Jong-Pyo Lee

A Study on HAZ Softening Characteristics of Fiber Laser Weldment for High-Strength Steel

Laser welding sector in the automotive industry has been widely recognized as one of the most important bonding processes, such as parts welding. Efforts to improve productivity and weld quality have been progressing steadily. In addition, laser welding is suitable for welding process that can produce high-quality welds suitable for flexible production and small quantity batch productions. In order to ensure the rigidity of the material, high strength material are applied to more than 1 GPa class body parts and automotive bumper beams. However, not only the situation is that the trend of domestic research, but also development is based on product molding considering freedom of shape where reinforcement is applied to meet the safety regulations and high-speed crash performance, despite the use of high strength materials. The tendency for heat-affected zone (HAZ) softening phenomenon common in areas of laser welded high tensile steel welding confirmed the occurrence of weld softening effect according to the process parameters. Based on this, range of process parameters could be selected for ensuring weld quality.

A Study on Development of STACO Model to Predict Bead Height in Tandem GMA Welding Process

One of the main challenges of the automatic arc welding process which has been widely used in various constructions such as steel structures, bridges, autos, motorcycles, construction machinery, ships, offshore structures, pressure vessels, and pipelines is to create specific welding knowledge and techniques with high quality and productivity of the production-based industry. Commercially available automated arc welding systems use simple control techniques that focus on linear system models with a small subset of the larger set of welding parameters, thereby limiting the number of applications that can be automated. However, the correlations of welding parameters and bead geometry as welding quality have mostly been linked by a trial and error method to adjust the welding parameters. In addition, the systematic correlation between these parameters have not been identified yet. To solve such problems, a new or modified models to determine the welding parameters for tandem GMA (Gas Metal Arc) welding process is required. In this study, A new predictive model called STACO model, has been proposed. Based on the experimental results, STACO model was developed with the help of a standard statistical package program, MINITAB software and MATLAB software. Cross-comparative analysis has been applied to verify the reliability of the developed model.

A Experiment Study of Torch Distance on Automated Tandem GMA Welding System

Abstract The tandem welding process is one of the most efficient welding processes widely used in material joining technique such as manufacturing of strong and durable structures. It facilitates high rate of joint fillingwith little increase in the overall rate of heat input due to the simultaneous deposition from two electrode wires. The two electrodes in tandem welding process helps in high-efficiency and high productive of welding process. In this study a automated tandem welding system is developed to determine the correlation between cathodeand anode and compared with current ratio of the two electrode torch. Three different inter-electrode distanceswere chosen, 25mm, 35mm and 45mm to perform the experiment with three different current ratio. From the experiment results, the current ratio between two torch has a large impact on width, height and depth of penetration. In addition, a stable bead geometry is obtained when inter-electrode distance is 35mm.Key Words : Tandem GMAW, Interface controller, Torch distance, Current ratio

A Study on Development of the Optimization Algorithms to Find the Seam Tracking

Abstract The Gas Metal Arc(GMA) welding, called Metal Inert Gas(MIG) welding, has been an important componentin manufacturing industries. A key technology for robotic welding processes is seam tracking system, whichis critical to improve the welding quality and welding capacities. The objectives of this study were to developthe intelligent and cost-effective algorithms for image processing in GMA welding which based on the laservision sensor. Welding images were captured from the CCD camera and then processed by the proposed algorithm to track the weld joint location. The proposed algorithms that commonly used at the present stage were verifiedand compared to obtain the optimal one for each step in image processing. Finally, validity of the proposed algorithms was examined by using weld seam images obtained with different welding environments for image processing. The results proved that the proposed algorithm was quite excellent in getting rid of the variable noises to extract the feature points and centerline for seam tracking in GMA welding and could be employed for general industrial application. Key Words : GMA welding process, Seam tracking, Image process, Laser vision sensorISSN 2466-2232Online ISSN 2466-2100

An Experimental Study on Prediction of Bead Geometry for GTA Multi-pass Welding in Underhead Position

Abstract The automatic arc welding is generally accepted as the preferred joining technique and commonly chosen for assembly of large metal structures such as in areas of automotive, aircraft and shipbuilding due to its joint strength, reliability, and low cost compared to other joint processes. Recently, several mathematical models have been developed and studied for control and monitoring welding quality, productivity, microstructure and weld properties in arc welding processes. This study indicates the prediction of process parameters for the expected welding quality with accordance to the adaptive GTA welding process. Furthermore, the mathematical models is also develop to aid the selection of an optimal welding process as the generation of process controls to predict the bead geometry as a function output parameters in the GTA welding process. The developed models through this study showed comparatively excellent predicted results, and will extend to other welding processes to integrate an optimized system for the robotic welding process.Key Words : GTAW, Multi-pass welding, Mathematical model, Curvilinear model, Main effects plot

Development on Tandem GMA Welding System using Seam Tracking System in Pipe Line

In this study to improve the productivity, advantage Tandem circumferential weld process of seam tracking system was applied for the laser vision sensor. Weld geometry scanning laser vision sensor and PLC control unit are used to scan correct positioning of welding torch when the program is implemented so that it can correctly track the welding line. The welding experiment was conducted to evaluate the performance of laser vision seam tracking sensor in tandem welding process. The seam tracking several experiments was to determine the reliability of the system, welding experiments relatively good quality welding bead was confirmed. Furthermore, the PLC program for seam tracking was used to confirm the validity of the application of tandem welding process according to the benefits of increased productivity, which is expected to contribute to national competitiveness.

A Study on Bead Geometry Prediction the GMA Fillet Welding using Genetic Algorithm

The GMA welding process involves large number of interdependent variables which may affect product quality, productivity and cost effectiveness. The relationships between process parameters for a fillet joint and bead geometry are complex because a number of process parameters are involved. To make the automated GMA welding, a method that predicts bead geometry and accomplishes the desired mechanical properties of the weldment should be developed. The developed method should also cover a wide range of material thicknesses and be applicable for all welding position. For the automatic welding system, the data must be available in the form of mathematical equations. In this study a new intelligent model with genetic algorithm has been proposed to investigate interrelationships between welding parameters and bead geometry for the automated GMA welding process. Through the developed model, the correlation between process parameters and bead geometry obtained from the actual experimental results, predicts that data did not show much of a difference, which means that it is quite suitable for the developed genetic algorithm. Progress to be able to control the process parameters in order to obtain the desired bead shape, as well as the systematic study of the genetic algorithm was developed on the basis of the data obtained through the experiments in this study can be applied. In addition, the developed genetic algorithm has the ability to predict the bead shape of the experimental results with satisfactory accuracy.

On-Line Empirical Models for Control of Bead Geometry in Robotic Arc Welding Process

Recently, not only robotic welders have replaced human welders in many welding applications, but also reasonable seam tracking systems are commercially available. However, fully adequate process control systems have not been developed due to a lack of reliable sensors and mathematical models that correlate welding parameters to the bead geometry for the automated welding process. Especially, real-time quality control in automated welding process is an important factor contributing to higher productivity, lower costs and greater reliability of the bead geometry. In this paper, on-line empirical models with experimental results are proposed in order to be applicable for the prediction of bead geometry. For development of the proposed predicting model, an attempt has been made to apply for a several methods. For the more accurate prediction, the prediction variables are first used to the surface temperatures measured using infrared thermometers with the welding parameters (welding current, arc voltage, CTWD and gas flow rate) because the surface temperature are strongly related to the formation of the bead geometry. And the developed model has been carried out a learning each time data acquired.