Earticle

In this study, we proposed a simulator for the development of a digital multi-process welding machine and a welding process monitoring system. The simulator, which mimics the data generation process of the welding machine, is composed of process control circuit, peripheral device circuit, and wireless communication circuit. Utilizing this simulator, we aimed to develop a welding process monitoring system that can monitor the welding situations of four multi-process welding machines and three processes each, with data transmission through wireless communication. Through the operation of the proposed simulator, sequential digital processing of multi-process welding data and wireless communication were achieved. The welding process monitoring system enabled real-time monitoring and accumulation of the process data. The selection of upper and lower limits for process variables was carried out using a deep neural network based on allowable changes in bead shape, enabling the management of welding quality by applying a process control technique based on the trend of received data.

In the development of a digital multi-process welding machine, we aimed to analyze the heat dissipation effects resulting from changes in the transformer's shape. Two installation configurations for the transformer, vertical and horizontal, were proposed. Thermal-flow analysis was conducted for the welding machine, taking into account variations in spacing between each proposed configuration. The results indicated that the shape and spacing of the components did not significantly alter the airflow around the reactor coil, which is the main heat-generating component of the machine. When comparing the heat dissipation effects across models with different transformer spacings, it was observed that models with narrower spacing exhibited improved heat dissipation, while the vertical configuration demonstrated a slightly higher heat dissipation effect overall. Transient analysis revealed the irregularities in internal flow and the resulting scattered temperature distribution over time within the welding machine.

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.

Optimization of process parameters for welding cupronickel alloys using CO2 laser welding process was investigated in thisstudy. Laser Beam Welding (LBW) process, is one of the beneficial techniques for airplane fastening. Turbine motorcomponents were made up of superalloy because of its high specific, low heat input, high heat focus, high-power density, andlow contortion. Using CO2 LBW process, welding can be done on a wide range of materials, especially alloys which aredifficult to weld by conventional welding process. This investigation focuses on optimizing the LBW process parameters ofcupronickel alloys utilizing multi criteria decision making (MCDM) methodology and TOPSIS analysis. The inputparameters like laser power, welding speed, welding angle and welding current are preferred as the fundamental part toenhance the welding. Welding process is carried out on 16 specimens in order to improve and support mechanical andmetallurgical qualities of the welded parts. Welding is made with four input variables in two levels of values. TOPSIS hasbeen employed as a statistical design tool to identify the most significant parameters on the overall Multiobjective function. Among the experiments, the best mechanical properties were observed in welding made with the parameters like Weldingcurrent (900 W), Welding angle (90°), Welding speed (1.4mm/min) and Laser power (30 W). This investigation strives toreveal the better process parameters, mechanical properties and energy consumption of CO2 LBW welded elements ofcupronickel alloy.

A residual stress generated in the steel structure is broadly categorized into initial residual stress during manufacturing steel material, welding residual stress caused by welding, and heat treatment residual stress by heat treatment. Initial residual stresses induced during the manufacturing process is combined with welding residual stress or heat treatment residual stress, and remained as a final residual stress. Because such final residual stress affects the safety and strength of the structure, it is of utmost importance to measure or predict the magnitude of residual stress, and to apply this point on the design of the structure. In this study, the initial residual stress of steel structures having thicknesses of 25 mm and 70 mm during manufacturing was measured in order to investigate initial residual stress (hereinafter, referred to as initial stress). In addition, thermal elastic plastic FEM analysis was performed with this initial condition, and the effect of initial stress on the welding residual stress was investigated. Further, the reliability of the FE analysis result, considering the initial stress and welding residual stress for the steel structures having two thicknesses, was validated by comparing it with the measured results. In the vicinity of the weld joint, the initial stress is released and finally controlled by the weld residual stress. On the other hand, the farther away from the weld joint, the greater the influence of the initial stress. The range in which the initial stress affects the weld residual stress was not changed by the initial stress. However, in the region where the initial stress occurs in the compressive stress, the magnitude of the weld residual compressive stress varies with the compression or tension of the initial stress. The effect of initial stress on the maximum compression residual stress was far larger when initial stress was considered in case of a thickness of 25 mm with a value of 180 MPa, while in case of thickness at 70 mm, it was 200 MPa. The increase in compressive residual stress is almost the same as the initial stress. However, if initial stress was tensile, there was no significant change in the maximum compression residual stress.

본 논문에서는 원통형 다층 이종 금속 용접부를 대상으로 유한요소 해석을 수행하여, 열원 입력 방법과 용접 비드 생성 방법이 용접 잔류 응력 분포에 미치는 영향을 고려하였다. 열원 입력 방법은 열속 입력 방법과 온도 경계조건 입력 방법으로 나누어 비교하였고, 용접 비드 생성 방법은 요소망 생성 방법과 평온 요소망 방법으로 나누어 비교하였다. 두 열원 입력 방법에 따른 열 해석 결과는 차이가 있었으나, 응력 해석 결과는 유사하였다. 이것은 고온(약 $1000^{\circ}C$ 이상)에 노출되었던 영역이 비슷하고, 고온에서 재료의 강도가 매우 낮아 용접 비드의 온도가 용접잔류응력에 미치는 영향이 미미하기 때문이다. 두 용접 비드 생성 방법의 용접 잔류응력 분포는 유사하였지만 요소망 생성 방법 적용 시 용접 비드 경계에서 겹침과 들뜸이 발생하였다. 대변형이 발생하는 모델의 용접부 형상을 정확하게 모사하기 위해서는 평온요소망이 더 적합하다고 판단된다.

In this study, a finite element analysis of a cylindrical multi-pass weldment for dissimilar metals was performed. The effects of the heat input method and weld bead generation method were considered. We compared two heat input methods: the heat flux method and the temperature method. We also compared two weld bead generation methods: the element birth method and the quiet element method. Although the results of the thermal analysis show deviations between the two heat input methods, the welding residual stresses were similar. Because the areas exposed to high temperature were similar and the strength of the material was very low in high temperature (above the $1000^{\circ}C$), the effects of the weld bead temperature were insignificant. The distributions of the welding residual stress were similar to each other. However, gaps and overlaps occurred on the welding boundary surfaces when the element birth method was applied. The quiet element method is more suitable for a large deformation model in order to simulate a more accurate weld shape.

Presented in this paper is the process planning for multi-weldline/multi-pass robot welding. First, downhand welding for welding quality and stability for welding productivity, the two concept of process planning for single-weldling/single-pass robot weldling are derived. Next, process planning procedure for single-weldling/single-pass robot weldling is proposed and the procedure is extended for multi-weldling and/or multi-pass robot welding.

Ultrasonic metal welding has been widely used for joining lithium-ion battery tabs. Weld quality monitoring has been an important issue in lithium-ion battery manufacturing. This study focuses on the weld quality monitoring in ultrasonic metal welding with the longitudinal-torsional vibration mode horn developed newly. As the quality of ultrasonic welding depends on welding parameters like pressure, time, and amplitude, the suitable values of these parameters were selected for experimentation. The welds were tested via tensile testing machine and weld strengths were investigated. The dataset collected for performance test was used to train the multi-layer perceptron neural network. The three layer neural network was used for the study and the optimum number of neurons in the first and second hidden layers were selected based on performances of each models. The best models were selected for the horn and then tested to see their performances on an unseen dataset. The neural network models for the longitudinal-torsional mode horn attained test accuracy of 90%. This result implies that proposed models has potential for the weld quality monitoring.