• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.422-428
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• 2001

The term High Speed Machining has been used for many years to describe end milling with small diameter tools at high rotational speeds, typically 10,000 - 100,000 rpm. The process was applied in the aerospace industry for the machining of light alloys, notably aluminium. In recent year, however, the mold and die industry has begun to use the technology for the production of components, including those manufactured from hardened tool steels. With increasing cutting speed used in modern machining operation, the thermal aspects of cutting become more and more important. It not only directly influences in rate of tool wear, but also will affect machining precision recognized as thermal expansion and the roughness of the surface finish. Hence, one needs to accurately evaluate the rate of cutting heat generation and temperature distributions on the machining surface. To overcome the heat generation, we used to cutting fluid. Cutting fluid play a roles in metal cutting process. Mechanically coupled effectiveness of cutting fluids affect to friction coefficient at tool-work-piece interface and cutting temperature and chip control, surface finish, tool wear and form accuracy. Through this study, we examined the behavior of heat generation in high-speed machining and the cooling performance of various cooling methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.452-455
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• 2005

The cutting characteristics of hardened steel by a PCBN tool is investigated with respect to workpiece surface roughness, cutting force and tool flank wear of the vision system. Backpropagation neural networks (BPNs) were used for detection of tool wear. The neural network consisted of three layers: input, hidden and output. The input vectors comprised of spindle rotational speed, feed rates, vision flank wear, and thrust force signals. The output was the tool wear state which was either usable or failure. Hard turning experiments with various spindle rotational speed and feed rates were carried out. The learning process was performed effectively by utilizing backpropagation. The detection of the abnormal states using BPNs achieved 96.4% reliability even when the spindle rotational speed and feedrate were changed.

• Fashion & Textile Research Journal
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• v.12 no.6
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• pp.821-829
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• 2010

The men's costume of eighteenth century showed feminine image of elegant decoration through the influence of social feminine atmosphere. As years go, heading towards the end of the eighteenth century, most of men's wear were simplified except vest, which had gorgeous decorations showing feminity. Therefore, men's vest of eighteenth was regarded as good item to apply to modern women's wear. The men's vest design of eighteenth century were divided into three types due to the passage of time, they showed the difference in the length, detail and trimming. Cutting lines in the modern fashion are used to give comfort and show the three-dimensional body silhouette. Also, cutting lines, as a decoration element, can define the costume's image and characteristics. Therefore, by using cutting lines, we can represent historical costume as modern costume and men's wear as women's wear. I made five women's costumes applying design characteristics of the men's vest of the eighteenth century. These five women's costumes have decorative aspect of men's vest of eighteenth century and simple aspect of men's costume. I applied dart manipulation in several different ways to make various cutting lines for women's costume. These cutting lines were emphasized by matching various colors and patterns of fabrics. I made small buttons and cords of these various fabrics. I sewed fabric buttons on five costumes for the purpose of function and decoration like buttons of the men's vest of eighteenth century. I applied fabric cords to decorate five costumes in various way. We should further study how to express important characteristics of historical costumes as modern costume in many ways.

• Journal of the Korean institute of surface engineering
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• v.41 no.6
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• pp.335-340
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• 2008

Cutting performance and wear behavior were studied with the diamond micro-blade of Cu/Sn bond materials containing various amount of lubricant materials such as graphite and $MoS_2$. Measurement of instantaneous electric power consumption for cutting glass workpiece at the constant velocity was conducted and proposed as a method to assess cutting efficiency. The energy consumption of micro-blade for glass cutting decreased with the content of graphite and $MoS_2$ while wear amount of blade in volume increased with the amount of lubricant addition during the dicing test. It is because that hardness, flexural strength, and fracture toughness ($K_{IC}$) reduced with the amount of lubricant addition. Blades with $MoS_2$ additive showed higher mechanical properties than those with graphite additives when the same amount of the lubricant additive in wt.% was added. Due to the lower density of graphite than $MoS_2$, higher volume fraction of graphite could result in stronger effect on lowering electric power consumption by reducing the friction between blade and work piece however increasing wear rate due to the reduction in strength and fracture toughness. Adhesive wearing mode of micro blade could be remarkably improved by the addition of graphite as well as $MoS_2$.

• Journal of Power System Engineering
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• v.5 no.3
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• pp.73-79
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• 2001

The purpose of this investigation is experimentally to clarify the machinability and tool wear of STS 304 steel pipe material for piping. In order to determine the effects of cutting parameters and tool wear on thrust, torque, AE RMS, drilling is conducted on CNC milling machine. In this experiment, it is measured that thrust, torque, tool wear length, tool wear area and AE RMS during drilling using Hss tool. It has been found that a) During the drilling, the thrust and the torque of the STS 304 pipe are received more the effect of the feed than the spindle speed and the thrust increase with the increase of feed, b) The value of the AE RMS is been larger the effect of the cutting speed than the feed rate, and the value of the AE RMS increase with the increase of spindle speed, c) It has been found that the suitable feed in feed condition of 0.03, 0.05, 0.1, 0.15mm/rev is below 0.05mm/rev, d) The value of the AE RMS was shown a characteristic of the jump value during it was a sudden inrcrease of the tool wear. The increased character of the AE RMS value can be known an effective factor of the tool wear detection, and e) It can be quantitatively evaluated the condition of the tool according to calculate a area of the drill wear image which is obtained by a vision system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.1021-1024
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• 2001

Out of all metal-cutting processes, 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. In this paper, the vision system of the sensing methods of drill flank wear on the basis of image processing is used to detect the wear pattern by non-contact and direct method and get the reliable wear information about drill. In image processing of acquired image, median filter is applied for noise removal. The vision flank wear area of the drill was measured. Backpropagation neural networks (BPns) were used for no-line detection of drill wear. The neural network consisted of three layers: input, hidden and output. The input vectors comprised of spindle rotational speed, feed rates, vision flank wear, thrust and torque signals. The output was the drill wear state which was either usable or failure. Drilling experiments with various spindle rotational speed and feed rates were carried out. The learning process was peformed effectively by utilizing backpropagation. The detection of the abnormal states using BPNs achieved 96.4% reliability even when the spindle rotational speed and feedrate were changed.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.5
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• pp.223-230
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• 1996

The quality and productivity in machining automobile parts are influenced by various factors such as cutting conditions, vibration, and used tool. To improve the quality and productivity of the automobile parts(torsion beam), lots of research on the evaluation of tool life and control of surface roughness has been required. Therefore, the width of flank wear, cutting force, and surface roughness are monitored to analyse the characteristics of tool wear and surface roughness at different tools. This experimental investigation is mainly focused on the characteristics of the tool wear, tool life and surface roughness in multi-insert milling of automobile parts(torsion beam) by using uncoated tungsten carbide tool(WC), TiN coated tool, and cermet tool.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.3
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• pp.254-262
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• 2008

The objective of the proposed study is to produce a tool-condition monitoring (TCM) strategy that will lead to a more efficient and economical drilling tool usage. Drill-wear monitoring is an important attribute in the automatic cutting processes as it can help preventing damages of the tools and workpieces and optimizing the tool usage. This study presents the architectures of a multi-layer feed-forward neural network with back-propagation training algorithm for the monitoring of drill wear. The input features to the neural networks were extracted from the AE signals using the wavelet transform analysis. Training and testing were performed under a moderate range of cutting conditions in the dry drilling of steel plates. The results indicated that the extracted input features from AE signals to the supervised neural networks were effective for drill wear monitoring and the output of the neural networks could be utilized for the tool life management planning.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.1
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• pp.53-59
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• 2011

End milling is available for machining the various shape of products and has been widely applied in many manufacturing industries. The quality of products depends on a machine tool performance and machining conditions. Recognition characteristics of the cutting condition is becoming a critical requirement for improving the utilization and flexibility of present-day CNC machine tools. The measurement of tool wear would be performed by coordinate-measuring machine(CMM). However, the usage of CMM requires much time and cost. In order to overcome the difficulties, on-line measurement(OLM) system was applied for a tool wear measurement. This study shows a reliable technique for the reduction of machining error components by developing a system using a CCD camera and machine vision to be able to precisely measure the size of tool wear in flat end milling for CNC machining. The CCD camera and machine vision attached to a CNC machine can determine tool wear quickly and easily.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.209-214
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• 2002

Mechanical micro-engineering is an easy and cheap way to fabricate micro-structures. If the application of the conventional machining method using flat-end mill becomes available for the micro-manufacturing process, it will be advanced as an extension of the conventional machining process. In this study, micro-grooves cutting using flat-end mill(($\phi$8) was performed. The characteristics on flat-end milling was investigated to improve machinability of micro-grooves. The experiments were performed according to variations of spindle revolution, depth of cut, and feed rate. Machinability through various cutting conditions was evaluated by surface geometry, tool wear, and cutting force. The results show that micro V-grooves of width(pitch) 29${\mu}{\textrm}{m}$ were acquired by flat-end milling. The maximum and minimum roughness of the wall of grooves was 438 and 67nm, respectively