• Laser Solutions
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• v.13 no.3
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• pp.1-6
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• 2010

The in-process monitoring of $CO_2$ welding of Zn-coated steel plates has been studied and compared with that of conventional thin plates. Relationships between weld defects and plasma emission signals were evaluated in laser lap joint of thick Zn-coated steel. According to the study, weld defects were found to increase with Zn content. As a result, measured plasma emission signals also decreased. In case of plate with $15{\mu}m$-thick Zn-coated layer, defects caused by evaporation of Zn could, therfore, controled by gap of 0.1mm, resulting in a stable emission signals. However, the amplitude of signals fluctuated very widely. Variation of amplitude sould be limited in 3-8V by FFT smoothing.

• Journal of Korean Society of Steel Construction
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• v.16 no.1 s.68
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• pp.43-49
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• 2004

With building structures becoming higher and having longer spans, new structural steel with better strength, thicker plate, and performance may be required rather than conventional structural steel. TMC steel is widely used in building structures largely due to its excellent seismic performance, superior weldability, and design strength that is not affected by plate thickness. To make use of TMC steel in pipe structures with large diameter and heavy wall, however, the this study, the degradation of material properties in submerged are welded SM520TMC steel pipes and tubes was evaluated using variable fabrication process and material change. Degradation test results showed that the yield and ultimate strength increased and elongation decreased regardless of the mode of fabrication, i.e., through roll bending or press forming, or steel used, i.e., domestic SM520TMC steel or SM520TMC steel from Japan.

• Journal of Korean Society for Quality Management
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• v.31 no.1
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• pp.123-131
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• 2003

This paper considers a six sigma project for reducing the defects rate of the welding process in manufacturing firms. The project follows a disciplined process of five macro phases. define, measure, analyze, improve and control(DMAIC). The need of customers is used to identify critical to quality(CTQ) of project. And a process map is used to identify process input factors of CTQ. Four key process input factors are selected by using an input factor evaluation of teams; an interval of welding, an abrasion, an electric current and a moving freely. DOE is utilized for finding the optimal process conditions of the three key process input factors. Another one key input factor improved to welding machine. The six sigma level of defects rate becomes a 2.01 from a 1.61 at the beginning of the project.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.937-942
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• 2000

This paper describes for applications of neural networks in the field of arc welding. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current and the torch travel speed. The relationship between the welding parameters and weld quality is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other - changing the welding current will affect the arc voltage, and so on. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.369-373
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• 2001

In this paper, we proposes the steps adopted to construct the neural network model for GMAW welds. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters are influenced by numerous factors, such as welding current, arc voltage, torch travel speed, electrode condition and shielding gas type and flow rate etc. In traditional work, the structural mathematical models have been used to represent this relationship. Contrary to the traditional model method, neural network models are based on non-parametric modeling techniques. For the welding process modeling, the non-linearity at well as the coupled input characteristics makes it apparent that the neural network is probably the most suitable candidate for this task. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.166-166
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• 2000

This paper describes for applications of neural networks in the field of arc welding. Conventional, automated process generally involves sophisticated sensing and control techniques applied to various processing parameters. Welding parameters affecting quality include the arc voltage, the welding current and the torch travel speed. The relationship between the welding parameters and weld qualify is not a direct one, and in addition, the effect of the weld parameter variables are not independent of the each other - changing the welding current will affect the arc voltage, and so on. Finally, a suitable proposal to improve the construction of the model has also been presented in the paper.

• Journal of Welding and Joining
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• v.30 no.5
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• pp.27-33
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• 2012

Friction stir processing (FSP), developed based on the basic principles of friction stir welding(FSW), a solid-state joining process originally developed for various metal alloys, is an emergingmetalworking technique that can provide localized modification and control of microstructures in near-surface layers of processed metallic components. The FSP causes intense plastic deformation, material mixing, and thermal exposure, resulting in significant microstructural refinement, densification, and homogeneity of the processed zone. The FSP technique has been successfully used for producing the fine-grained structure and surface composite, modifying the microstructure of materials, and synthesizing the composite and intermetallic compound in situ. In this review article, the current state of the understanding and development of FSP is addressed.

• Journal of the KSME
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• v.57 no.11
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• pp.44-49
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• 2017

항공용 가스터빈엔진 개발은 전문성과 경험을 요하는 많은 요소기술과 시험설비, 그리고 상당한 개발기간과 세부단계별 검증을 필요로 하는 복잡한 프로세스로 구성된다. 고온/고압 및 고속 회전 등 매우 가혹한 조건에서 운용되는 제품 특성 때문에 장납기 및 고가의 내열/고강도 소재 혹은 주단조 개발, 정밀한 제작 치수 및 공정관리, 코팅/브레이징/용접 등 고 난이도의 특수공정관리, 정교한 조립 및 다양한 종류의 엔진 검증 시험 등을 필요로 하며 이러한 이유로 상세설계 이후의 조립/시험 단계에서 설계변경이 발생할 경우 개발일정 및 비용 관점에서 제품개발에 큰 부담을 초래하게 된다. 공력/이차유로/열전달/구조/동특성/시스템 설계 등 개발 단계별 다양한 기법의 시뮬레이션 및 사전 검증시험 등의 중요성이 크게 부각된다. 이 글에서는 한화테크윈(혹은 HTW 로 표기)의 엔진개발 경험에 기반한 단계별 개발 시험의 종류, 필요 시험 설비 및 한화테크윈의 설비 운용 특징에 대해 소개하고자 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.794-801
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• 2021

This study examined the mechanical strength and corrosion resistance of a dissimilar joint with an aluminum alloy and steel by resistance element spot welding. SPFC980 steels and Al5052 alloys were applied as the base materials. S20C steels were assembled on Al5052 for the riveting element before the electric resistance welding process. The SPFC980-S20C riveted Al5052 was welded at a 6.5 kA current and 250 kgf/㎠. As a result, the engraved S20C elements formed unstable nuggets after the spot welding processes. In contrast, in the embossed S20C elements, exceptional mechanical properties, such as robust corrosion resistance and fatigue resistance, were obtained by structurally sound joints. The correlation between the microstructure and mechanical properties were examined by microstructural investigations and FEM simulations. The corrosion reliability of element spot-welded SPFC980-Al5052 dissimilar joints was investigated systematically.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.73-73
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• 2009

In this sutdy, a new class ACA(Anisotropic Conductive Adhesive) with low-melting-point alloy(LMPA) and self-organized interconnection method were developed. This developed self-organized interconnection method are achieved by the flow, melting, coalescence and wetting characteristics of the LMPA fillers in ACA. In order to observe self-interconnection characteristic, the QFP($14{\times}14{\times}2.7mm$ size and 1mm lead pitch) was used. Thermal characteristic of the ACA and temperature-dependant viscosity characteristics of the polymer were observed by differential scanning calorimetry(DSC) and torsional parallel rheometer, respectively. A electrical and mechanical characteristics of QFP bonding were measured using multimeter and pull tester, respectively. Wetting and coalescence characteristics of LMPA filler particles and morphology of conduction path were observed by microfocus X-ray inspection systems and cross-sectional optical microscope. As a result, the developed self-organized interconnection method has a good electrical characteristic($2.41m{\Omega}$) and bonding strength(17.19N) by metallurgical interconnection of molten solder particles in ACA.