No abstract

The thorough description of the peculiarities of additively manufactured (AM) structures represents a current challenge for aspiring freeform fabrication methods, such as selective laser melting (SLM). These methods have an immense advantage in the fast fabrication (no special tooling or moulds required) of components, geometrical flexibility in their design, and efficiency when only small quantities are required. However, designs demand precise knowledge of the material properties, which in the case of additively manufactured structures are anisotropic and, under certain circumstances, inhomogeneous in nature. Furthermore, these characteristics are highly dependent on the fabrication settings. In this study, the anisotropic tensile properties of selective laser-melted stainless steel (1.4404, 316L) are investigated: the Young’s modulus ranged from 148 to 227 GPa, the ultimate tensile strength from 512 to 699 MPa, and the breaking elongation ranged, respectively, from 12% to 43%. The results were compared to related studies in order to classify the influence of the fabrication settings. Furthermore, the influence of the chosen raw material was addressed by comparing deviations on the directional dependencies reasoned from differing microstructural developments during manufacture. Stainless steel was found to possess its maximum strength at a 45° layer versus loading offset, which is precisely where AlSi10Mg was previously reported to be at its weakest.

Additive manufacturing has multiple advantages over conventional fabrication techniques, such as the geometrical freedom and, to a great extent, the omission of tooling equipment. Hence, futuristic designs and non-standard topology-optimized structures can be fabricated without causing noteworthy extra cost, since the geometrical complexity is, exaggeratedly spoken, for free. The manufacturing time and the amount of required raw material are the key criteria, which determine the expenses. What at first glance appears as an engineer's dream, introduces its complexity in the description of the material's characteristics and their volatility to the manufacturing conditions. Within this study, the main properties (i.e., surface hardness, tensile, and compression strength, as well as fracture toughness) and their anisotropic and inhomogeneous nature are addressed. Detailed overviews of the progress to date for aluminum, iron, titanium, cobalt, and nickel based raw materials are provided. Furthermore, an overview about the state-of-the-art in the medical sector is included, comprising the areas of utilization and several trail studies.

Additive manufacturing of metal components with laser-powder bed fusion is a very complex process, since powder has to be melted and cooled in each layer to produce a part. Many parameters influence the printing process; however, defects resulting from suboptimal parameter settings are usually detected after the process. To detect these defects during the printing, different process monitoring techniques such as melt pool monitoring or off-axis infrared monitoring have been proposed. In this work, we used a combination of thermographic off-axis imaging as data source and deep learning-based neural network architectures, to detect printing defects. For the network training, a k-fold cross validation and a hold-out cross validation were used. With these techniques, defects such as delamination and splatter can be recognized with an accuracy of 96.80%. In addition, the model was evaluated with computing class activation heatmaps. The architecture is very small and has low computing costs, which means that it is suitable to operate in real time even on less powerful hardware.

Before utilising selective laser melting in real applications, the process as well as the outcome component and its characteristics need to be fully understood. Based on the layer-wise fabrication, with its distinctive orientations in translations and thermal influences within this additive manufacturing process, the obtained material properties and the microstructure are anticipated to be anisotropic. The selective laser melting process involves: the laser movement pattern in plane and rotation between single layers; recoater movement; substrate plate heating and movement; laser irradiation from the top; and inert gas flow. In order to gain insight into the process and its related characteristics, different sets of prismatic specimens in terms of orientation and inclination were produced and evaluated. The evaluation contained surface quality investigations with two independent measurement approaches, i.e. tactile and optical, density measurements based on the Archimedes principle and micro-section evaluation. Furthermore, ultrasonic analyses were conducted to study the feasibility of determining the mechanical properties, i.e. Young's modulus and Poisson's ratio, in accordance with the recorded longitudinal and transversal sonic velocities.The chosen raw material for these investigations was AlSi10Mg and the fabricated parts exhibited a high relative density of at least 99.5 %. Remarkable deviations were evident in the obtained surface quality and clear trends could be determined based on the inclination and orientation condition of the sample during manufacturing. In regards to the ultrasonic investigation, it was found that the reported inherent anisotropy of selective laser melted samples could not be detected with the non-destructive ultrasonic investigation, and destructive procedures, to date, represent the only reliable method to accurately reveal the material characteristics.Keywords: Powder-bed based additive manufacturing / Flushing process / irradiation strategy / Positioning and inclination / Surface quality Im Rahmen der erfolgreichen Implementierung des selektiven Laserstrahlschmelzens in industriellen Anwendungen sind die Kenntnis und das Verständnis der charakteristischen und verfahrensbezogenen Eigenschaften der generierten Kompo-