Nieuwe methoden om de productiviteit van Laser Poederbed Fusie te verhogen

Laser Powder Bed Fusion (LPBF) is one of the most prevalent Additive Manufacturing techniques for metal part fabrication. It operates by depositing thin layers of a metal powder and selectively fusing them, based on the information gathered by digitally slicing a 3D file of the desired geometry. The process allows for more design complexity than traditional manufacturing technologies, enabling advantages in weight reduction, functional integration, and customization. Nevertheless, LPBF components are typically significantly more expensive than traditionally manufactured alternatives, where the major cost driver is the long manufacturing time, often expressed in hours or even days. This manuscript aims to explore three novel methods to enhance LPBF productivity. First, optimal use of multi-laser systems is examined. Instead of the conventional approach of independently operating lasers, this work explores a {synchronized dual laser system. Here, both beams follow the same scan path with a lateral beam offset, in order to develop a single coalesced melt pool. A semi-analytical model was developed to predict the resulting thermal fields, which was validated using high-speed single track experiments, demonstrating good predictive accuracy for the melt width and coalescence, with moderate accuracy on the depth. Owing to its rapid nature, this model enabled the prediction of the optimal beam separation for maximum build rate, indicating that synchronized beams could theoretically operate 2.35 times faster than a single laser system. These results were validated using 3D parts, representing the first demonstration of parallel synchronized scanning on multilayer components. With a maximum build rate increase of 2.32, the synchronized strategy outperforms the theoretical maximum build rate factor of independently operating beams, resulting in a 16% increase in process efficiency per laser. This demonstrates a significant improvement over current operating practices can be achieved by a change in scanning strategy. This was followed by a study of a {Variable Beam Profile laser with in-source beam shaping capabilities. A thermal simulation model was developed to predict the behavior under the various beam profiles and demonstrated adequate model accuracy. The model was validated with single tracks experiments as well as full builds, allowing for the development of process windows for both Gaussian and Ring beams. While Ring beams are known to allow for increased productivity, their shallower melt pools are theorized to limit the maximum layer thickness. The interaction between beam shaping and layer thickness was examined, revealing that the build rate gains of shaped beams are limited to thin powder layers, while small Gaussian beams are better suited for larger layer thicknesses. Additionally, lowering the desired density threshold allowed for increased productivity, and was found to have a more pronounced effect on the performance of shaped beams compared to a Gaussian profile. Combined, this provides a more nuanced understanding of capabilities and limits of beam shaping for LPBF. Finally, the concept of Adaptive Slicing was explored. Although it is known that a larger layer thickness enables increased productivity, the maximum thickness allowed is limited by the surface quality. However, this is most detrimental in near-horizontal surface, implying thicker layers can be used for near-vertical inclinations with minimal loss in part quality. Nevertheless, the use of variable layer thickness within a part, Adaptive Slicing, had not yet been demonstrated for metal LPBF, as it requires an infeasible number of experiments for optimal parameter determination. Therefore, an Autonomous Parameter Generation (APG) algorithm was developed. After calibration, this led to dense parameter sets for 316L stainless steel with a layer thickness distribution varying between 10 and 100 µm. Without further calibration, the APG was capable of predicting suitable parameters for titanium and a CoCr alloy, and was successfully implemented on a commercial system. Furthermore, the model revealed suitable parameter sets at layer thicknesses up to 240 µm. Although geometry dependent, Adaptive Slicing as a software-based approach allowed for doubling the build rate, while a combined approach of AS and Hull/Bulk slicing theoretically increases productivity up to at least 2.8x. In conclusion, each of the examined methods demonstrated a significant increase in process efficiency and build rate compared to conventional strategies, with minimal modifications to machine hardware. The manuscript successfully achieved its objectives by presenting viable options to substantially enhance LPBF productivity. Owing to the effectiveness and efficiency of the proposed methods, these findings reduce the transition gap from academic research to industrial implementation, paving the way for more cost-effective metal additive manufacturing.