• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1101-1104
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• 1995

Through welding fabrication, user can feel an surficaial and capable unsatisfaction because of welded defects, Generally speaking, these are called weld defects. For checking these defects effectively without time loss effectively, weldability estimation system setup isan urgent thing for detecting whole specimen quality. In this study, by laser vision camera, catching a rawdata on welded specimen profiles, treating vision processing with these data, qualititative defects are estimated from getting these information at first. At the same time, for detecting quantitative defects, whole specimen weldability estimation is pursued by multifeature pattern recognition, which is a kind of fuzzy pattern recognition. For user friendly, by weldability estimation results are shown each profiles, final reports and visual graphics method, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line weldability estimation.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.4
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• pp.22-28
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• 2007

The welded defects are usually called user's unsatisfaction for appearance and functional usage. For checking these defects effectively without time loss, setup of weldability estimation system is an important for detecting whole specimen quality. In this study, after catching a rawdata on welded specimen profiles and treating vision processing with these data, the qualitative defects are estimated from getting these information by laser vision camera at first. At the same time, the weldability estimation for whole specimen is produced. For user friendly, the weldability estimation results are shown each profiles, final reports and visual graphics method. So, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line setup of weldability estimation system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.3
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• pp.605-610
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• 2008

Through welding fabrication, user can feel unsatisfaction of surface quality because of welded defects, Generally speaking, these are called weld defects. For checking these defects effectively without time loss effectively, weldability estimation system setup is an urgent thing for detecting whole specimen quality. In this study, by laser vision camera, catching a rawdata on welded specimen profiles, treating vision processing with these data, qualitative defects are estimated from getting these information at first. At the same time, for detecting quantitative defects, whole specimen weldability estimation is pursued by multifeature pattern recognition, which is a kind of fuzzy pattern recognition. For user friendly, by weldability estimation results are shown each profiles, final reports and visual graphics method, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line weldability estimation.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.60-68
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• 2007

It has been conducted by laser vision sensor for weldability estimation of front-bead after doing high speed butt laser welding of any condition. It has been developed a real time GUI(Graphic User Interface) system for weldability application in the basis of texts and field qualify levels. In the reference of bead imperfections, defects absolute position and defects intensity index of front-bead in the basis of formability reference, it has been produced a weldability estimation and defects intensity index of back-bead by back propagation neural network. In the result of by comparing measuring data by laser vision sensor of back-bead and data by back propagation neural network of one, it has been shown the similar results. Finally, under knowledge of welding condition in production line, it has been conducted a weldability estimation of back-bead only in knowledge of informations of front-bead data without using laser vision sensor or welding inspection experts and furthermore it can be used data for final inspection results of back-bead.

• Journal of Welding and Joining
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• v.16 no.5
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• pp.76-85
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• 1998

The resistance spot welding process has been used for joining the sheet metal in automotive engineering. In the resistance spot welding, the weld quality is very important, because the quality of weld is one of the most important factors to the automobile quality. The size of he molten nugget has been utilized to estimate the weld quality. However, it is not easy to find the weld defects. For weldability estimation, we have to use the nondestructive method such as X-ray or ultrasonic inspection. But these kinds of approaches are not suitable for detecting the defects in real time. The purpose of this study is to develop the real time monitoring of the weld quality in the resistance spot welding. Obtained data were used to estimate weldability using fuzzy algorithm. It is sound that this monitoring and estimation system can be useful to improve the weld quality in the resistance spot welding process and it is possible to estimate the weldability in real time.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.49-59
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• 2005

This paper describes a development of the extrusion process and estimation of the weldability for multi cell tubes used to cooling system of automobiles. A study on extrusion process is performed through the 3D FE simulation in non-steady state and extrusion experimentation. Also, nano-indentation test is employed to estimate the weldability of tubes. Especially, An evaluation of the weldability using the nano-indentation is accomplished as compared with nano-hardness in welded part and in the others. Finally, the pattern of the mandrel defection is investigated according to shapes of the porthole and/or chamber.

• Proceedings of the KWS Conference
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• 1997.10a
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• pp.176-178
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• 1997

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.3
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• pp.1070-1077
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• 2011

This paper is studied on the influence of machining conditions on weldability obtained by ultrasonic machining. The weldability estimation of dissimilar Ni-Cu sheets with the optimization of one-wavelength horn is confirmed by the use of ultrasonic machining. The optimal welding condition with tensile test by setting the ultrasonic machining parameters is suggested and the weldability is estimated by SEM observation and EDX-ray analysis. Experimental studies are worked with the measure of tensile strength and the analysis of SEM photograph after the ultrasonic machining of workpiece. Machining parameters of machining time, pressure, and amplitude are also applied to this paper.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.4
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• pp.79-86
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• 2007

The shape of excessive penetration mainly depends on welding conditions(welding current and welding voltage), and welding process(groove gap and welding speed). These conditions are the major affecting factors to width and height of back bead. In this paper, back-bead prediction and weldability estimation using artificial neural network were investigated. Results are as follows. 1) If groove gap, welding current, welding voltage and welding speed will be previously determined as a welding condition, width and height of back bead can be predicted by artificial neural network system without experimental measurement. 2) From the result applied to three weld quality levels(ISO 5817), both experimented measurement using vision sensor and predicted mean values by artificial neural network showed good agreement. 3) The width and height of back bead are proportional to groove gap, welding current and welding voltage, but welding speed. is not.

• Journal of Welding and Joining
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• v.23 no.4
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• pp.59-65
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• 2005

The resistance spot welding is one of the most commonly used welding process for joining the sheet metal in automotive manufacturing process due to higher deposition rates and higher economy achieved. Control variables in the resistance spot welding for achieving high quality are welding current, welding force and welding time. Generally at the manufacturing scene, welding current Vs welding time lobe diagram is used to estimate weldability because controlling welding force is not practical due to economical reasons. However new automotive steel plates have been developed to make lightweight automobiles and to improve resistance against rusting. Also the weldability of these steel plates are worst than the existing steel plates because of changing bare metal and surface plating effect. In consequence of above mentioned reasons, it is necessary to use welding force to present the lobe diagram. In this study, we obtained the welding force Vs welding current lobe diagram for commonly used GA steel plate and found that the second order repression model of tensile shear strength was useful in reducing the number of experiments, and the indentation, and thickness change during welding were used as a response to estimate quantitatively expulsion.