Penetration control is an important factor in determining the weld quality in keyhole mode laser welding, which enables deep penetration. In this study, machine learning models and neural network models were developed by using 380 published welding data which were constructed for steel base metals under the following welding conditions: a laser power of 0.3-16.7 kW, a welding speed of 0.3-20.0 m/min, and a bead diameter of 0.05-0.78 mm. A machine learning model SVM (supported vector machine) could accurately predict the penetration depth with a coefficient of determination, R2 of 0.95. A shallow neural network model with five nodes in only one hidden layer was developed with a slightly improved accuracy with R2 of 0.98. It was confirmed that neither model was overfitted, and process parameters (welding speed and beam diameter) maps with penetration depth contours were provided for a laser power of 2-8 kW.

Recently, for the high performance of automobiles, the application ratio of zinc-coated steel sheets with excellent corrosion resistance has been increasing. However, it is difficult to achieve sound welds, as porosities form from zinc during welding. In this study, a laser welding process, with the addition of a pretreatment step to conventional laser welding, was devised to improve weld quality by eliminating pores caused by zinc in the welds. Laser welding was performed on the overlapping joint of hot-dip galvanized steel sheets (SGARC 340, Hyundai Steel., Suncheon-Si, Jeollanam-do, Republic of Korea), with a thickness of 1.2 mm in the upper sheet and 0.9 mm in the lower sheet, and the welding characteristics were investigated by varying the laser power and focal position. Compared to conventional laser welding, the three-step laser stitch welding process significantly reduced the degree of spatter generation and welding defects. Additionally, it increased the tensile–shear load by approximately 37%. Moreover, the reduction in the zinc component of the three-step laser stitch welds was confirmed through SEM-EDS analysis. These findings contribute valuable information for securing high-quality welding joints and effectively addressing zinc-coated steel sheet welding quality issues in the automotive and industrial sectors.

This study examines the joining characteristics of Cu foil stacks to lead tabs using green-laser welding in the main-welding step of a sequential welding process for lithium-ion pouch cells. The influence of lap configuration, line and wobble seam strategies, and process parameters was systematically investigated in terms of bead morphology, mechanical performance, metallurgical characteristics, and electrical resistance. Under the present line-welding parameter window (2.0 kW, 100–200 mm/s), humping, pinholes, and porosity were observed, particularly in the upper lead-tab configuration, which is attributed to melt-pool/keyhole instability under the applied conditions. Wobble welding effectively suppressed these defects in the foil-stack configuration by promoting stable melt flow and efficient bubble expulsion. Mechanical tests revealed that the wobble-based seam strategy achieved a maximum tensile–shear load of approximately 1.28 kN at a wobble amplitude of 0.8 mm. Fracture analysis confirmed a transition from seam-type interfacial failure in line welding to ductile tearing in the heat-affected zone with wobble welding. In electrical performance, wobble welding reduced resistance to as low as 45 µΩ at a wobble amplitude of 1.2 mm, while line welding yielded higher and scattered values. These results should be interpreted as the combined outcome of the wobble-based seam strategy (beam oscillation together with overlapped stitch welding at a lower travel speed) under the present processing windows. A strictly matched A/B comparison at identical linear energy density and seam layout will be investigated in future work to isolate the effect of oscillation.

This study investigates the joint characteristics of a 60-layered copper foil stack using linear vibration ultrasonic welding for lithium-ion pouch cell applications. With increasing demand for high-capacity electric vehicle batteries, ensuring the reliability of multilayer electrode joints is essential. Experiments were conducted by varying vibrational amplitude, welding time, and clamping pressure. Weld quality was analyzed based on indentation profiles, joint strength, and failure modes. Results revealed that optimal welding energy (500–900 J) produced well-formed joints without surface cracks or tearing. Excessive welding energy (>900 J) led to material thinning and interfacial failure. The maximum T-peel peak load of 138.7 N was obtained at the 30th joining interface under 25 µm amplitude, 0.8 s welding time, and 1.5 bar clamping pressure. Interface-dependent optimum conditions were observed, reflecting thickness–direction variations in deformation and bonding within the 60-layer stack. Indentation length and depth correlated linearly with welding energy. Failure modes transitioned from no adhesion to tearing and button-pull types. The findings provide guidelines for optimizing welding parameters for high-quality multilayer foil joints in battery manufacturing.

Laser welding of multilayer copper foil stacks for lithium-ion battery tabs generates steep thermal gradients that can induce plastic deformation and residual stresses, potentially affecting joint integrity. This study numerically investigates the effect of laser beam oscillation on the thermo-mechanical behavior of a 60-layer Cu foil stack joined to a 0.3 mm Cu tab using a three-dimensional sequentially coupled finite element model. Line and wobble welding were compared using temperature-dependent material properties and a moving conical Gaussian heat source. Beam oscillation increased the predicted peak temperature from 2060 K to 2577 K while reducing the through-thickness temperature reduction from approximately 22.5% to 12.1%, indicating a more uniform thermal field. The dominant longitudinal residual stress decreased from approximately 225 MPa to 181 MPa, while the von Mises equivalent residual stress decreased from 199 MPa to 141 MPa, corresponding to a reduction of approximately 29%. These results demonstrate that beam oscillation redistributes thermal energy and mitigates localized residual-stress concentration, providing a numerical basis for optimizing laser welding of multilayer Cu battery-tab joints.