An Integrated Hybrid Methodology for Estimation of Absorptivity and Interface Temperature in Laser Transmission Welding

This study reports a new hybrid integrated technique to predict the absorptivity of absorber and the interface temperature of the joint in laser transmission welding. The new approach is more robust as the numerical model is confirmed through experimental observations initially with weld width and further with surface temperature. Experiments are performed on a polycarbonate sheets with electrolytic iron powder (EIP) as an absorber. The surface temperature and weld width are measured from the experiments. A transient 3-D finite element-based numerical model is developed for heat transfer analysis. The variation of heat flux with stand-off distance is also considered to enhance the accuracy of the computed results. The absorptivity is tuned in the numerical model so that the numerical weld width is in close conjunction with the experimental weld width. The numerical model is validated by comparing the upper surface temperatures at the center, measured in the experiments using infrared thermography. The results indicate that the surface temperatures in the numerical model are in good agreement with experimental observations, and the average error is less than 6%. The interface temperatures are estimated after the validation of the numerical model.

Laser Oscillating of Nickel Alloyed Welds on Press-hardened Steel

Laser oscillating welding was employed to fabricate Al-Si coated press-hardened steel (PHS) to improve the element homogeneity in the fusion zone. Three oscillation amplitudes that are 0 mm, 0.5 mm and 1.3 mm were studied in this present. Ni foil of 0.06 mm thickness was used as an interlayer between two tailored PHS welded. Welds defects was absent for any oscillation amplitudes, and weld width increased with increasing oscillation amplitudes. Compared to linear laser welding, Ni and Al had an uneven elemental profile due to strong stirring force, full martensite was achieved in fusion zone. However, δ-ferrite was present with oscillation amplitudes increased to 1.3 mm, since Ni content had a sharp descent compared to Al. Tensile srtength of welded joints was not influnced by altering oscillation amplitudes.

Study on Effect of Laser Process Parameters on Laser Transmission Weld Parameters using ANSYS

In recent years, a mode of welding that has garnered a considerable amount of interest is the laser transmission welding of thermoplastics. Laser transmission welding is now being used as an alternative to adhesives to join two thermoplastics. In this study, a finite element model has been developed to simulate the laser transmission welding of polypropylene. The movement of the laser beam was done using a Moving Heat Source in Ansys®. Process parameters namely laser power, welding speed, and the number of passes have been studied in order to investigate their effects on the temperatures and the weld widths achieved during welding. It was found that an increase in the laser power had a positive effect on the maximum temperature at the weld interface as well as the weld width. Similarly, an increase in the welding speed had a negative influence on the maximum temperature at the weld interface as well as the weld width.

A Novel Method of Defect Detection Based on Experimental Investigation of Galvanized Steel Welded Plates Using Wobble Laser Process

This paper aims at investigating the effect of laser welding parameters on the hardness profile, using hardness mapping analyses, and welding geometry of galvanized steel plates. Hardness distribution and geometry deflection of galvanized welded thin plates are commonly applied in fields where the weld quality is of utmost importance. Due to the welding process and material condition, welding galvanized steel is one of the problematic matters in welding technology. Here, the design of experiment (DOE) approach is used to study the effect of process parameters. Using a pattern matrix of micro-indentation hardness experiment, the welding defects are visualized on hardness profile of the weld cross-section. The effect of process parameters on welding defect formation is then qualitatively analyzed. The geometrical defects of welding such as weld width and voids are then quantitatively studied based on analysis of variance (ANOVA), and predictive models of welding voids and weld seam width are developed based on the regression method. Response surface method (RSM) is then applied to define the trend of process factors interaction on the welding defects. The experimental results confirm the reliability of developed predictive models of welding defects geometry, weld width, and voids area of laser-welded galvanized plates.

An automatic compensation method for improving forming precision of multi-layer multi-bead component

Wire and arc additive manufacturing (WAAM) is a promising technology for manufacturing large-sized metal components. However, the material shortage region (MSR) at the edge of each slicing layer can influence the forming precision and surface flatness of components. To solve these problems, this paper proposes a shape follow-up edge cycle compensation (SECC) method and model for predicting the weld width and weld height to improve the efficiency of the WAAM process. First, the prediction model was used to determine the weld width and weld height for various welding parameters. The predicted width was then used to obtain the optimal overlap distance, and the filling path of each layer was generated. The same weld height was used for slicing of the 3D model and the tool path compensation cycle was generated. Second, the influence of the MSR on the morphology of multi-layer multi-bead (MLMB) components was analyzed. The MSR results in a height difference between the edge height and the middle height of every deposited layer, and the height difference increases as more layers are added and the height of the component increases. Furthermore, the influence of the MSR gradually extends from the edge to the middle, such that the upper surface presents a parabolic shape. Finally, a mathematical model was established to determine the height difference based on the area of the MSR. When the height difference reaches the weld height, an edge compensation weld is added to eliminate the height difference. Our experimental results show that the proposed forming control strategy improves forming precision and surface flatness. The method is highly feasible and can be applied to a wide range of WAAM applications.

Experimental Investigation on Laser Transmission Welding of Polycarbonate and Acrylic

This chapter presents the effect of various process parameters, namely laser power, pulse frequency, and welding speed, on the weld shear strength and weld width using a diode laser system. Here, laser transmission welding of transparent polycarbonate and black carbon filled acrylic each of 2.8 mm thickness have been performed to create lap joint by using low power laser. Response surface methodology is applied to develop the mathematical model between the laser welding process parameters and the responses of weld joint. The developed mathematical model is tested for its adequacy using analysis of variance and other adequacy measures. It has been observed that laser power and welding speed are the dominant factor followed by frequency. A confirmation test has also been conducted to validate the experimental results at optimum parameter setting. Results show that weld strength of 34.3173 N/mm and weld width of 2.61547 mm have been achieved at optimum parameter setting using desirability function-based optimization technique.

TIG Stainless Steel Molten Pool Contour Detection and Weld Width Prediction Based on Res-Seg

As the basic visual morphological characteristics of molten pool, contour extraction plays an important role in on-line monitoring of welding quality. The limitations of traditional edge detection algorithms make deep learning play a more important role in the task of target segmentation. In this paper, a molten pool visual sensing system in a tungsten inert gas welding (TIG) process environment is established and the corresponding molten pool image data set is made. Based on a residual network, a multi-scale feature fusion semantic segmentation network Res-Seg is designed. In order to further improve the generalization ability of the network model, this paper uses deep convolutional generative adversarial networks (DCGAN) to supplement the molten pool data set, then performs color and morphological data enhancement before network training. By comparing with other traditional edge detection algorithms and semantic segmentation network, it is verified that the scheme has high accuracy and robustness in the actual welding environment. Moreover, a back propagation (BP) neural network is used to predict the weld width, and a fitting test is carried out for the pixel width of the molten pool and its corresponding actual weld width. The average testing error is less than 0.2 mm, which meets the welding accuracy requirements.