A greedy algorithm for optimal heating in powder-bed-based additive manufacturing

Powder-bed-based additive manufacturing involves melting of a powder bed using a moving laser or electron beam as a heat source. In this paper, we formulate an optimization scheme that aims to control this type of melting. The goal consists of tracking maximum temperatures on lines that run along the beam path. Time-dependent beam parameters (more specifically, beam power, spot size, and speed) act as control functions. The scheme is greedy in the sense that it exploits local properties of the melt pool in order to divide a large optimization problem into several small ones. As illustrated by numerical examples, the scheme can resolve heat conduction issues such as concentrated heat accumulation at turning points and non-uniform melt depths

A greedy algorithm for optimal heating in powder-bed-based additive manufacturing

Powder-bed-based additive manufacturing involves melting of a powder bed using a moving laser or electron beam as a heat source. In this paper, we formulate an optimization scheme that aims to control this type of melting. The goal consists of tracking maximum temperatures on lines that run along the beam path. Time-dependent beam parameters (more specifically, beam power, spot size, and speed) act as control functions. The scheme is greedy in the sense that it exploits local properties of the melt pool in order to divide a large optimization problem into several small ones. As illustrated by numerical examples, the scheme can resolve heat conduction issues such as concentrated heat accumulation at turning points and non-uniform melt depths

Additive Manufacturing (AM) of Metallic Alloys

The introduction of metal AM processes in such industrial sectors as the aerospace, automotive, defense, jewelry, medical and tool-making fields, has led to a significant reduction in waste material and in the lead times of the components, innovative designs with higher strength, lower weight, and fewer potential failure points from joining features. This Special Issue on “Additive Manufacturing (AM) of Metallic Alloys” contains a mixture of review articles and original contributions on some problems that limit the wider uptake and exploitation of metals in AM

Fast and simple creation of powder beds for selective laser melting

In selective laser melting, components are produced by layer-by-layer melting of a powder bed. To investigate the interaction between the powder bed and the laser energy in the process, it is necessary to generate different powder bed configurations with a defined particle size distribution. For this purpose, based on different particle contact approaches, a simple algorithm for planar particle bed configurations was developed in the Julia programming language. Based on the so called 0and 1-particle-contact approaches, a monodisperse sphere packing with a filling ratio of up to 64%, and with a normally distributed particle size with a filling ratio of up to 67% were generated. With the 0-particle-contact approach, the individual powder beds could be generated more quickly, but showed an insufficient degree of filling. In contrast, the 1-particle-contact approach can produce powder beds realistically. An extension for spatial problems, as well as variations in the contact approaches, is given by the simple algorithm design and shall be implemented and further investigated in simulations of selective laser melting

Effects of Alloy Composition and Solid-State Diffusion Kinetics on Powder Bed Fusion Cracking Susceptibility

Laser powder bed fusion (LPBF) has demonstrated its unique ability to produce customized, complex engineering components. However, processing of many commercial Al-alloys by LPBF remains challenging due to the formation of solidification cracking, although they are labelled castable or weldable. In order to elucidate this divergence, solidification cracking susceptibility from the steepness of the solidification curves, specifically |dT⁄dfs1⁄2|, as the fraction solidified nears 1 towards complete solidification, was calculated via Scheil–Gulliver model as a function of solute concentration in simple binary Al-Si, Al-Mg, and Al-Cu systems. Introduction of “diffusion in solid” into Scheil–Gulliver model resulted in a drastic reduction in the cracking susceptibility (i.e., reduction in the magnitude of |dT⁄dfs1⁄2|) and a shift in the maximum |dT⁄dfs1⁄2| to higher concentrations of solute. Overall, the calculated solidification cracking susceptibility correlated well with experimental observation made using LPBF AA5083 (e.g., Al-Mg) and Al-Si binary alloys with varying Si concentration. Cracking susceptibility was found to be highly sensitive to the composition of the alloy, which governs the variation of |dT⁄dfs1⁄2|. Furthermore, experimental observation suggests that the contribution of “diffusion in solids” to reduce the cracking susceptibility can be more significant than what is expected from an instinctive assumption of negligible diffusion and rapid cooling typically associated with LPBF

Homogénéité des surfaces de pièces obtenues par Fabrication Additive

La fabrication additive par fusion d'un lit de poudre fait partie des technologies prometteuses dans le domaine de l'impression 3D. Appliquée aux matériaux métalliques, elle se présente comme une technologie de rupture pour l'industrie. Cependant, l'état de surface des pièces générées par ce procédé présente un aspect rugueux qui peut impacter la fonction ou l'apparence de la pièce. La littérature fait principalement état de l'influence de l'angle de l'axe de fabrication d'une pièce fabriquée par procédé additif sur son état de surface, alors que les traitements thermiques couramment utilisés ont aussi un impact sur l'aspect de la pièce. Les auteurs se proposent d'identifier les paramètres les plus influents concernant la rugosité d'une pièce obtenue par fabrication additive. Il apparaît que le traitement thermique employé peut engendrer des variations de l'ordre de 5% de l'amplitude de la rugosité initiale. En revanche l'emploi de poudre recyclée peut amener des variations de l'état de surface pouvant atteindre 20% de l'amplitude de la rugosité initiale au sein d'une seule pièce et 12% entre plusieurs séries de pièces supposées identiques, en moyenne sur la série