• Journal of Welding and Joining
• /
• v.16 no.1
• /
• pp.77-87
• /
• 1998

This paper deals with the effect of laser welding parameters on the weld formation. Thin steels for automotive application were prepared so as to be welded with high power carbon dioxide laser system. Major process parameters were position of focus and travel speed. The effect of shielding gas was also discussed by employing the high speed photometry. Test results showed that the optimal position of focus varied in accordance with the joint configuration; bead-on-plate, butt or lap welding. It was recommended that the position of focus for the lap welding be located at slightly inner part of the material to be welded. In this case, however, it was noticeable that the weld penetration ratio, d/t$_{0}$ dropped drastically at the critical region. Results also demonstrated that both the bead width and penetration reduced as the travel speed increased. The penetration ratio showed two distinct regions; stabilized zone at the lower range of the travel spped and sudden drop zone at the higher range of travel speed. Lower limit of the penetration for acceptable weld was proved to be about 90% of the parent metal thickness based on the physical properties of the weld. Mixed gas application for both the shielding of molten metal and laser induced plasma control was recommended as far as the penetration was concerned.d.

• Journal of the Korean Society of Industry Convergence
• /
• v.5 no.2
• /
• pp.111-118
• /
• 2002

In GMAW(Gas Metal Arc Welding) processes, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality, Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWD (contact-tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using neuro-fuzzy algorithm. Neural networks was applied to design FLC(fuzzy logic control), The parameters of input membership functions and those of consequence functions in FLC were tuned through the method of learning by backpropagation algorithm, Bead geometry could he reasoned from welding current, arc voltage, travel speed on FLC using the results learned by neural networks. On the developed inference system of bead geometry using neuo-fuzzy algorithm, the inference error percent of bead width was within ${\pm}4%$, that of bead height was within ${\pm}3%$, and that of penetration was within ${\pm}8%$, Neural networks came into effect to find the parameters of input membership functions and those of consequence in FLC. Therefore the inference system of welding quality expects to be developed through proposed algorithm.

• Journal of Environmental Health Sciences
• /
• v.21 no.2
• /
• pp.1-6
• /
• 1995

Authors investigated the size distribution and mass fraction of dusts in work environment of Changwon industrial complex. Size distribution of suspended dusts in welding and grinding processes were evaluated using ambient cascade impactors. The mass median diameters of dusts were 0.25 to $0.60 \mu m$ at welding sites and 1.20 to $1.92 \mu m$ at grinding sites. Respirable mass fractions were 63.68 to 73.50% at welding sites and 43.24 to 51.47% at grinding sites. Respirable fractions were calculated from the size distribution data for the ACGIH criteria by the respirable particle mass. In case of dust removal system, electrostatic precipitator and bag filter were appropriate for welding process and grinding process, respectively.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2002.04a
• /
• pp.637-642
• /
• 2002

Generally, the use of robots in manufacturing industry has been increased during the past decade. GMA(Gas Metal Are) welding is an actively growing area and many new procedures have been developed for use with high strength alloys. One of the basic requirement for welding applications is to study relationships between process parameters and bead geometry. The objective of this paper is to develop a new approach involving the use of neural network and multiple regression methods in the prediction of bead geometry for GMA welding process and to develop an intelligent system that enables the prediction of bead geometry using Rapid Prototyping(RP) in order to employ the robotic GMA welding processes. This system developed using MATLAB/SIMULINK, could be effectively implemented not only for estimating bead geometry, but also employed to monitor and control the bead geometry in real time.

• Journal of Ocean Engineering and Technology
• /
• v.25 no.6
• /
• pp.105-109
• /
• 2011

As is well appreciated, welding is the most important fundamental process in manufacturing marine structures. However, weld-induced deformation is inevitable because of the non-uniform distribution of temperature during welding. The deformation caused by welding is one of the principal obstacles in enhancing the productivity in the manufacturing procedure for marine structures. This should be much more seriously considered in the case of the thin blocks found in a ship with multi-deck structures. This paper is concerned with the deformation control of thin panel blocks by applying intermittent welding to fillet welding. In order to investigate the quantitative effect of the intermittent welding, a thermo elasto-plastic analysis was carried out with various welding pitches and plate thicknesses. Welding tests were also carried out to show the validity of the present thermo-elasto-plastic analysis. Numerical analysis results showed good agreement with those of the welding tests. As far as the present numerical results are concerned, it has been seen that a more than 50% reduction in angular distortion can be achieved by applying the intermittent welding because of the low heat input.

• Journal of the Optical Society of Korea
• /
• v.7 no.3
• /
• pp.193-196
• /
• 2003

We have developed a laser welding monitoring system to monitor laser welding process conditions such as sample feed rate, laser focal position, and laser power. A 2 ㎾ Nd:YAG CW laser beam has been applied to the welding of a stainless steel plate (SUS306) to investigate the welding monitoring. Theradiation signal from the weld pool was guided back through the focusing optics and the laser delivery fiber, and measured by a photo detector. By changing the focus of the laser beam along the z-direction, the penetration depth of the welding material has been measured. That shows the penetration depth depends on the frequency fluctuations of the plume signals which can be used in welding quality control.

• Journal of Ocean Engineering and Technology
• /
• v.10 no.2
• /
• pp.69-76
• /
• 1996

In-process quality control and high reliability of the weld are the major concerns in applying friction welding to the economical and qualified mass-production. Experimental examinations and quantitative analysis were performed for the optimiaztion of similar friction welding of hydraulic valve spool steels(SNCM220, SCM435, SACM645, SCM415, ${\varphi}24). The quantitative correlations were found between the initial cumulative counts of acoustic emission(AE) occurring during plastic deformation periods of the welding and the fatigue life as well as weld strength and welding conditions. A real-time evaluation system was developed for the friction weld quality by AE.

• Interaction and multiscale mechanics
• /
• v.5 no.2
• /
• pp.145-155
• /
• 2012

The thin-plate structure and the box-beam structure are two typical welded structures in railway vehicles. Because of their structure complexity, bigger size and multi-seams, welding residual distortion which occur in welding process bring unfavorable effect on the quality of welding products manufacturing and service. As a result, welding distortion forecasting and control become an important and urgent research topic in railway vehicles. In this paper, three different numerical methods are presented corresponding to three typical types of welded structures of railway vehicles and welding deformation are simulated. Consistence of numerical results and experimental data proves the correctness of models and feasibility of simulation methods.

• Journal of Welding and Joining
• /
• v.21 no.1
• /
• pp.80-86
• /
• 2003

This study develops a system for effective prediction of residual stresses by the backpropagation algorithm using the neural network. To achieve this goal, a series of experiments were carried out to and measured the residual stresses using the sectional method. With the experimental results, the optional control algorithms using a neural network could be developed in order to reduce the effect of the external disturbances during GMA welding processes. Then the results obtained from this study were compared between the measured and calculated results, weld guality might be controlled by the neural network based on backpropagation algorithm.. This system can not only help to understand the interaction between the process parameters and residual stress, but also improve the quantity control for welded structures.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2009.05a
• /
• pp.227-230
• /
• 2009

The aim of this study was to improve extrudability limit, eliminate welding line and obtain optimum thixoextrusion conditions for manufacturing tubes of 7075 Al wrought alloy. By thixoextrusion, it was possible to improve deformability, control isotropy with extrusion direction, eliminate welding line (seamless) and save cost due to low energy consumption compared with conventional extrusion processes. The welded part was not observed at the welding line area. The grains of thixoextruded tube were homogeneously distributed and equiaxed grains were observed. Therefore, thixoextrusion is the most effective variable for the control of the magnitude of the welding line.