• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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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.

• Transactions of Materials Processing
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• v.28 no.1
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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.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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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.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.2
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• pp.11-22
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• 2022

This paper presents the development process for a high-power diode laser for metal surface hardening. To combine the emissions from several laser bars, it is necessary to collimate the emitted light using an optical lens. Thus, to achieve a suitable power density and uniform beam profile, several optical layouts were proposed. To estimate the laser beam for a flat-top distribution, a numerical analysis was performed using the ZEMAX software, and the results were compared with the experimental results. With a focal lens assembled in a serial diode stack source, the design can utilize the advantage of compacting the overall beam size. Experimental results for a robotic system demonstrated the processing ability of this diode laser module in industrial laser hardening.

• Journal of Welding and Joining
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• v.25 no.3
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.292-292
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• 2000

Since high-power CO$_2$ Laser can be make a high densed energy to Local processing area, manufacturing processes using the laser can be processed for very Localized areas at a very fast rate with minimal or no distortion. Accordingly, the laser has been widely used in the fields of thermal manufacturing processes such as welding, fusion cutting, grooving, and heat treatment of metals. In particular, interest in the laser heat treatment process has grown tremendously in the past few years. In this process, maintaining the uniform hardening depth is important problem to obtain good quality products and to reduce heat induced distortion and residual stress. For achieving this objective, we introduced a new design technique of a fuzzy logic controller that greatly simplified the design procedure by defining several simplified design parameters. In the design procedure, the major design parameters of the controller are characterized by identifying several common aspects. From a series of simulation results, we found that the proposed design technique can be effectively used to design of a fuzzy logic controller for the LASER surface hardening process.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.883-888
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• 1993

This paper proposes a monitoring method using an infrared temperature sensor in laser surface hardening process. To investigate the validity of the method a series of experiments are performed for various conditions. The experimental results show that the surface temperature depends upon the laser power, travelling speed and surface conditions of a specimen. Especially, the laser surface hardening process is greatly influenced by the surface conditions of the specimen, such as coating thickness and materials.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.8
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1048-1054
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• 2003

In laser surface hardening processes, the geometrical parameters such as the depth and the width of a hardened layer can be utilized to assess the hardened layer quality. However, accurate monitoring of the geometrical parameters for on-line process control as well as for on-line quality evaluation is very difficult because the hardened layer is formed beneath a material surface and is not visible. Therefore, temperature monitoring of a point of specimen surface has most frequently been used as a process monitoring method. But, a hardened layer depends on the temperature distribution and the thermal history of a specimen during laser surface hardening processing. So, this paper describes the estimation results of the geometric parameters using multi-point surface temperature monitoring. A series of hardening experiments were performed to find the relationships between the geometric parameters and the measured temperature. Estimation results using a neural network show the enhanced effectiveness of multi-point surface temperature monitoring compared to one-point monitoring.