The geometrical process conditions of thin foils in laser cutting result in higher local surface tension forces, increasing the susceptibility to dross attachment. Drop-like dross formation patterns and modes in laser cutting of 100 μm thin stainless steel foils were investigated using high-speed imaging and run length analysis. Laser power and cutting speed significantly influenced dross formation. Three distinct dross patterns were identified: an alternating side pattern, single-sided formation, and irregular formations on both sides. These patterns, observed via bottom-view high-speed imaging, correspond to the three melt flow modes A, S, and I respectively, each associated with different line energy regimes. Mode S tends to occur at low line energy, with about 3 ms duration until drop completion, while Mode A is more likely at high line energy, with about 18 ms completion time. A run length was introduced, where analysis revealed up to 36 consecutive dross deposits within the single-sided formation pattern. The preferred movement of the melt, either to the one or to the other cut edge, is based on details of the complex fluid mechanics, which could partially be explained, aided by high-speed imaging. Occasional drop merging events were observed during single-sided formation when molten dross remained in contact with a newly formed drop before solidification. Dross diameter and kerf width were measured, as key criteria for controlled laser cutting. These findings offer new insights into how process parameters govern dross behavior in thin-sheet laser cutting, aiming to keep one side dross-free.

Schlieren monitoring techniques were applied to Laser Directed Energy Deposition (L-DED) and Laser Cladding (LC) processes to evaluate their performance in capturing thermal dynamics and spatter formation under varying process parameters. Two schlieren setups were compared based on their ability to detect changes in temperature, pressure and material state within the process zone. The first, using a background-oriented design, exhibited higher resolution and sensitivity to local thermal gradients and plume dynamics, while the second, with a broader field of view, demonstrated enhanced stability in monitoring cumulative thermal buildup. Optical flow analysis revealed a strong correlation between line energy and the magnitude of optical turbulence, particularly in regions where vaporization occurred, with a clear plateau observed between 110.6 J/mm and 243.9 J/mm, corresponding to optimal melt pool conditions. Beyond 243.9 J/mm, a significant increase in optical flow was observed, indicating plasma formation and enhanced turbulence. A dome-like schlieren structure consistently formed above the melt pool, expanding with higher energy input, offering insights into the balance between thermal buoyancy and vapor pressure. Additionally, the quadratic relationship between line energy and the schlieren dome volume of enclosed optical flow provided a means to identify energy-efficient and stable process conditions. The findings underscore the potential of schlieren-based monitoring for precise control and optimization of additive manufacturing processes, with implications for improving process stability and minimizing defects like spatter and porosity.

Real-time process monitoring is essential for ensuring stability and defect control in directed energy deposition - laser beam/metal (DED-LB/M). Schlieren imaging has proven to be a valuable tool for detecting refractive index variations in the process zone, providing insights into gas flow behaviour, shielding gas efficiency and process plume dynamics. However, schlieren imaging typically requires specialized optical setups, making integration into industrial systems challenging. This study explores an artificial intelligence-driven cross-modality transfer approach that enables the prediction of schlieren-induced refractive index variations from coaxial imaging data, eliminating the need for a dedicated schlieren setup. A background-oriented schlieren system was used to capture reference data, while a coaxial camera recorded the melt pool and surrounding process zone during DED-LB/M. A machine learning model was trained on the combined dataset, establishing correlations between schlieren activity and intensity variations in the coaxial images. The model successfully predicted schlieren-induced disturbances, allowing for the indirect detection of gas flow instabilities and shielding gas deficiencies. The results demonstrate that artificial intelligence-based analysis of coaxial imaging can provide schlieren-equivalent process information, making it possible to monitor refractive index variations, detect process deviations and improve defect prediction in real time. This approach enhances process monitoring capabilities in DED-LB/M, enabling cost-effective, scalable and easily integrable monitoring solutions for industrial applications.

A schlieren system, adapted for Laser Directed Energy Deposition, was used to monitor and analyze the process zone under various conditions, including deliberate contamination and parameter limits. This approach enabled the identification and correlation of process-induced defects with schlieren phenomena. Events and zones were characterized and qualitative categorized to validate schlieren monitoring as a diagnostic tool. Notably, a highly active and spatially confined schlieren formation was consistently observed above the melt pool. Using a tailored schlieren optical setup and simulations, schlieren patterns were linked to refractive index changes in process gases, enabling quantitative analysis. The refractive index within the hot gas dome over the molten pool was observed to range from 1.00000712 to 1.00875126, with fluctuation speeds reaching up to 210 m/s. As a result, a model was developed to describe the impact of refractive index dynamics on the performance of coaxial monitoring systems in laser processes. A case study using an exemplary imaging monitoring system demonstrated that schlieren phenomena can cause wavelength-dependent lateral geometric shifts of up to 228 µm, significantly affecting the accuracy of object-based monitoring outcomes. The findings offer critical insights into the complex interplay between refractive index variations and monitoring results, paving the way for refined monitoring strategies that enhance reliability and precision in laser cladding applications.

Metal additive manufacturing using powder sheets (MAPS) melts powder attached in a sheet with a polymer binder, avoiding risks of loose powders in material waste, safety and health during laser additive manufacturing among other for e-mobility applications. However, this concept remains challenging for aluminum alloys due to occurring defects. To address this challenge, the mass transfer and defect formation mechanism during MAPS-AlSi10Mg were investigated using high-speed imaging and metallographic observations. The results showed that the mass transfer is realized via droplets formed first from the powder sheet in front of the melt pool and their incorporations into the melt pool. However, a much laser defocusing significantly inhibits the droplets’ incorporation into the melt pool and promotes the balling. Polymer coatings or it wrapped into the AlSi10Mg droplets, generates the inclusions once the droplets were incorporated into the melt pool. Furthermore, under the laser beam in focus, the large particle-size powder sheet, powder side up or low scanning speed easily induce pores via shielding gas/polymer vapor inclusion. The laser defocusing of +15 mm, average laser intensity of  W/cm2, and binder side up induce defect-free tracks, owing to the complete removal of polymers by their sufficient evaporation and powder agglomeration spatters. This work unveils that the droplets’ incorporation into melt pool leads to the mass transfer of MAPS-AlSi10Mg while the droplets containing polymers and gas/vapor inclusion generate inclusions and pores. Meanwhile, the defect-free production strategy of suitable defocusing and high laser intensity is proposed.

This research delves into the intricate melt flow dynamics observed in asymmetric stainless steel 316L T-joints with dual-beam laser welding, with a particular focus on configurations involving sheets inclined at angles up to 45°. Given the complexity of this welding scenario, the use of filler wire is necessitated, which is only accessible from the top side in this case. To capture the transient melt pool phenomena high-speed imaging techniques (HSI) were employed at both the top and root of the weld. Through HSI observations along with streak analysis, three primary mechanisms were identified: Atypical-flow connection-root and top side, atypical-flow connection-top side and typical-flow disconnection-root side. These observations highlight several critical factors, at the top and bottom of the weld, including intermittent keyhole openings, transient melt flow effects, potential spatter ejection, reabsorption, pronounced bulge and disintegration. These phenomena collectively contribute to weld imperfections, revealing impacts on meandering root and craters. The study provides a comprehensive understanding of 3D asymmetric melt flow dynamics. By categorizing the observed mechanisms, this research is theoretically described and formulated in a systematic flowchart, for laser welding of an asymmetric T-joint. 

Several numerical and analytical methods were developed over the years in the attempt to properly model the keyhole laser welding. Among them, semi-analytical models revealed to be effective and efficient for the calculation of the keyhole geometry. They can take into account the plasma absorption mechanism through inverse Bremsstrahlung, as well as the effects related to the multiple reflection phenomena that the laser beam rays experience in the keyhole cavity, with relatively low computational costs. However, multiple reflections contribution was usually calculated through a very simple average estimation. In this work, a semi-analytical model that employs an iterative ray-tracing technique for the calculation of multiple reflections inside the keyhole is described. The approach can take precisely into account the absorption mechanism for each laser beam ray along its segmented path in the keyhole considering also the commonly neglected-upward oriented reflections. The energy transferred to the molten material due to all the rays hitting the keyhole wall is locally considered for the energy balance and the keyhole is recalculated iteratively until the profile does not significantly deviate from the previous one. The laser beam attenuation due to the plasma plume that develops above the keyhole is also considered, for a CO2-laser, investigating different plume height values. A numerical-experimental comparison considering two different laser welding setups is then performed. The results show that both the upward-oriented reflections and the plasma plume damping have noticeable effects on the cavity shape and depth, while the numerical-experimental comparison reveals that the model is able to predict keyhole depths, especially for welding configurations with higher heat input values. 

This study presents an approach for in-situ monitoring of laser powder bed fusion. Using standard laser optics, coaxial high-resolution multispectral images of powder beds are acquired in a pre-objective scanning configuration. A continuous overview image of the entire 114 × 114 mm powder bed can be generated, detecting objects down to 20 µm in diameter with a maximum offset of 22–49 µm. Multispectral information is obtained by capturing images at 6 different wavelengths from 405 nm to 850 nm. This allows in-line determination of the absorbance of the powder bed with a maximum deviation of 2.5% compared to the absorbance spectra of established methods. For the qualification of this method, ray tracing simulations on powder surfaces and tests with 20 different powders have been carried out. These included different particle sizes, aged and oxidized powders.

Laser-induced ablation of drops from a metal wire enables the sequential deposition of voxels, for additive manufacturing. Striving for the goal of controlled, reproducible drop transfer, for this new technique, further trends and phenomena have been studied. Different modes of drop growth along with necking have been observed. Rather reproducible was a growing pending drop underneath the wire tip until separation for a certain size. In contrast, initial transients from the laser-induced recoil pressure can lead to a quick separation of a smaller drop. Initiation of a swinging cycle can also cause drop ablation after one cycle. For too fast wire feeding, the wire underpins the melt for a while in a spoon-like manner. Apart from the drop size, the different modes affect the scatter of the flight trajectory and landing position, as important optimization criteria, for controlled 3D-printing.

This study investigates melt flow dynamics in asymmetric T-joint laser welding, particularly with sheets inclined up to 45°. This complex scenario requires filler wire, accessible only from the flat sheet side. High-speed imaging at the top and root captures transient phenomena leading to weld imperfections. Research on stainless-steel involved the impact of first-order welding parameters on the weld quality. This included multi-spot laser welding with two beams. The analysis focused on melt pool dynamics under these challenging conditions. The asymmetric root side’s geometry necessitates proper melt flow to form a favorable root topology, avoiding defects like wavy roots and porosity. Key observations included intermittent keyhole openings, transient melt flow effects, and potential spatter ejection at the bottom. The findings offer a comprehensive understanding of 3D asymmetric melt flow, laying the analytical groundwork for enhancing the weld quality.