The effects of short pulse laser surface cleaning on porosity formation and reduction in laser welding of aluminium alloy for automotive component manufacture

Laser welding of aluminium alloys typically results in porosity in the fusion zones, leading to poor mechanical and corrosion performances. Mechanical and chemical cleaning of surfaces has been used previously to remove contaminants for weld joint preparations. However, these methods are slow, ineffective (e.g. due to hydrogen trapping) or lead to environmental hazards. This paper reports the effects of short pulsed laser surface cleaning on porosity formation and reduction in laser welding of AC-170PX (AA6014) aluminium sheets (coated with Ti/Zr and lubricated using a dry lubricant AlO70) with two types of joints: fillet edge and flange couch, using an AA4043 filler wire for automotive component assembly. The effect of laser cleaning on porosity reduction during laser welding using a filler wire has not been reported before. In this work, porosity and weld fusion zone geometry were examined prior to and after laser cleaning. The nanosecond pulsed Nd:YAG laser cleaning was found to reduce porosity significantly in the weld fusion zones. For the fillet edge welds, porosity was reduced to less than 0.5% compared with 10–80% without laser cleaning. For flange couch welds, porosity was reduced to 0.23–0.8% with laser cleaning from 0.7% to 4.3% without laser cleaning. This has been found to be due to the elimination of contaminations and oxide layers that contribute to the porosity formation. The laser cleaning is based on thermal ablation

In situ radiographic and ex situ tomographic analysis of pore interactions during multilayer builds in laser powder bed fusion

Porosity and high surface roughness can be detrimental to the mechanical performance of laser powder bed fusion (LPBF) additive manufactured components, potentially resulting in reduced component life. However, the link between powder layer thickness on pore formation and surface undulations in the LPBF parts remains unclear. In this paper, the influence of processing parameters on Ti-6Al-4 V additive manufactured thin-wall components are investigated for multilayer builds, using a custom-built process replicator and in situ high-speed synchrotron X-ray imaging. In addition to the formation of initial keyhole pores, the results reveal three pore phenomena in multilayer builds resulting from keyhole melting: (i) healing of the previous layers' pores via liquid filling during remelting; (ii) insufficient laser penetration depth to remelt and heal pores; and (iii) pores formed by keyholing which merge with existing pores, increasing the pore size. The results also show that the variation of powder layer thickness influences which pore formation mechanisms take place in multilayer builds. High-resolution microcomputed tomography images reveal that clusters of pores form at the ends of tracks, and variations in the layer thickness and melt flow cause irregular remelting and track height undulations. Extreme variations in height were found to lead to lack of fusion pores in the trough regions. It is hypothesised that the end of track pores were augmented by soluble gas which is partitioned into the melt pool and swept to track ends, supersaturating during end of track solidification and diffusing into pores increasing their size

Caractérisation, modélisation et maîtrise des porosités créées lors du soudage laser Nd-YAG d'alliages d'aluminium

Les alliages d'aluminium font l'objet d'un intérêt croissant (aéronautique, automobile... ) dans l'optique de réduire le poids des composants et permettre ainsi un gain d'énergie. L'emploi de ces matériaux nécessite de développer des procédés d'assemblage tel que le soudage laser. Ce procédé apparaît prometteur pour les alliages d'aluminium, toutefois on met en évidence des porosités, attribuées à des vaporisations d'éléments alliés, type magnésium, ainsi que de nombreux dégazages. Ces porosités de taille millimétrique sont néfastes à la tenue mécanique des cordons. Lors de cette étude, nous évaluerons la soudabilité sous faisceau laser de deux alliages d'aluminium, respectivement, le 5083 et l'AS7G03. Les facteurs métallurgiques (vaporisation, état de surface) et procédé (dédoublement du faisceau) seront analysés. Pour ce faire, une caractérisation métallurgique (radiographie, densitométrie, duretés) des cordons sera mise en oeuvre ainsi qu'un suivi du procédé (par caméra et pyrométrie).Aluminium alloys have received an increasing interest (aeronautics, car manufacturing) in the view of lightening the structures allowing an economy of energy. The use of these materials needs to develop joining processes as the laser welding. This process seems promising for aluminium alloys. Nevertheless, porosities are evidences attributed to the vaporisation of elements like aluminium and degazing of hydrogen. These porosities are harmful for mechanical properties of the welds. In this study, we will evaluate the weldability by laser beam of two aluminium alloys, respectively, the AA5083 and the A356. The metallurgical factors (vaporisation, surface state) and process parameters (dual beam configuration) will be analysed. A metallurgical characterisation of the welds (X-ray radiographs, densitometry results, hardness) and also a process visualisation would be carried out.LYON-Ecole Centrale (690812301) / SudocSudocFranceF

ANN modelling to optimize manufacturing processes: the case of laser welding

In this work, an artificial neural network (ANN) was implemented to investigate the main effects of process parameters on the laser welding process quality. A high brightness Yb fiber laser was used to carry out the analysis. Full penetration autogenous welding of 6 mm thick AA5754 aluminum alloy sheets was performed in butt configuration. The welding speed and the shielding gas varied in the experimental plan. The process quality was analyzed by visually inspecting the bead appearance. The ANN modeling code was built by Neural Tools (Excel add-in) – Palisade Corporation®. The statistical estimation revealed the relationship of the process parameters with the weld geometry, which provides a deeper understanding of the welding process. Eventually, the usefulness of ANN modeling for optimizing the quality of manufacturing processes was demonstrated