Additive manufacturing, especially material extrusion (MEX), has received a lot of attention recently. The reasons for this are the numerous advantages compared to conventional manufacturing processes, which result in various new possibilities for product development and -design. By applying material layer by layer, parts with complex, load-path optimized geometries can be manufactured at neutral costs. To expand the application fields of MEX, high-strength and simultaneously lightweight materials are required which fulfill the requirements of highly resilient technical parts. For instance, the embedding of continuous carbon and flax fibers in a polymer matrix offers great potential for this. To achieve the highest possible variability with regard to the material combinations while ensuring simple and economical production, the fiber–matrix bonding should be carried out in one process step together with the actual parts manufacture. This paper deals with the adaptation and improvement of the 3D printer on the one hand and the characterization of 3D printed test specimens based on carbon and flax fibers on the other hand. For this purpose, the print head development for in-situ processing of contin uous fiber-reinforced parts with improved mechanical properties is described. It was determined that compared to neat polylactic acid (PLA), the continuous fiber-reinforced test specimens achieve up to 430% higher tensile strength and 890% higher tensile modulus for the carbon fiber reinforcement and an increase of up to 325% in tensile strength and 570% in tensile modulus for the flax fibers. Similar improvements in performance were achieved in the bending tests.

A proven method to enhance the mechanical properties of additively manufactured plastic parts is the embedding of continuous fibers. Due to its great flexibility, continuous fiber-reinforced material extrusion allows fiber strands to be deposited along optimized paths. Nevertheless, the fibers have so far been embedded in the parts contour-based or on the basis of regular patterns. The outstanding strength and stiffness properties of the fibers in the longitudinal direction cannot be optimally utilized. Therefore, a method is proposed which allows to embed fibers along the principal stresses into the parts in a load-oriented manner. A G-code is generated from the calculated principal stress trajectories and the part geometry, which also takes into account the specific restrictions of the manufacturing technology used. A distinction is made between fiber paths and the matrix so that the average fiber volume content can be set in a defined way. To determine the mechanical properties, tensile and flexural tests are carried out on specimens consisting of carbon fiber-reinforced polyamide. In order to increase the influence of the principal stress-based fiber orientation, open-hole plates are used for the tensile tests, as this leads to variable stresses across the cross section. In addition, a digital image correlation system is used to determine the deformations during the mechanical tests. It was found that the peak load of the optimized open-hole plates was greater by a factor of 3 and the optimized flexural specimens by a factor of 1.9 than the comparison specimens with unidirectional fiber alignment.

An existing challenge in the use of continuous fiber reinforcements in additively manufactured parts is the limited availability of suitable fiber materials. This leads to a reduced adaptability of the mechanical properties to the load case. The increased design freedom of additive manufacturing allows the flexible deposition of fiber strands at defined positions, so that even different fiber materials can be easily combined in a printed part. In this work, therefore, an approach is taken to combine carbon and aramid fibers in printed composite parts to investigate their effects on mechanical properties. For this purpose, tensile, flexural and impact tests were performed on printed composite parts made of carbon and aramid fibers in a nylon matrix with five different mixing ratios. The tests showed that the use of hybrid composites for additive manufacturing is a reasonable approach to adapt the mechanical properties to the loading case at hand. The experiments showed that increasing the aramid fiber content resulted in an increase in impact strength, but a decrease in tensile and flexural strength and a decrease in stiffness. Microstructural investigations of the fracture surfaces showed that debonding and delamination were the main failure mechanisms. Finally, Rule of Hybrid Mixture equations were applied to predict the mechanical properties at different mixture ratios. This resulted in predicted values that differed from the experimentally determined values by an average of 5.6%.

Additive manufacturing (AM), widely known as 3D-printing, builds parts by adding material in a layer-by-layer process. This tool-less procedure enables the manufacturing of porous sound absorbers with defined geometric features, however, the connection of the acoustic behavior and the material’s micro-scale structure is only known for special cases. To bridge this gap, the work presented here employs machine-learning techniques that compute acoustic material parameters (Biot parameters) from the material’s micro-scale geometry. For this purpose, a set of test specimens is used that have been developed in earlier studies. The test specimens resemble generic absorbers by a regular lattice structure based on a bar design and allow a variety of parameter variations, such as bar width, or bar height. A set of 50 test specimens is manufactured by material extrusion (MEX) with a nozzle diameter of $0.2$ mm and a targeted under extrusion to represent finer structures. For the training of the machine learning models, the Biot parameters are inversely identified from the manufactured specimen. Therefore, laboratory measurements of the flow resistivity and absorption coefficient are used. The resulting data is used for training two different machine learning models, an artificial neural network and a k-nearest neighbor approach. It can be shown that both models are able to predict the Biot parameters from the specimen’s micro-scale with reasonable accuracy. Moreover, the detour via the Biot parameters allows the application of the process for application cases that lie beyond the scope of the initial database, for example, the material behavior for other sound fields or frequency ranges can be predicted. This makes the process particularly useful for material design and takes a step forward in the direction of tailoring materials specific to their application.

Advances in manufacturing technologies and computational engineering are key enablers for optimized designs necessary for product performance improvements. Amongst other manufacturing technologies, particularly Additive Manufacturing (AM) is pushing the envelope of feasible design complexity challenging design engineers as well as their Computer-Aided Design (CAD) tools. The research field of Design for Additive Manufacturing (DfAM) provides an exhaustive supply of specific engineering design knowledge and methodological approaches accordingly. To enable design engineers to put those approaches into practice, this research gathers and structures not yet addressed AM-related requirements on the state of the art CAD tools. Additionally, architectural CAD functions as well as features are being pointed out and envisioned design workflow adaptions introduced, necessary to enable engineers to holistically utilize AM design potentials with CAD systems of the mid-term future.

Recent research efforts have highlighted the potential of hybrid composites in the context of additive manufacturing. The use of hybrid composites can lead to an enhanced adaptability of the mechanical properties to the specific loading case. Furthermore, the hybridization of multiple fiber materials can result in positive hybrid effects such as increased stiffness or strength. In contrast to the literature, where only the interply and intrayarn approach has been experimentally validated, this study presents a new intraply approach, which is experimentally and numerically investigated. Three different types of tensile specimens were tested. The non-hybrid tensile specimens were reinforced with contour-based fiber strands of carbon and glass. In addition, hybrid tensile specimens were manufactured using an intraply approach with alternating carbon and glass fiber strands in a layer plane. In addition to experimental testing, a finite element model was developed to better understand the failure modes of the hybrid and non-hybrid specimens. The failure was estimated using the Hashin and Tsai–Wu failure criteria. The specimens showed similar strengths but greatly different stiffnesses based on the experimental results. The hybrid specimens demonstrated a significant positive hybrid effect in terms of stiffness. Using FEA, the failure load and fracture locations of the specimens were determined with good accuracy. Microstructural investigations of the fracture surfaces showed notable evidence of delamination between the different fiber strands of the hybrid specimens. In addition to delamination, strong debonding was particularly evident in all specimen types.