The advent of multidisciplinary product development may require a corresponding evolution or adaptation of product development practices within companies. To support this, researchers have developed various groupings of concepts and techniques, such as “toolboxes” or “maps”, which can be assimilated to static databases. Consequently, this article presents a first step towards a community-driven database for the dynamic representation of links between approaches, processes, methods and tools in research documents. Following a comparative analysis of different representations, a preliminary design of a dynamic database is presented using Unified Modeling Language models to define its architecture. A use case diagram paired with screenshots of the dynamic database presents the core functionalities, which include real-time data filtering, visualisation, navigation and modification.

Creativity is a requirement for excellence in product engineering. Despite its important role, the concept of creativity in engineering is challenging to articulate and define, both for practitioners and researchers. What makes technical creativity unique? Existing definitions often fall short of capturing the essence of creativity in technical contexts. The process of defining technical creativity is performed iteratively. In product engineering, creativity is not an abstract concept but a practical necessity, requiring motivation, imagination, expertise and experience. Therefore, two workshops with product engineers were held and the results were used to refine the definition. A shared understanding of technical creativity, that can be applied in daily engineering practice is created, enhancing both research and practical outcomes in product engineering.

The circular economy (CE) seeks to replace traditional linear models by focusing on resource reuse and circulation. However, developing effective CE business strategies is difficult due to complex user behaviors and product flows. Existing scenario analysis tools often rely on survey-based conjoint methods, raising concerns about discrepancies with real purchasing patterns. This study introduces a data-driven simulation approach that employs a consumer preference model and product circulation processes based on actual operational data. Applied to a second-hand PC rental business, our method more accurately reproduces market behavior and reveals that targeting certain customer segments can enhance profitability and resource utilization. These findings underscore the approach’s value as a practical tool for pre-evaluating strategies in CE businesses.

Laser Powder Bed Fusion (LPBF) enables complex metal components for the space industry. However, as-built surface roughness affects material properties and is closely linked to design geometry. As computer-aided design tools struggle to model roughness accurately, this study explores Additive Manufacturing Design Artefacts (AMDAs) to investigate design-related roughness and its impact on fatigue performance. A space industry case study using AMDAs to replicate a 4 mm unsupported roof radius of a rocket engine component found fatigue performance reductions of 88% in horizontal builds and 65% in vertical builds compared to machined surfaces. Microstructural analysis confirmed the influence of roughness and grain structure on fatigue behaviour. Findings highlight how AMDAs provide design-specific insights and support engineers in investigating uncertainties.

Managing high-variant product portfolios effectively is a crucial competitive advantage in offering mass customized products on saturated markets. Association Rule Mining (ARM) is a field of data mining determining frequent itemsets from historic transactions and deriving patterns of conclusion. This paper introduces a new approach to transfer ARM to feature-based configuration e.g. in the German automotive industry. Combined, existing apriori product knowledge is used in constraints to effectively lowering runtime by reducing the number of candidate-sets through introduction of a Boolean satisfiability check. For an efficient implementation, three different Apriori algorithms are tested and benchmarked on a generic dataset for different parameters. Results show a significant improvement in using SAT-based pre-screening while efficiency of the implementation depends on the given example.

Disaster Risk Financing (DRF) presents a massive challenge to governments worldwide in protecting against catastrophic disaster losses. This study explores the development of a Disaster Fund that optimally integrates various DRF instruments, considering several real-world factors, including limited reserves, constrained risk horizons, risk aversion, risk tolerance, insurance structures, and premium pricing strategies. We demonstrate that the Value-at-Risk (VaR) and Tail VaR constraints are equivalent when the government has a limited risk horizon. Furthermore, we investigate the optimality of various insurance structures under different premium principles, conduct comparative statics on key parameters, and analyze the influence of a VaR constraint on the optimal mix of disaster financing instruments. Lastly, we apply our Disaster Fund model to the National Flood Insurance Program dataset to assess the optimal disaster financing strategy within the context of our framework.

The advent of complex socio-technical systems in modern society calls for teaching value-based participatory design in engineering curricula. Yet, no scientific literature supports teachers in this effort. This paper introduces a teaching approach called “value-based participatory design of complex socio-technical systems” and reports on its implementation. It emphasizes the importance of actively involving stakeholders and tapping into their values from the very start of the design process. Following this approach, students learn to (1) design with stakeholders, (2) identify key values and conflicts to create a value-based mission statement, (3) navigate uncertainties, (4) adopt an iterative design process, and (5) recognize that only stakeholders can define what works best. Results of an academic course based on this approach confirm its value and importance for engineering curricula.

Species recognition is an essential part of biological and paleontological study. In gastropods, although species are genetic entities, shell morphology continues to be used as the primary source of information to recognize most species. While there are few directly tested cases, variations in conchological characters for modern species are expected to reflect underlying genetic differences that define a biological species, an assumption that is also applied to identify species in the fossil record. Additionally, how consistently shell shape differentiates gastropod species remains poorly understood. In this study, shell shape of Recent and Pliocene–Pleistocene fossil specimens of well-known intertidal gastropods (Littorinidae, periwinkles: †Littorina petricola, Littorina keenae, and the sister-species pair Littorina plena and Littorina scutulata) from the east Pacific was analyzed using landmark-based morphometrics and compared with published molecular data. For the extant species, there is a general positive relationship between shell shape and genetic differences. Discriminant function analyses indicate distantly related species can be more reliably recognized from their shells, while closely related species have a higher error. Fossils and recent specimens were classified with similar consistency. More work is needed to illuminate whether this case applies more widely.

Designing healthcare interventions for children with complex health needs often overlooks the perspectives of key stakeholders, including children. Collaborative design is essential for creating solutions that integrate diverse viewpoints and bridge communication gaps. However, prior studies lack tools to align stakeholder perspectives in pediatric care. This study introduces Octo, an educational toy, as a boundary object to enhance communication among children aged 4 to 10 with congenital heart disease (CHD), their parents, and healthcare providers. Octo evolves from a prototype to a functional educational tool, fostering engagement through play while promoting health literacy and stakeholder collaboration. This research through design (RtD) demonstrates the effectiveness of boundary objects in advancing inclusive, child-led interventions and collaborative healthcare design.

Restrictive voting laws are an increasingly salient feature of American politics. Yet estimating their direct impact on turnout is challenging, given the strategic actions political actors take to impose and mitigate the costs of these laws. Using individual-level data from Davidson County, Tennessee, we leverage variation induced by an early-morning tornado on Super Tuesday 2020 to estimate the direct causal effect of polling-site consolidations. We find moving to a new polling station decreases in-person turnout by 5.65 percentage points, on average, and that the variable cost—proxied by change in travel distance—drives almost all of this decline. Voting at a consolidated site only decreases turnout when the number of individuals assigned to a station increases by more than 100%.

The reprocessing of used products within a circular factory relies on instance-individual design decisions. This requires specific design knowledge (SDK) on relations between embodiment and functional behavior. However, existing approaches do not model SDK in a way that supports product reuse to fulfill the functional requirements of new product generations. This paper presents a hypothesis-based modeling approach on building and structuring qualitative SDK. Drawing on elements of existing product models, the approach yields three outcomes - a function-related structure, design hypotheses, and the assignment of testing strategies. A case study of an angle grinder demonstrates how the approach addresses the requirements of a circular factory by facilitating targeted SDK buildup, ensuring comprehensive documentation, and preparing the quantification of knowledge.

Thanks to its design freedom, additive manufacturing (AM) offers the possibility of directly integrating functions and effects into parts. One of these effects is particle damping, which can significantly increase the damping of parts due to the friction of loose particles in closed cavities. However, the design of these cavities is challenging due to a large number of influencing factors. This article presents a tool that optimizes the component topology and creates particle damping cavities. Using the bidirectional evolutionary structure optimization method, an optimization of mass, stiffness, and damping is achieved. The verification of the tool shows that, in addition to reducing the part mass, the integration of the particle dampers is successfully implemented in compliance with the design principles from the literature. Furthermore, restrictions of the AM process were implemented.

Feminist understandings of shame often explore the machinations of power over gendered bodies. This article theorizes a feminist politics of shame to describe gendered shame-as-discipline, and possible resistance, within institutions. The central case comes from US medical education, in which a “culture of shame” has been identified. In July 2020 the Journal of Vascular Surgery published an article classifying trainee surgeons’ social media posts as either “professional” or “unprofessional,” with the latter category counting images of trainees wearing “inappropriate” attire including bikinis and swimwear. The article was interpreted as explicit shaming of gendered bodies in healthcare and met backlash through a Twitter (now X) campaign in which healthcare workers posted their bikini pictures alongside #MedBikini; the article was retracted by the journal. I analyze #MedBikini Twitter discourse and institutional responses to explore shame, discipline, knowledge, and power in the medical institution. The article made visible shame-as-discipline, utilizing surveillance, shame, and classification to manifest power and encourage institutional normativity. Participants in #MedBikini resignified bikinis (and their gendered, racialized bodies) as not-shameful, but valuable and resistant to dominant norms. This resistance clarifies the machinations of gendered discipline and surveillance and bolsters an intersectional feminist politics of shame for responding to power-knowledge-shame structures within institutions.

Large Language Models (LLMs) have advanced the extraction and generation of engineering design (ED) knowledge from textual data. However, assessing their accuracy in ED tasks remains challenging due to the lack of benchmark datasets specifically designed for ED applications. To address this, the study examines how theoretical concepts from Axiomatic Design Theory—such as Functional Requirements, Design Parameters, and their relationship—are expressed in natural language and develops a systematic approach for annotating ED concepts in text. It introduces a novel dataset of 6,000 patent sentences, annotated by domain experts. Annotation performance is assessed using inter-annotator agreement metrics, providing insights into the challenges of identifying ED concepts in text. The findings aim to support designers in better integrating design theories within LLMs for extracting ED knowledge.

The contribution introduces the Application Domain Card (ADC) as a structured, problem-oriented method for documenting the status quo and challenges within application domains, addressing a gap in existing AI development methodologies. Derived through a literature review, the ADC emphasizes flexibility, modularity, and accessibility, thereby enabling domain experts to identify AI use cases independently while fostering collaboration with AI experts. The practical applicability of the ADC was confirmed by a support evaluation involving technical drawing assessments in the context of design theory exercises. Future research will focus on refining the ADC to meet specific demands of industrial product development. This includes developing a software-supported application with automated tools for information collection and creating a library of practical examples for the method’s modules.

The evolving landscape of engineering is shaped by trends such as digitalization, sustainability, and globalization. While these trends impact product development, their direct effects on engineers remain underexplored. This study investigates how current trends shape engineering work environments and identifies key factors that enable engineers to thrive. Using a mixed-method approach, we conducted qualitative interviews and a quantitative survey with 122 engineers across industries. Our findings reveal that trends influence collaboration, autonomy, stakeholder involvement, and digital tool integration. The results emphasize the need for human-centered approaches, such as New Work, to balance flexibility and structure. The insights contribute to designing adaptive engineering environments that foster resilience, well-being, and innovation.

We corroborate findings showing a disparity in one’s willingness to update political beliefs in the face of counterevidence among bilinguals, examining the role of the Foreign Language effect (FLe) on belief maintenance. 133 Liberal English-Spanish bilinguals and 70 English monolinguals showed that belief change on political issues is lesser than on nonpolitical issues following counterevidence. Bilinguals, however, showed greater change in the second language (L2) compared to the first and greater belief change than the monolinguals overall. The second language also led to slower reading and rating times across all conditions, which corresponded with greater belief change. Among bilinguals using their L2, those most likely to show belief change reported having a less meaningful connection to the foreign language.

Technical standards provide order and consistency in application domains; however, standards development organizations produce large families of related documents containing significant amounts of information that can be difficult to access, evaluate, and produce consistently. We describe standards as linguistically, socially, and conceptually dynamic constructs using theory drawn from systems engineering and linguistics to create a model of standards documents that can be updated, evaluated, and queried to retrieve information reliably. We describe the theoretical basis for this model from multiple perspectives and explain broadly how it can be used to retrieve relevant information from standards.