• 한국공작기계학회논문집
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• 제11권2호
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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.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.821-826
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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. One important aspect in controlling the drilling process is monitoring drill wear status. Accordingly, this paper deals with Basic system and Online system. Basic system comprised of spindle rotational speed, feed rates, thrust, torque and flank wear measured tool microscope. Online system comprised of spindle rotational speed, feed rates, AE signal, flank wear area measured 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. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

• 대한기계학회논문집
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• 제12권6호
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• pp.1290-1295
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• 1988

본 연구에서는 공구마멸에 대한 정량적인 해석을 바탕으로 현대 산업사회의 주요소재인 강(steel)에 대한 최적 공구재를 선정하는 방법을 제시하므로서 앞으로의 공구재 개발에 대한 이론적인 접근을 시도하였다.

• 한국정밀공학회지
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• 제16권1호통권94호
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• pp.174-181
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• 1999

In this paper the technique to predict tool wear theoretically in shearing process is suggested. The tool wear in the process affects the tolerances of final pans, metal flows and costs of processes. In order to predict the tool wear the deformation of workpiece during the process is analyzed by using non-isothermal finite element program. The ductile fracture criterion and the element kill method are also used to estimate if and where a fracture will occur and to investigate the features of the sheared surface in shearing process. Results obtained from finite element simulation, such as nodal velocities and nodal forces, are transformed into sliding velocity and normal pressure on tool monitoring points respectively. The monitoring points are automatically generated and the wear rates on these points are accumulated during the process. It is assumed that the wear depth on the tool surface is linear function of the lot sizes based upon the known experimental results. The influence of clearance between die and punch upon tool wear is also discussed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.67-72
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• 1994

Tool test was conducted to investigate the were process of only flank face TiN coated HSS tool in interrupted cutting for variuos cutting speeds and feed rates. Flank wear was caused by microchipping at the cutting edge. At high cutting speed, the which was formed as a result of diffusion and abrasion lowered cutting edge and influenced flank were. Flank wear due to chipping was little influenced by cutting speed.

• 한국공작기계학회논문집
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• 제14권6호
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• pp.16-21
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• 2005

The cutting characteristics of hardened steel(AISI 52100) by PCBN tools is investigated with respect to cutting force, workpiece surface roughness and tool flank wear by the vision system. Hard Owning is carried out with various cutting conditions; spindle rotational speed, depth of cut and feed rate. Backpropagation neural networks(BPNs) are used for detection of tool wear. The input vectors of neural network comprise of spindle rotational speed, feed rates, vision flank wear, and thrust force signals. The output is the tool wear state which is either usable or failure. The detection of the abnormal states using BPNs achieves $96.8\%$ reliability even when the spindle rotational speed and feedrate are changed.

• Tribology and Lubricants
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• 제32권6호
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• pp.195-200
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• 2016

This study examines the wear behavior of mild steel pins mated against alloyed tool steel discs in a pin-on-disc type sliding test machine and provides specific clarification regarding the effects of disc hardness on the wear behavior of a mating mild steel pin. The analysis confirms these effects through the observation of differences in the wear rates of the mild steel pins at low sliding speed ranges. These differences occur even though the hardness of the mating disc does not affect the wear characteristic curve patterns for the sliding speeds, regardless of the wear regime. In the running-in wear regime, increasing the hardness of the mating disc results in a decrease in the wear rates of the mild steel pins at low sliding speed ranges. However, in the steady-state wear region, the wear rate of a pin mated against the 42DISC is greater than the wear rate of a pin mated against the 30DISC, which has a lower hardness value. This means that the tribochemical reactivity of the mating disc, which is based on hardness value, influences the wear behavior of mild steel at low sliding speed ranges. In particular, oxides with higher oxygen contents, such as $Fe_2O_3$ oxides, form predominantly on the worn surface of the 42DISC. On the contrary, the wear behavior of mild steel pins at high sliding speed ranges is nearly unaffected by the hardness of the mating disc.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1997년도 추계학술대회 논문집
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• pp.43-47
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• 1997

Advances in EDM power supplies have made the process competitive in some areas dominated by conventional and numerically controlled machines. This paper will produce more comprehensive data than are presently available and will use this data in applying concepts of optimization based on manufacturer's guide lines utilizing neural networks. A method will be developed for determining the machining parameters of the EDM process considering the conflicting desirability of good surface finish, low tool wear and high rates of metal removal. By the proposed method, one can select machining parameters that can maintain permissible tool wear and obtain maximum machining rates on the system represented by the data.

• 한국자동차공학회논문집
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• 제24권1호
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• pp.67-73
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• 2016

The application of titanium has been gradually rising because the utilizing ranges for low weight and high strength are rapidly increased by the need for improving the fuel economy in production industries such as the aviation and automotive in recent. The purpose in this study is to investigate the appropriate cutting conditions on the life of flat and round end mills by measuring the maximum cutting temperature relative to the machining time, and calculating the wear rates of cutting tool with the spindle speed and feed rate of vertical machining center as a parameter in the titanium roughing cut machining which is widely used in critical parts of aircraft, cars, etc. When the wetted roughing cut machining of titanium with a soluble cutting oil is conducted by the flat and round end mills, the maximum cutting temperatures for a variety of spindle speed and feed rate are measured at ten-minute intervals during 60 minutes by an infrared thermometer, and the wear rates of cutting tool are calculated by the weight ratios based on tool wear before and after the experiment. It is found that the maximum cutting temperature and the wear rates of cutting tool are raised as the cutting amount per tool edge is increased with the rise of feed rate, in this experimental range, and as the frictional area due to the rise of contacting friction numbers between tool and specimen is increased with the rises of cutting time and spindle speed. In addition, the increasing rate of maximum cutting temperature in the flat and round end mills are the highest for the cutting time from 50 to 60 minutes, and the wear rate of cutting tool in the flat end mill is 1.14 to 1.55 times higher than that in the round end mill for all experimental conditions.