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Lattice structures in additive manufacturing of 316L stainless steel have gained increasing attention due to their well-suited mechanical properties and lightweight characteristics. Infill structures such as honeycomb, lattice, and gyroid have shown promise in achieving desirable mechanical properties for various applications. However, the design process of these structures is complex and time-consuming. In this study, we propose a machine learning-based approach to optimize the design of honeycomb, lattice, and gyroid infill structures in 316L stainless steel fabricated using laser powder bed fusion (L-PBF) technology under different loading conditions. A dataset of simulated lattice structures with varying geometries, wall thickness, distance, and angle using a computational model that simulates the mechanical behavior of infill structures under different loading conditions was generated. The dataset was then used to train a machine learning model to predict the mechanical properties of infill structures based on their design parameters. Using the trained machine learning model, we then performed a design exploration to identify the optimal infill structure geometry for a given set of mechanical requirements and loading conditions. Finally, we fabricated the optimized infill structures using L-PBF technology and conducted a series of mechanical tests to validate their performance under different loading conditions. Overall, our study demonstrates the potential of machine learning-based approaches for efficient and effective designing of honeycomb, lattice, and gyroid infill structures in 316L stainless steel fabricated using L-PBF technology under different loading conditions. Furthermore, this approach can be used for dynamic loading studies of infill structures.

Powder bed fusion of metals using laser beam (PBF-LB/M) is a commonly used additive manufacturing process for the production of high-performance metal parts. AlSi10Mg is a widely used material in PBF-LB/M due to its excellent mechanical and thermal properties. However, the part quality of AlSi10Mg parts produced using PBF-LB/M can vary significantly depending on the process parameters. This study investigates the use of machine learning (ML) algorithms for the prediction of the resulting part density of AlSi10Mg parts produced using PBF-LB/M. An empirical data set of PBF-LB/M process parameters and resulting part densities is used to train ML models. Furthermore, a methodology is developed to allow density predictions based on simulated meltpool dimensions for different process parameters. This approach uses finite element simulations to calculate the meltpool dimensions, which are then used as input parameters for the ML models. The accuracy of this methodology is evaluated by comparing the predicted densities with experimental measurements. The results show that ML models can accurately predict the part density of AlSi10Mg parts produced using PBF-LB/M. Moreover, the methodology based on simulated meltpool dimensions can provide accurate predictions while significantly reducing the experimental effort needed in process development in PBF-LB/M. This study provides insights into the development of data-driven approaches for the optimization of PBF-LB/M process parameters and the prediction of part properties.

Filament-based material extrusion (MEX/M) presents a rapid and inexpensive alternative to e.g. metal injection molding, particularly for prototype production. The filament consists of metal powder in a plastic matrix and is melted and applied layer by layer until a so-called green body is created. These green parts are subsequently debinded and sintered at high temperatures to form a dense metal component. It is crucial to identify the material-specific and process-specific limits in order to be able to manufacture true to size. This paper therefore develops design guidelines for the MEX/M process for green part manufacturing for the widely used austenitic stainless steel AISI 316L (1.4404). Basic geometrical features such as walls, boreholes and overhangs are studied and influencing factors on the dimensional accuracy are assessed. Based on the results, recommendations for part design are presented.

Piston-based material extrusion enables cost savings for metal injection molding users when it is utilized as a complementary shaping process for green parts in small batch sizes. This, however, requires the use of series feedstock and the production of sufficiently dense green parts in order to ensure metal injection molding-like material properties. In this paper, a methodological approach is presented to identify material-specific process parameters for an industrially used Ti-6Al-4V metal injection molding feedstock based on the extrusion force. It was found that for an optimum extrusion temperature of 95 °C and printing speed of 8 mm/s an extrusion force of 1300 N ensures high-density green parts without under-extrusion. The resulting sintered part properties exhibit values comparable to metal injection molding in terms of part density (max. 99.1%) and tensile properties (max. yield strength: 933 MPa, max. ultimate tensile strength: 1000 MPa, max. elongation at break: 18.5%) depending on the selected build orientation. Thus, a complementary use could be demonstrated in principle for the Ti-6Al-4V feedstock., Piston-based material extrusion enables cost savings for metal injection molding users when it is utilized as a complementary shaping process for green parts in small batch sizes. This, however, requires the use of series feedstock and the production of sufficiently dense green parts in order to ensure metal injection molding-like material properties. In this paper, a methodological approach is presented to identify material-specific process parameters for an industrially used Ti-6Al-4V metal injection molding feedstock based on the extrusion force. It was found that for an optimum extrusion temperature of 95 °C and printing speed of 8 mm/s an extrusion force of 1300 N ensures high-density green parts without under-extrusion. The resulting sintered part properties exhibit values comparable to metal injection molding in terms of part density (max. 99.1%) and tensile properties (max. yield strength: 933 MPa, max. ultimate tensile strength: 1000 MPa, max. elongation at break: 18.5%) depending on the selected build orientation. Thus, a complementary use could be demonstrated in principle for the Ti-6Al-4V feedstock., Bundesministerium für Wirtschaft und Energie - BMWi

Additive manufacturing (AM) has been leveraged across various industries to potentially open design spaces allowing the design of parts to reduce the weight, cost, and integrated design. Over the past decade, AM has sped up fast enough to penetrate various industry offering potential solutions for multiple materials, such as metals, alloys, plastics, polymers, etc. However, challenges lie to best utilize the opened design spaces as current generation engineers are trained to design parts for the conventional manufacturing process. With this lack of design guidelines for the AM process, users are limiting themselves to best utilize the offering made by advanced manufacturing. For aerospace parts, the design freedom of additive manufacturing is attractive mainly for two purposes: for weight reduction through lighter, integrated design concepts as well as for functional optimization of parts aiming at an increase of performance, e.g., by optimizing flow paths. For both purposes, it is vital to understand the material-specific and manufacturing process design limits. In AM, combination of each material and manufacturing process defines the design space by influencing minimum thickness, angle, roughness, etc. This paper outlines a design guideline for the laser powder bed fusion (also DMLM, direct metal laser melting) AM process with Inconel 718 material. Inconel 718 is a superalloy with superior mechanical properties and corrosion resistance at elevated temperatures up to 700 °C and is, therefore, used in several applications including aerospace engine parts. Due to its weldability, the alloy has also been extensively investigated in laser powder bed fusion and other additive manufacturing processes. A comprehensive study is provided both analytically and experimentally suggesting how parts can be designed having critical design features, manufacturing direction/orientation to meet design requirements, design accuracy, and quality. Design features presented include wall

Support structures are essential to laser powder bed fusion (PBF-LB/M). They sustain overhangs, prevent distortion, and dissipate process-induced heat. Their removal after manufacturing is required, though, increasing the overall costs. Therefore, optimization is important to increase the economic efficiency of PBF-LB/M. To enable optimization focused on the support structures’ costs, a cost model is developed. The whole production process, including the design, manufacturing, and post-processing of a part, is considered by deriving formulas for the individual costs. The cost model is applied to a previously developed benchmark procedure. Additionally, a case study investigating different support layout strategies is conducted.

Additive manufacturing (AM) has been leveraged across various industries to potentially open design spaces allowing the design of parts to reduce the weight, cost, and integrated design. Over the past decade, AM has sped up fast enough to penetrate various industry offering potential solutions for multiple materials, such as metals, alloys, plastics, polymers, etc. However, challenges lie to best utilize the opened design spaces as current generation engineers are trained to design parts for the conventional manufacturing process. With this lack of design guidelines for the AM process, users are limiting themselves to best utilize the offering made by advanced manufacturing. For aerospace parts, the design freedom of additive manufacturing is attractive mainly for two purposes: for weight reduction through lighter, integrated design concepts as well as for functional optimization of parts aiming at an increase of performance, e.g., by optimizing flow paths. For both purposes, it is vital to understand the material-specific and manufacturing process design limits. In AM, combination of each material and manufacturing process defines the design space by influencing minimum thickness, angle, roughness, etc. This paper outlines a design guideline for the laser powder bed fusion (also DMLM, direct metal laser melting) AM process with Inconel 718 material. Inconel 718 is a superalloy with superior mechanical properties and corrosion resistance at elevated temperatures up to 700 °C and is, therefore, used in several applications including aerospace engine parts. Due to its weldability, the alloy has also been extensively investigated in laser powder bed fusion and other additive manufacturing processes. A comprehensive study is provided both analytically and experimentally suggesting how parts can be designed having critical design features, manufacturing direction/orientation to meet design requirements, design accuracy, and quality. Design features presented include wall

Industrialization of directed energy deposition (DED) process relies on the development and implementation of a quality assurance system that makes the process reliable and repetitive. One of the geometrical characteristics that needs constant monitoring and control during any DED process is the height of the deposited layer. In this paper, a multidirectional layer height monitoring system relying on the laser triangulation principle that has been developed for real-time direct measurement, in contrast to the majority of the sensor systems that derive layer height based on melt pool temperature, is presented. Existing commercial laser triangulation systems are unidirectional, which hinder the flexibility of the material handling system, like industrial robot, in most of the cases. An additional challenge lies on the integration with the deposition head due to its form, size, and extreme working conditions. Therefore, a novel configuration of laser triangulation sensors that enable multidirectionality and limit shadowing effect has been developed at Fraunhofer IAPT. In this paper, the development of such a sensor with a focus on the mechanical design has been presented. The sensor is designed for operation at high temperature and harsh environmental conditions close to the build zone. The developed sensor has been successfully tested for the powder-based laser metal deposition system. In-process layer height measurement and control are possible with this sensor, thereby enabling digitalization and quality assurance during the build process. 3D point cloud generated using this sensor can be used for the dimensional deviation measurement and also for downstream processes like machining. Such an in-process quality measurement and assurance system negates a postmeasurement step, thereby saving cost and time and ensuring quality.

Laser powder bed fusion (PBF-LB/M) of metals belongs to the advanced additive manufacturing processes on the brink of industrialization. Successful manufacturing often requires the utilization of support structures to support overhangs, dissipate heat, and prevent distortion due to residual stresses. Since the support structures result in increased costs, research, as well as industry, aim at optimizing the application of those or the support structures themselves. New approaches are validated with individual use cases, though, preventing an objective comparison of optimization strategies. This paper contributes to the advance of support structure optimization by providing a benchmark strategy including part geometries, which enables to evaluate technical as well as economical aspects of support structures or support strategies. The benchmark process is demonstrated with the help of the currently most used block and pin support structures.

The ductility of the Al alloys produced by additive manufacturing (AM) has become a critical property, as the AM Al alloys are increasingly used in the automotive industry. However, the ductility of as-built AM Al alloys is relatively low, even with optimized AM conditions. The post-annealing treatment provides an efficient way to improve ductility. Previous investigation has shown that the annealed AM AlSi3.5Mg2.5 alloy possesses superior ductility. However, the plastic deformation micro-mechanisms of the annealed AM AlSi3.5Mg2.5 alloy remain unclear. In this study, in-situ neutron diffraction was employed to explore the annealed AM AlSi3.5Mg2.5 alloy. The evolutions of phase stresses, dislocation density, and crystallite size in the annealed AM AlSi3.5Mg2.5 alloy during tensile deformation were analyzed. The experimental investigation reveals that the dislocation density in the Al matrix of the annealed AM AlSi3.5Mg2.5 alloy increases slowly in the early plastic deformation stage, and it reaches a saturated level upon the following uniform deformation. The crystallite size decreases quickly in the early deformation stage, and then it decreases slowly. The Kocks-Mecking model and the Voce model can capture the strain hardening behavior well. The determined physical constitutive equations can be applied in continuum mechanical computer simulations., Bundesministerium für Bildung und Forschung (BMBF), Fraunhofer Cluster of Excellence “Programmable Materials” (CPM)

Today’s smart devices come equipped with powerful hard- and software-enabling professional use cases. The latest hardware by Apple utilizes LiDAR and TrueDepth, which offer the capability of 3D scanning. Devices equipped with these camera systems allow manufacturers to obtain 3D data from their customers at low costs, which potentially enables time-efficient mass customization and product differentiation strategies. However, the utilization is limited by the scanning accuracy. To determine the potential application of LiDAR and TrueDepth as a 3D scanning solution, in this paper an evaluation was performed. For this purpose, different Lego bricks were scanned with the technologies and an industrial 3D scanner. The results were compared according to shape and position tolerances. Even though the industrial 3D scanner consistently delivered more accurate results, the accuracy of the smart device technologies may already be sufficient, depending on the application., Today’s smart devices come equipped with powerful hard- and software-enabling professional use cases. The latest hardware by Apple utilizes LiDAR and TrueDepth, which offer the capability of 3D scanning. Devices equipped with these camera systems allow manufacturers to obtain 3D data from their customers at low costs, which potentially enables time-efficient mass customization and product differentiation strategies. However, the utilization is limited by the scanning accuracy. To determine the potential application of LiDAR and TrueDepth as a 3D scanning solution, in this paper an evaluation was performed. For this purpose, different Lego bricks were scanned with the technologies and an industrial 3D scanner. The results were compared according to shape and position tolerances. Even though the industrial 3D scanner consistently delivered more accurate results, the accuracy of the smart device technologies may already be sufficient, depending on the application.

To overcome current limitations in laser remote processing of large-scale sheet and plate metal applications, an automated laser remote scanner (LRS) with a 30 kW laser power has been developed. Due to the high laser power, an unacceptable focus shift occurs at the processing location, mainly generated by the fused silica optics. A computationally efficient real-time focus shift compensation and control of the focus position have been investigated and are presented. In the first section, the 30 kW LRS concept is briefly introduced. Section two explains the focus shift effect and presents its impact on manufacturing scenarios in welding and cutting. The third section highlights significant effects accounted for: thermo-optical, stress-optical, geometric, and ambient. A set of simulated data of temperature, refractive index, and focus shift profiles have been generated in section four and model the performance of the 30 kW LRS. The results are discussed and a summary is given.

© 2020 The Authors. Published by Wiley-VCH GmbH In chemical process engineering, fast gas-liquid reactions often suffer from an inefficient distribution of gas and therefore mixing and mass transfer performance. This study deals with the possibility of influencing the local gas holdup and bubble size distribution in a gas-liquid process using additively manufactured lattice structures (AMLS). The used measuring technique to study bubble size, velocity, and the local gas holdup is a photo-optical needle probe. By using AMLS, a significant radial homogenization of the local gas holdup and the mean bubble size is achieved. Furthermore, it can be demonstrated that the bubble size can be tailored by the geometry of the inserted structure. It is illustrated that the mean bubble velocities are lowered within the lattice resulting in a higher residence time of the dispersed phase with an impact on the mass transfer performance within the AMLS.

© 2014 The Authors. Published by Elsevier B.V. Laser Additive Manufacturing (LAM) enables economical production of complex lightweight structures as well as patient individual implants. Due to these possibilities the additive manufacturing technology gains increasing importance in the aircraft and the medical industry. Yet these industries obtain high quality standards and demand predictability of material properties for static and dynamic load cases. However, especially fatigue and crack propagation properties are not sufficiently determined. Therefore this paper presents an analysis and simulation of crack propagation behavior considering Laser Additive Manufacturing specific defects, such as porosity and surface roughness. For the mechanical characterization of laser additive manufactured titanium alloy Ti-6Al-4V, crack propagation rates are experimentally determined and used for an analytical modeling and simulation of fatigue. Using experimental results from HCF tests and simulated data, the fatigue and crack resistance performance is analyzed considering material specific defects and surface roughness. The accumulated results enable the reliable prediction of the defects influence on fatigue life of laser additive manufactured titanium components.

Delamination is a major problem in contour milling of fiber reinforced plastics (FRP) causing scrap or rework. Today, delamination avoidance limits overall productivity and tool life. Damage of the top layer of a composite structure is initiated if fibers are not cut during first engagement of the cutting edge, but deflected. Generated cracks propagate due to recurrent contact of fibers with the rotating tool. In contrast, when laser cutting FRP, the heat input often leads to an extensive heat-affected zone (HAZ), particularly in case of large laminate thickness and high energy input. Combination of both processes is a promising approach to overcome the mentioned disadvantages. Experiments indicate that pre-scoring of the top layer is possible with negligible HAZ for FRP materials using proper laser parameters, especially low energy input per unit length. Positioning of the laser scored kerf along the contour to be manufactured by the subsequent milling tool prevents crack propagation along the fiber direction even with a heavily worn milling tool at increased feed rate. Furthermore, laser pre-scoring eliminates protruding fibers and allows for edge chamfering. The process understanding is enhanced using simulation of the laser pre-scoring, particularly considering heat conduction and forced convection, as well as by presenting a model for the mechanism of delamination prevention.

In der vorliegenden Dissertation “Qualification of SLM - Additive Manufacturing for Aluminium Alloys” wird die Eignung von Aluminiumlegierungen für die additive Fertigungstechnik Selektives Laserstrahlschmelzen (SLM) betrachtet. Der SLM - Prozess bietet Abkühlraten, die völlig neue Optionen für Aluminiumlegierungen ermöglichen. Die Untersuchungen vertiefen das wissenschaftliche Verständnis der, auf das SLM Verfahren zugeschnittenen, Al-Legierungen Scalmalloy und SilmagAl. Verschiedene Aspekte der Prozesskette werden hinsichtlich der Definition von Pulver- und Materialspezifikationen für Luft- und Raumfahrtanwendungen beschrieben, analysiert und diskutiert. Prozessbeeinflussende Pulvereigenschaften werden identifiziert und Möglichkeiten zur Charakterisierung werden diskutiert. Der additiv gefertigte Werkstoff beider Legierungen wird umfassend auf dessen mechanische und physikalische Eigenschaften untersucht. Damit wird der Reifegrad dieser beiden Aluminiumlegierungen erhöht um die zeit- und kostenintensive Luft- und Raumfahrtqualifikationen zu beschleunigen. Prozesswege werden identifiziert mit denen die vorgeschlagenen Materialspezifikationen für verschieden Bauteil aus der Flugzeugstrukur erreicht werden können., The present Thesis "Qualification of SLM - Additive Manufacturing for Aluminium Alloys" considers the suitability of two aluminum alloys for the additive manufacturing technique Selective Laserbeam Melting (SLM). High cooling rates can be realised in SLM which allow the use of the tailored Al-alloy options Scalmalloy and SilmagAl. The investigations deepen the scholarly understanding of processing both alloys in SLM. Different aspects of the process chain are described, analysed and discussed with regard to define powder and material specifications for aerospace applications. Main process influencing powder characteristics are identified and characterising techniques are discussed. The additive manufactured material of both alloys is comprehensively investigated regarding mechanical and physical properties. As result, different processing routes are identified which aim to meet the final proposed material specification for principle structural elements (PSE) and non-principle structural elements (non-PSE) in aerospace qualifications.

Additive Metal Deposition (AMD) is an additive manufacturing process building parts based on a nozzle-fed powder by laser assisted solidification. The AMD technology offers unique advantages for the production of near net-shape parts. In contrast to the powder bed-based technologies it provides a high productivity grade. Today AMD lacks reproducible process strategies manufacturing large parts in narrow tolerances. The building height of a single layer and the geometrical shape of a whole part alter progressively with increasing part dimensions - consecutively leading to a higher effort in the manufacturing-process development for such parts. To reduce this effort, in this paper first an iterative identification of optimal process parameters is performed by following an evolutionary algorithm under varied BC. Based on the geometry-related parameter sets, tolerances are defined. The process strategies and tolerances are validated for a prototype application considering the defined quality aims. Finally the results are discussed and summarized in an a-priori process design guideline for AMD Ti6Al4V-parts.

Laser melting of titanium material, e.g. Ti-6Al-4V, offers great potential in manufacturing automotive components, lightweight structures and medical implants. In order to achieve required mechanical properties of laser melted components quality of powder materials is essential. Unmelted powder is recycled and reused in a subsequent process. Due to repeated recycling it is suggested that powder material changes. In this paper aging processes of Ti-6Al-4V powder are studied. It was observed that powder particles coarsen and flowability increases. Comparing examined powder characteristics to bulk material properties it was noticed that there are significant effects of aged powder on laser melted components.

Additive Manufacturing technology, such as Selective Laser Melting, allows fabrication of complex metal parts with freeform surfaces. Using biocompatible metal alloys, e.g. TiAl6V4, medical implants can be produced. To increase osseointegrative behavior the ability to fabricate filigree lattice structures can be utilized to achieve a modified implant surface. In order to increase dimensional accuracy when applying a lattice structure on a curved surface, process constraints for single lattice bars are studied. The investigated lattice structure was thereupon applied on the surface of a medical implant. © 2011 Published by Elsevier Ltd.