values in igneous rocks, it became faster in sedimentary rocks as the RMR values got lower.

• Structural Engineering and Mechanics
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• v.80 no.5
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• pp.503-522
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• 2021

This paper investigates experimentally and numerically the influence of drilling process on the mechanical and thermomechanical behaviors of woven glass fiber reinforced polymer (GFRP) composite plate. Through the experimental analysis, a CNC machine with cemented carbide drill (point angles 𝜙=118° and 6 mm diameter) was used to drill a woven GFRP laminated squared plate with a length of 36.6 mm and different thicknesses. A produced temperature during drilling "heat affected zone (HAZ)" was measured by two different procedures using thermal IR camera and thermocouples. A thrust force and cutting torque were measured by a Kistler 9272 dynamometer. The delamination factors were evaluated by the image processing technique. Finite element model (FEM) has been developed by using LS-Dyna to simulate the drilling processing and validate the thrust force and torque with those obtained by experimental technique. It is found that, the present finite element model has the capability to predict the force and torque efficiently at various drilling conditions. Numerical parametric analysis is presented to illustrate the influences of the speeding up, coefficient of friction, element type, and mass scaling effects on the calculated thrust force, torque and calculation's cost. It is found that, the cutting time can be adjusted by drilling parameters (feed, speed, and specimen thickness) to control the induced temperature and thus, the force, torque and delamination factor in drilling GFRP composites. The delamination of woven GFRP is accompanied with edge chipping, spalling, and uncut fibers.