• 소성∙가공
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• 제28권1호
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• pp.27-33
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• 2019

The effect of hardening methods and process parameters on surface hardening of a Ti-6Al-4V Alloy has been investigated in this study. To characterize the effectiveness of the respective surface hardening methods, samples of a Ti-6Al-4V alloy were self-quenched, laser-nitrided, laser-carburized, laser-carbonitrided at the same laser irradiation conditions. This experimental procedure was followed by comparing the microstructural evolutions and mechanical properties of the respective samples after the laser surface hardenings. The hardening characteristics of the respective laser surface hardenings were well defined in this study, and the hardness was significantly influenced by the reaction compounds and laser energy density.

• 한국재료학회지
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• 제11권11호
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• pp.1001-1005
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• 2001

In this study, the surface of 40Cr steel was hardened by $CO_2$Laser, and then the microstructural transformations and the hardness distributions of the laser surface hardened layer were observed. The experimental results showed the surface hardening layer was consisted of three parts, which is outmost surface layer of needle martensite, middle layer of martensite and remained pearlite, and transitory boundary layer. In hardness distributions, the surface hardeness of the surface hardening layer had Hv 800~1000, that was 2 to 4 times of matrix's hardness. The hardeness distribution of laser hardening layer that of surface layer hardened by general heat treatment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.212-217
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• 1993

In this paper, the hardening depth in Laser surface hardening process is estimated using a multilayered neural network. Input data of the neural network are surface temperature of five points, power and travelling speed of Laser beam. A FDM(finite difference method) is used for modeling the Laser surface hardening process. This model is used to obtain the network's training data sample and to evaluate the performance of the neural network estimator. The simulational results showed that the proposed scheme can be used to estimate the hardening depth on real time.

• 열처리공학회지
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• 제8권1호
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• pp.44-52
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• 1995

The specimen for laser hardening have been carried out using SM45C which is coated with black paint or graphite for better absorption. Segmented mirror was used in order to produce a square beam ($10{\times}10mm$) at the surface with a homegeneous intensity distribution across the beam. $CO_2$-Laser power was changed from 2kW to 4kW and transfer velocity was varied from 0.1m/min to 2.0m/min. The maximum hardness and case depth of SM45C steel are 790Hv and 1.5mm by laser hardening. When the surface of specimens was melted during laser hardening. the surface hardness of SM45C steel was decreased. The surface hardness of 2 layer coated specimen(black paint: $15.4{\mu}m$, graphite coating: $9.5{\mu}m$) was increased than that of 1 layer coated specimen. It is desirable to prepare 2 or more coating layer on the steel surface in order to sufficient case depth and hardness in laser hardening. The graphite coating on the specimen surface was obtained more uniform temperature distribution than black paint coating in laser hardening process.

• 대한기계학회논문집
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• 제19권8호
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• pp.1907-1914
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• 1995

An on-line measurement of the workpiece hardened depth in laser surface hardening processes is very much difficult to achieve, since the hardening process occurs in depth wise direction. In this paper, the hardened depth is estimated using a multilayered neural network. Input data of the neural network are the surface temperatures at arbitrary chosen five surface points, laser power and traveling speed of laser beam torch. To simulate the actual hardening process, a finite difference method(FDM) is used to model the process. Since this model yields the calculation results of the temperature distribution around the workpiece volume in the vicinity of the laser torch, this model is used to obtain the network's training data and laser to evaluate the performance of the neural network estimator. The simulation results show that the proposed scheme can be used to estimate the hardened depth with reasonable accuracy.

• Journal of Welding and Joining
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• 제25권3호
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• pp.78-84
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• 2007

Laser Material Processing has been replaced the conventional machining systems - cutting, drilling, welding and surface modification and so on. Especially, LTH(Laser Transformation Hardening) process is one branch of the laser surface modification process. Conventionally, some techniques like a gas carburizing and nitriding as well as induction and torch heating have been used to harden the carbon steels. But these methods not only request post-machining resulted from a deformation but also have complex processing procedures. Besides, LTH process has some merits as : 1. It is easy to control the case depth because of output(laser power) adjustability. 2. It is able to harden the localized and complicated a.ea and minimize a deformation due to a unique property of a localized heat source. 3. An additional cooling medium is not required due to self quenching. 4. A prominent hardening results can be obtained. This study is related to the surface hardening of the rod-shaped carbon steel applied to the lathe based complex processing mechanism, a basic behavior of surface hardening, hardness distribution and structural characteristics in the hardened zone.

• Journal of Advanced Marine Engineering and Technology
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• 제31권8호
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• pp.961-969
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• 2007

The laser material processing has replaced a conventional material processing such as a welding, cutting, drilling and surface modification and so on. LTH(Laser Transformation Hardening) is one branch of the laser surface modification process. A lot of energy is needed for the LTH process to elevate workpiece surface to temperature of the austenite transformation($A_3$), which results from utilizing a beam with a larger size and lower power intensity comparatively. The absorptivity of the laser energy with respect to material depends on the wave length of a beam. This study is related to the surface hardening for the rod-shaped carbon steel by the high power diode laser(HPDL) whose beam absorptivity is better than conventional types of lasers such as $CO_2$ or Nd:YAG laser. Because a beam proceeds on the rotating specimen the pretreated hardened-phase can be tempered and softened by the overlapping between hardened tracks. Accordingly, the longitudinal hardness measurement and observation of the micro structure was carried out for an assessment of the hardening characteristics. In addition, a hardening characteristics as a hardenability of materials was compared in the point of view of the hardness distribution and hardening depth and width.

• 한국레이저가공학회지
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• 제11권4호
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• pp.7-12
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• 2008

Laser Transformation Hardening(LTH) is one branch of the laser surface modification processes. A lot of energy is needed for the LTH process to elevate workpiece surface to temperature of the austenite transformation($A_3$), which results from utilizing a beam with a larger size and lower power density comparatively. This study is related to the surface hardening for the rod-shaped carbon steel by the high power diode laser whose beam absorptivity is better than conventional types of lasers such as $CO_2$ or Nd:YAG laser. Because a beam proceeds on the rotating specimen, the pretreated hardened-phase can be tempered and softened by the overlapping between hardened tracks. Accordingly, the longitudinal hardness measurement and observation of the micro structure was carried out for an assessment of the hardening characteristics. In addition, a hardening characteristics as a hardenability of materials was compared in the point of view of the hardness distribution and hardening depth and width.

• 한국정밀공학회지
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• 제12권11호
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• pp.52-62
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• 1995

In the laser surface hardening process the geometrical parameters, especially the depth, of the hardened layer are utilized to assess the integrity of the hardening layer quality. Monitoring of this geometrical parameter ofr on-line process control as well as for on-line quality evaluation, however, is an extremely difficult problem because the hardening layer is formed beneath a material surface. Moreover, the uncertainties in monitoring the depth can be raised by the inevitable use of a surface coating to enhance the processing efficiency and the insufficient knowledge on the effects of coating materials and its thicknesses. The paper describes the extimation results using neural network to estimate the hardening layer depth from measured surface temperanture and process variables (laser beam power and feeding velocity) under various situations. To evaluate the effec- tiveness of the measured temperature in estimating the harding layer depth, estimation was performed with or without temperature informations. Also to investigate the effects of coating thickness variations in the real industry situations, in which the coating thickness cannot be controlled uniform with good precision, estimation was done over only uniformly coated specimen or various thickness-coated specimens. A series of hardening experiments were performed to find the relationships between the hardening layer depth, temperature and process variables. The estimation results show the temperature informations greatly improve the estimation accuracy over various thickness-coated specimens.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.219-220
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• 2006

Laser surface hardening technologies have been used to improve characteristics of wear and to enhance the fatigue resistance for mold parts. The objective of this research work is to investigate the influence of the process parameters, such as power of laser and defocused spot position, on the characteristics of laser surface hardening for the case of SKD61 steel. CW Nd:YAG laser is selected as the heat source. The optical lens with the elliptical profile is designed to obtain a wide surface hardening area with a uniform hardness. From the results of the experiments, it has been shown that the maximum hardness is approximatly 740 Hv when the power, focal position and the travel of laser are 1,095 W, +1mm and 0.3 m/min, respectively. In addition, the hardening width using the elliptical lens was three time larger than that using the defocusing of laser beam.