The individualization of patient-specific ankle joint orthoses is becoming increasingly important and can be ideally realized by means of additive manufacturing. However, currently, there are no functional additively manufactured fiber-reinforced products that are used in the field of orthopedic treatment. In this paper, an approach as to how additively manufactured orthopedic products can be designed and produced quickly and flexibly in the future is presented. This is demonstrated using the example of a solid ankle–foot orthosis. For this purpose, test results on PETG-CF15, which were determined in a previous work, were integrated into a material map for an FEA simulation. Therewith, the question can be answered as to whether production parameters that were determined at the test specimen level can also be adapted to real, usable components. Furthermore, gait recordings were used as loading conditions to obtain exact results for the final product. In order to perfectly adapt the design of the splint to the user, a 3D scan of a foot was performed to obtain a perfect design space for topology optimization. This resulted in a patient-specific and stiffness-optimized product. Subsequently, it was demonstrated that the orthosis could be manufactured using fused layer modelling. Finally, a comparison between the conventional design and the consideration of AM-specific properties was made. On this basis, it can be stated that the wearing comfort of the patient-specific design is very good, but the tightening of the splint still needs to be improved.

A digital twin describes the virtual representation of a real process. This twin is constantly updated with real data and can thus control and adapt the real model. Designing suitable digital twins for path planning of autonomous robots or drones is often challenging due to the large number of different dynamic environments and multi-task and agent systems. However, common path algorithms are often limited to two tasks and to finding shortest paths. In real applications, not only a short path but also the width of the passage with a path as centered as possible are crucial, since robotic systems are not ideal and require recalibration frequently. In this work, so-called homotopic shrinking is used to generate the digital twin, which can be used to extract all possible path proposals including their passage widths for 2D and 3D environments and multiple tasks and robots. The erosion of the environment is controlled by constraints such that the task stations, the robot or drone positions, and the topology of the environment are considered. Such a deterministic path algorithm can flexibly respond to changing environmental conditions and consider multiple tasks simultaneously for path generation. A distinctive feature of these paths is the central orientation to the non-passable areas, which can have significant benefits for worker and patient safety. The method is tested on 2D and 3D maps with different tasks, obstacles, and multiple robots. For example, the robust generation of the digital twin for a maze and also the dynamic adaptation in case of sudden changes in the environment is covered. This variety of use cases and the comparison with alternative methods result in significant advantages, such as high robustness, consideration of multiple targets, and high safety distances to obstacles and areas that cannot be traversed. Finally, it was shown that the environment for the digital twin can be reduced to reasonable paths by constrained shrinking, both for real 2D maps and for complex virtual 2D and 3D maps.

Patients who suffer from foot drop have impaired gait pattern functions and a higher risk of stumbling and falling. Therefore, they are usually treated with an assistive device, a so-called ankle–foot orthosis. The support of the orthosis should be in accordance with the motor requirements of the patient and should only be provided when needed, which is referred to as assistance-as-needed. Thus, in this publication, an approach is presented to determine the assistance-as-needed support using musculoskeletal human models. Based on motion capture recordings of multiple subjects performing gaits at different speeds, a parameter study varying the optimal force of a reserve actuator representing the ankle–foot orthosis added in the musculoskeletal simulation is conducted. The results show the dependency of the simulation results on the selected optimal force of the reserve actuator but with a possible identification of the assistance-as-needed support required from the ankle–foot orthosis. The required increase in support due to the increasing severity of foot drop is especially demonstrated with the approach. With this approach, information for the required support of individual subjects can be gathered, which can further be used to derive the design of an ankle–foot orthosis that optimally assists the subjects.

Only by using accurate material data can precise simulation results be achieved. This principle also and especially applies in the field of crash simulation. However, in the simulation of short-fibre reinforced thermoplastics, material parameters are usually used that originate from the material testing of as-new samples. In order to get closer to the condition on the roads, where not only new vehicles are driving, the influence of service loads on the crashworthiness has to be investigated. This paper reports on studies of PBT GF30, a polybutylene terephthalate reinforced with 30% glass fibres, in which fatigue damage was induced in the material by cyclic loading. The residual strength was then determined in a high-speed experiment and compared with the strength of virgin samples. In order to enable the usability of the findings in the simulation, a modified failure criterion was implemented that takes the previous fatigue damage into account. The prediction quality of the simulation model was compared with the experimental findings and it can be concluded that there is good agreement.

This work presents a novel infill method for additive manufacturing, specifically designed to optimize material use and enhance stiffness in fused filament fabrication (FFF) parts through a geometry-aware, corrugated design inspired by sandwich structures. Unlike standard infill patterns, which typically employ uniform, space-filling grids that often disregard load-specific requirements, this method generates a cavity inside the component to be printed and fill the space between inner and outer contours with continuous, adaptable extrusion paths. This design enables consistent support and improved load distribution, making it particularly effective for parts under bending stresses, as it enhances structural resilience without requiring additional material. Simulations performed on a 10 cm³ test part using this method showed potential reductions in material consumption by up to 77% and a decrease in print time by 78%, while maintaining stiffness comparable to parts using conventional 100% grid infill. Additionally, simulations demonstrated that the new corrugated infill pattern provides near-isotropic stiffness, addressing the anisotropic limitations often seen in traditional infill designs that are sensitive to load orientation. This geometry-aware infill strategy thus contributes to balanced stiffness across complex geometries, enhancing reliability under mechanical loads. By integrating directly with slicer software, this approach simplifies advanced stiffness optimization without the necessity of finite element analysis-based topology optimization.