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The mitigation of material defects from additive manufacturing (AM) processes is critical to reliability in their fabricated parts and is enabled by modeling the complex relations between available build monitoring signals and final…
Modeling plays a critical role in additive manufacturing (AM), enabling a deeper understanding of underlying processes. Parametric solutions for such models are of great importance, enabling the optimization of production processes and…
Open-loop control of laser powder bed fusion (LPBF) additive manufacturing (AM) has enabled the production of complex, high-criticality parts for various industries. This method relies on static parameter sets from extensive experimentation…
This study demonstrates the significant effect of the recoil pressure and Marangoni convection in laser powder bed fusion (L-PBF) of 316L stainless steel. A three-dimensional high fidelity powder-scale model reveals how the strong dynamical…
Process optimization for metal additive manufacturing (AM) is crucial to ensure repeatability, control microstructure, and minimize defects. Despite efforts to address this via the traditional design of experiments and statistical process…
Selective Laser Melting (SLM) is a powder-bed additive manufacturing technique whose part quality depends critically on feedstock morphology. However, conventional powder characterization methods are low-throughput and qualitative, failing…
Additive manufacturing is a free-form manufacturing technique in which parts are built in a layer-by-layer manner. Laser powder bed fusion is one of the popular techniques used to fabricate metal parts. However, it induces residual stress…
Additive manufacturing (AM) of metallic components promises many advantages over conventional manufacturing processes through high design flexibility across multiple length scales and precision coupled with an astonishing combination of…
Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and…
A major goal of materials design is to find material structures with desired properties and in a second step to find a processing path to reach one of these structures. In this paper, we propose and investigate a deep reinforcement learning…
The effectiveness of machine learning in metallographic microstructure segmentation is often constrained by the lack of human-annotated phase masks, particularly for rare or compositionally complex morphologies within the metal alloy. We…
Efficient simulation of Laser Powder Bed Fusion (LPBF) is crucial for process prediction due to the lasting issue of high computational cost associated with traditional numerical methods such as finite element analysis (FEA). While a…
Predicting the microstructure during selective laser sintering (SLS) is of great interests, which can compliment the current time and cost expensive trial-and-error principle with an efficient computational design tool. However, it still…
Additive manufacturing technologies enable the production of complex and bioinspired shapes using magneto-responsive materials, which find diverse applications in soft robotics. Particularly, the development of composites with controlled…
Additive manufacturing (AM) techniques hold promise but face significant challenges in process planning and optimization. The large temporal and spatial variations in temperature that can occur in layer-wise AM lead to thermal excursions,…
The stochastic formation of defects during Laser Powder Bed Fusion (L-PBF) negatively impacts its adoption for high-precision use cases. Optical monitoring techniques can be used to identify defects based on layer-wise imaging, but these…
Powder Bed Fusion (PBF) is a type of Additive Manufacturing (AM) technology that builds parts in a layer-by-layer fashion out of a bed of metal powder via the selective melting action of a laser or electron beam heat source. The technology…
Laser powder bed fusion (LPBF) is an additive manufacturing (AM) technology. To achieve high product quality, the powder is best spread as a uniform, dense layer. The challenge for LPBF manufacturers is to develop a spreading process that…
Qualification of high-performance metal components produced by laser powder bed fusion (LPBF) must identify process-induced porous defects that reduce ductility and nucleate fatigue cracking. Detecting such defects via optical monitoring of…
Foundation models are at the forefront of an increasing number of critical applications. In regards to technologies such as additive manufacturing (AM), these models have the potential to dramatically accelerate process optimization and, in…