There has been considerable research in recent years on the additive manufacturing (AM) of carbon fiber reinforced polymer (CFRP) parts based on the process of fused deposition modeling (FDM). The currently-applied steps within the manufacturing pipeline, such as slicing and path planning, consider only the planar case of filament deposition and mostly make no use of the possibility to place single pre-impregnated (prepreg) filaments. Classical methods such as tape-laying and laminating struggle with highly curved and complex geometries and require the costly production of molds, whereas when using AM, these geometries can be realized more easily and molds can be created using the same process. In this paper, a set of algorithms is presented that aims to resolve these problems. Criteria are formulated which enable the goal oriented development and evaluation of the presented methods and represent metrics for future methods. The developed algorithms enable the use of both continuous and discontinuous fiber patches in a much wider range of applications in designing and manufacturing of CFRPs. This opens up new possibilities in this promising field. The developed metrics and infrastructure further constitute progress in the field of multi-axis non-planar path planning for slicing algorithms in general and the conducted evaluation proves the formal applicability of the developed algorithms.

In vibration tests, the behavior of the structure depends on its mechanical boundary conditions, which are represented in physical tests by connecting elements with mechanical properties. Adjustable impedance elements are machine elements fulfilling the task of an adjustable connection on a vibration test bench and therefore represent a variety of properties. Their mechanical properties must be known over wider ranges than comparable compliant structures tested in the literature. This paper is dedicated to vibration testing of the adjustable impedance elements themselves, taking the influences of fixtures and measuring devices of the test bench into account. Different approaches for measuring the frequency response functions are applied to freely vibrating masses at a hydraulic and an electrodynamic test bench. Mass cancellation and the frequency-dependent measurement systems function have shown their usefulness in characterizing the biodynamic response of hand–arm models before. This measurement method is extended to be transferable to machine elements to obtain reliable results under a wider range of test conditions. The necessity for dynamically calibrated measurement of the frequency response functions is demonstrated for different free vibration masses and for two compliant elements on two different test benches to provide results over a wide range of test conditions.

The use of drop-in capable alternative fuels in aircraft can support the European aviation sector to achieve its goals for sustainable development. They can be a transitional solution in the short and medium term, as their use does not require any structural changes to the aircraft power-train. However, the production of alternative fuels is often energy-intensive, and some feedstocks are associated with harmful effects on the environment. In addition, alternative fuels are often more expensive to produce than fossil kerosene, which can make their use unattractive. Therefore, this paper analyzes the environmental and economic impacts of four types of alternative fuels compared to fossil kerosene in a well-to-wake perspective. The fuels investigated are sustainable aviation fuels produced by power-to-liquid and biomass-to-liquid pathways. Life cycle assessment and life cycle costing are used as environmental and economic assessment methods. The results of this well-to-wake analysis reveal that the use of sustainable aviation fuels can reduce the environmental impacts of aircraft operations. However, an electricity mix based on renewable energies is needed to achieve significant reductions. In addition, from an economic perspective, the use of fossil kerosene ranks best among the alternatives. A scenario analysis confirms this result and shows that the production of sustainable aviation fuels using an electricity mix based solely on renewable energy can lead to significant reductions in environmental impact, but economic competitiveness remains problem-atic.

The selection of products to be offered on the market is a critical decision-making process encountered in all industry sectors. It is not just a matter of maximizing profit or optimizing the utilization of corporate resources but also specifically concerns determining a product portfolio that is most suitably aligned to corporate strengths and that appeals to the most attractive and emerging markets. Hence, corporate competencies such as strategic management and production capabilities must be taken into account concurrently. Starting from this point of view, a twofold decision support system (DSS) has been developed. On the one hand, a theory of constraints (TOC)-based analytic hierarchy process (AHP) approach, including a taboo search algorithm, has been developed in order to derive the right product mix for maximizing the total profit amount by considering the bottleneck problem. On the other hand, a GE/McKinsey screen matrix is added to this consolidated approach to support decision-makers in the formulation of product portfolio strategies. The DSS provides a platform to compare outputs coming from the preceding two processes, which allows for the refinement of the solution. The proposed DSS is executed with a problem dataset from the industry to test its accuracy and reliability.

The retention factor is the key quantity for the thermodynamic analysis of the retention mechanism in chromatographic experiments. In this work, we measure retention factors for moderately polar solutes on four silica-based porous matrices as stationary phases by supercritical fluid chromatography. Elution of the solutes is only possible with binary mixtures of supercritical carbon dioxide (sc-CO₂) and modifier (methanol) due to the low polarity of pure sc-CO₂. The addition of modifiers makes the retention mechanism more complex and masks interactions between solute and stationary phase. In this work, we develop and validate several retention models that allow the obtaining of retention factors in modifier-free sc-CO₂. Such models pave the way for quantifying adsorption interactions between polar solutes and non-swellable porous matrices in pure sc-CO₂ based on retention data obtained in sc-CO₂-modifier mixtures. The obtained information will thereby facilitate the understanding and design of impregnation processes, which are often performed in modifier-free conditions.

Human-centred design as a research field is characterised by multidisciplinarity and a variety of many similar methods. Previous research attempted to classify existing methods into groups and categories, e.g., according to the degree of user involvement. The research question here is the following: How can human-centredness be measured and evaluated based on resulting product concepts? The goal of the paper is to present and apply a new metric—the Human-Centredness Metric (HCM)—for the early estimation of the quality of any human-centred activity based on the four goals of human-centred design. HCM was employed to evaluate 16 concepts, utilising a 4-point Likert scale, covering four different everyday products that were created by four students, which used three different human-centred design methods for this. The first concept was created without the application of any additional human-centred design method. The results illuminated trends regarding the impact of additional human-centred design methods on the HCM score. However, statistical significance remained elusive, potentially due to a series of limitations such as concept complexity, the small number of concepts, and the early developmental stage. The study’s limitations underscore the need for refined items and expanded samples to better gauge the impact of human-centred methods on product development.

The design of modular product families enables a high external variety of products by a low internal variety of components and processes. This variety optimization leads to large economic savings along the entire value chain. However, when designing and selecting suitable modular product architecture concepts, often only direct costs are considered, and indirect costs as well as cross-cost center benefits are neglected. A lack of knowledge about the full savings potential often results in the selection of inferior solutions. Since available approaches do not adequately address this problem, this paper provides a new methodological support tool that ensures consideration of the full savings potentials in the evaluation of modular product architecture concepts. For this purpose, the visual knowledge base of the Impact Model of Modular Product Families (IMF) is used, extended and implemented in a model-based environment using SysML. The newly developed Sys-IMF is then applied to the product family example of electric medium-voltage motors. The support tool is dynamic, expandable and filterable and embedded in a methodical procedure for knowledge-based decision support. Sys-IMF supports decision makers in the early phase of interdisciplinary product development and enables the selection of the most suitable modular solution for the company.

Aviation significantly contributes to anthropogenic radiative forcing with both CO2 and non-CO2 emissions. In contrast to technical advancements to mitigate the climate impact, operational measures can benefit from short implementation times and thus are expected to be of high relevance in the near future. This study evaluates the climate mitigation potential of nine operational improvements, covering both in-flight and ground operations. For this purpose, an innovative approach is presented to compare the results of measure-specific case studies, despite the wide differences in the underlying modeling assumptions and boundary conditions. To this end, a selection of KPIs is identified to estimate the impact of the studied operational improvements on both climate and the stakeholders of the air transport system. This article presents a comparative method to scale the results of the individual studies to a comparable reference, considering differences in traffic sample size as well as CO2 climate effects. A quantitative comparison is performed for operational improvements belonging to the same category, i.e., trajectory-related, network-related, and ground-related measures, and a qualitative comparison is carried out among all considered operational improvements. Results show that the in-flight operational improvements are more effective in mitigating the impact on climate with respect to ground operations. However, the latter generally have a weaker impact on the aviation industry and a higher maturity level. Further research could expand this study by assessing the effects of implementation enablers, such as actions at the regulatory level, to facilitate the acceptance of the studied measures in the aviation industry.

In the context of Industry 4.0, construction processes are shifting towards automation by implementing additive manufacturing (AM) of concrete structures, also referred to as concrete printing. Adapting concrete as a printing material entails complex material–process interactions between concrete and manufacturing processes that require specialized data modeling. However, data modeling for the AM of concrete structures has not kept up with concrete printing research and development. Aiming to enhance data modeling for the AM of concrete structures, this paper proposes a semantic modeling approach, referred to as “printing information modeling” (PIM). The PIM approach defines input parameters and material–process interaction in a generic printing information model for designing and planning concrete printing projects. Exchange requirements for concrete printing are identified and evaluated, serving as the basis for the printing information model. The printing information model, as a semantic (or meta) model, is conceptualized using object-oriented modeling concepts, formalized as an ontology, verified as an instantiable semantic model, and validated with a software tool developed as a plug-in for BIM platforms. As a result, a printing information model is developed to serve as a generally valid semantic model for the AM of concrete structures and has the potential to improve data modeling concepts currently deployed for concrete printing.

In order to ensure high weld qualities and structural integrity of engineering structures, it is crucial to detect areas of high stress concentrations along weld seams. Traditional inspection methods rely on visual inspection and manual weld geometry measurements. Recent advances in the field of automated measurement techniques allow virtually unrestricted numbers of inspections by laser measurements of weld profiles; however, in order to compare weld qualities of different welding processes and manufacturers, a deeper understanding of statistical distributions of stress concentrations along weld seams is required. Hence, this study presents an approach to statistically characterize different types of butt joint weld seams. For this purpose, an artificial neural network is created from 945 finite element simulations to determine stress concentration factors at butt joints. Besides higher quality of predictions compared to empirical estimation functions, the new approach can directly be applied to all types welded structures, including arc- and laser-welded butt joints, and coupled with all types of 3D-measurement devices. Furthermore, sheet thickness ranging from 1 mm to 100 mm can be assessed.