• 한국분말재료학회지
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• 제14권6호
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• pp.367-371
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• 2007

P/M high speed steel (1.26% C, 4.42% Cr, 6.54% W, 4.92% Mo, 3.21 % V, 8.77% Co, bal. Fe) was applied to hot former die. It showed that the die life became 2.7 times higher than that of cast/wrought SKH 55 tool steel which is commercially used. The increase of die life was corresponding to the improved hardness and transverse rupture strength of PM high speed steel due to the finer grain and carbide as well as the uniform carbide distribution. The P/M high speed steel with the promoted die life could be an alternative to the conventional SKH55.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2007년도 추계학술대회 논문집
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• pp.116-119
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• 2007

The application of light weight materials, such as aluminum alloy, has been limited due of their poor formability. Especially, aluminum alloy tube has limited expansion capability at most 15% at room temperature. New manufacturing process, called hot air forming, is introduced to apply aluminum tube to the automotive suspension components which have complex shape and require high expansion ratio about 40%. The process is carried out at the elevated temperature above $500^{\circ}C$, so numerous material properties and process parameters related to the high temperature should be investigated and determined to get a sound product. In this study, the effect of thermal properties and forming parameters such as the temperature of tool, axial feeding and gas pressure are analyzed by using explicit finite element method.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 추계학술대회 논문집
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• pp.41-46
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• 2002

In the face of global competition, the requirements fer the continuously increasing productivity, flexibility and quality (dimensional accuracy, mechanical properties and surface properties) have imposed a major change on steel manufacturing industries. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. To achieve this objectives, a new loaming method with neural network to improve the accuracy of rolling force prediction in hot rolling mill is developed. Also, Genetic Algorithm(GA) is applied to select the optimal structure of the neural network and compared with that of engineers experience. It is shown from this research that both structure selection methods can lead to similar results.

• 대한기계학회논문집A
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• 제25권12호
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• pp.1944-1949
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• 2001

Four SiC-Si$_3$N$_4$ceramic cutting tools with different composition have been fabricated by hot-pressing. Correlations among the annealing time, the corresponding microstructure and the mechanical properties of resulting ceramics have been investigated. The fracture toughness and the grain size of both SiC and Si$_3$N$_4$in SiC-Si$_3$N$_4$composites increased with the annealing time. 1\`he hardness of SiC-Si$_3$N$_4$composites was relatively independent of the grain size and the sintered density. These ceramic cutting tools were tested under various cutting conditions and compared with the commercial Si$_3$N$_4$ceramic cutting tools. The experimental results were compared in terms of tool life and cutting force. The performance of SiC-Si$_3$N$_4$ceramic cutting tool shows the possibility to be a new ceramic tool.

• 한국공작기계학회논문집
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• 제10권6호
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• pp.78-84
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• 2001

In the present study, SiCSi-$Si_3 N_4$-SiC ceramic composites that contained up to 30 wt% of dispersed SiC particles were fabricat-ed cia hot-pressing with an oxynitride glass. The microstructure, the mechanical properties and the cutting performance of resulting ceramic composites were investigated. By fixing the composition as $Si_3 N_4$-20wf%SiC, the effect of sintering time on the microstructure, the mechanical properties and the cutting performance were also investigated. The longer sir-tering time is, the bigger the grain size of SiC is. The fracture toughness(-$K_k$) of the $Si_3 N_4$-SiC ceramic composites increased with the increase of gain size, while the flexural strengthh($\sigma$) decreased. For machining SCM440, the insert with 20wt%r SiC sintered for 8 hours showed the longest tool life while the insert with 20wt% SiC sintered for 12 hours showed the longest tool life for machining gray cast iron.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2008년도 추계학술대회 논문집
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• pp.26-29
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• 2008

Recently, the hydroforming of high strength aluminum tubes has many studies and applications in manufacturing industry, especially in automotive industry. But high strength aluminum tube has limited expansion capability at most 15% at normal temperature. New manufacturing process, called hot air forming, is introduced to apply aluminum tube to the automotive sub frame components which have complex shape and require high expansion ratio about 40%. The process is carried out at the elevated temperature above $500^{\circ}C$, so numerous material properties and process parameters related to high temperature should be investigated and determined to get a sound product. In this paper, the hot air forming process of automotive sub frame was investigated. The effect of the forming parameters such as the temperature of tool, axial feeding and gas pressure are analyzes by using explicit finite element method.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.368-373
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• 2003

A major concern at present is the simultaneous control of transverse thickness profile and flatness in the finishing stages of hot rolling process. The mathematical modeling of hot rolling process has long been recognized to be a desirable approach to investigate rolling operating practice and the design of mill equipment to improve productivity and quality. However, many factors make the mathematical analysis of the rolling process very complex and time-consuming. In order to overcome these problems and to obtain an accurate rolling force, the predicted model of rolling force using neural networks has widely been employed. In this paper, Radial Basis Function Network(RBFN) is applied to improve the accuracy of rolling force prediction in hot rolling mill. In order to verify and analysis the performance of applied neural network, the comparison with the measured rolling force and the predicted results using two different neural networks - RBFN, MLP, has respectively been carried out. The results obtained using RBFN neural network are much more accurate those obtained the MLP.

• 한국공작기계학회논문집
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• 제13권6호
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• pp.29-33
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• 2004

A major concern at present is the simultaneous control of transverse thickness profile and flatness in the finishing stages of hot rolling process. The mathematical modeling of hot rolling process has long been recognized to be a desirable approach to investigate rolling operating practice and the design of mill equipment to improve productivity and quality. However, many factors make the mathematical analysis of the rolling process very complex and time-consuming. In order to overcome these problems and to obtain an accurate rolling force, the predicted model of rolling force using neural networks has widely been employed. In this paper, Radial Basis Function Network(RBFN) is applied to improve the accuracy of rolling force prediction in hot rolling mill. In order to verify and analyze the performance of applied neural network the comparison with the measured rolling force and the predicted results using two different neural networks-RBFN, MLP, has respectively been carried out. The results obtained using RBFN neural network are much more accurate those obtained the MLP.

• 한국시뮬레이션학회논문지
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• 제22권4호
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• pp.93-98
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• 2013

본 논문에서는, 초고집적과 초고내압 MOSFET를 위한 높은 임계전압에서 제안한 구조의 얕은 트랜치 접합 격리 구조에 대한 시뮬레이션 하였다. 열전자 스트레스와 열 손상의 유전 강화 전계의 물리적 기본 모델들은 주위 온도와 스트레스 바이어스의 넓은 범위에 걸친 집적화된 소자들에 있어서 분석하는 전기적의 목표인 TCAD 툴을 이용하였다. 시뮬레이션 결과, 얕은 트랜치 접합 격리 구조가 수동적인 전기적 기능 일지라도, 소자의 크기가 감소됨에 따라서, 초대규모 집적회로 공정의 응용에서 제안된 얕은 트랜치 격리 구조가 전기적 특성에서 전위차, 전계와 포화 임계 전압이 높게 나타났다.

• 동의생리병리학회지
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• 제30권6호
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• pp.376-384
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• 2016

Systems biology is an emerging field aiming at a systems level understanding of living organisms and focusing on the characteristics of the whole network of them. The emergence of systems biology is partly because of the availability of huge amounts of data on organisms and the extensive support of computational technologies as the tools for understanding complex biological systems. The scientific understanding of Korean medicine has been obstructed because of the lack of proper methods examining the complex nature and the unique property of it. However, systems biology could give a chance understanding Korean medicine objectively and scientifically. Pattern classification is a unique tool of Korean medicine to diagnose and treat patients and systems biology would give a useful tool to interpret pattern classification. Various omics technologies has been used to explain the relations between pattern classification and biological factors and then many characteristics of pattern classification in various diseases have been discovered. Therefore, pattern classification could be a bridge to understand the features and differences of western medicine and Korean medicine and it could be a basis to develop pattern-based personalized medicine.