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This paper presents an experimental investigation of laser welding low carbon galvanized steel in butt-joint configurations. The experimental work is focused on the effects of various laser welding parameters on the welds quality. The investigations are based on a structured experimental design using the Taguchi method. Welding experiments are conducted using a 3 kW Nd:YAG laser source. The selected laser welding parameters (laser power, welding speed, laser fiber diameter, gap between sheets and sheet thickness) are combined and used to evaluate the variation of four weld quality attributes (bead width, penetration depth, underfill and hardness) and to identify the possible relationship between welding parameters and weld physical and geometrical attributes. The effects of these parameters are studied using ANOVA to find their contributions to the variation of different weld characteristics. Plots of the main effects and the interaction effects are also used to understand the influence of the welding parameters. The results reveal that all welding parameters are relevant to bead width (BDW) and depth of penetration (DOP) with a relative predominance of laser power and welding speed. The effect of laser fiber diameter on penetration depth is insignificant. Typical gap-dependent weld shapes show that a small gap results in a narrower and deeper weld. Due to the standard sheared edge, an underfill between 5% and 10% occurs for no-gap experiments. The resulting hardness values are relatively similar for all the experimental tests.

The quality assessment and prediction becomes one of the most critical requirements for improving reliability, efficiency and safety of laser welding. Accurate and efficient model to perform non-destructive quality estimation is an essential part of this assessment. This paper presents a structured and comprehensive approach developed to design an effective artificial neural network based model for weld bead geometry prediction and control in laser welding of galvanized steel in butt joint configurations. The proposed approach examines laser welding parameters and conditions known to have an influence on geometric characteristics of the welds and builds a weld quality prediction model step by step. The modelling procedure begins by examining, through structured experimental investigations and exhaustive 3D modelling and simulation efforts, the direct and the interaction effects of laser welding parameters such as laser power, welding speed, fibre diameter and gap, on the weld bead geometry (i.e. depth of penetration and bead width). Using these results and various statistical tools, various neural network based prediction models are developed and evaluated. The results demonstrate that the proposed approach can effectively lead to a consistent model able to accurately and reliably provide an appropriate prediction of weld bead geometry under variable welding conditions.

This paper presents an experimentally validated weld joint shape and dimensions predictive 3D modeling for low carbon galvanized steel in butt-joint configurations. The proposed modelling approach is based on metallurgical transformations using temperature dependent material properties and the enthalpy method. Conduction and keyhole modes welding are investigated using surface and volumetric heat sources, respectively. Transition between the heat sources is carried out according to the power density and interaction time. Simulations are carried out using 3D finite element model on commercial software. The simulation results of the weld shape and dimensions are validated using a structured experimental investigation based on Taguchi method. Experimental validation conducted on a 3 kW Nd: YAG laser source reveals that the modelling approach can provide not only a consistent and accurate prediction of the weld characteristics under variable welding parameters and conditions but also a comprehensive and quantitative analysis of process parameters effects. The results show great concordance between predicted and measured values for the weld joint shape and dimensions.