As environmental sustainability pushes organisations to integrate sustainable system design into engineering workflows, there remains a gap in translating high-level environmental objectives into actionable design practices. This research addresses the integration gap by developing a Model-Based Systems Engineering enabled ecodesign approach tailored for early-stage product design at a Dutch radar system developer. A ten-step methodology integrates carbon footprint analysis with MBSE functional data to identify architectural hotspots, enabling data-driven decisions within existing workflows.

Design Structure Matrices (DSMs) capture dependencies between system entities and help analyze system complexity, but manually creating them from unstructured documents is time consuming. This work proposes an automated DSM extraction framework using LLMs and RAG with an explicit reasoning step before the LLM determines the presence of a dependency between two system entities. Using a hand-curated dataset, we evaluate three LLM models (GPT-4o-mini, GPT-3.5, and GPT-4o) across six performance metrics and cost.The findings show that reasoning length affects LLM’s DSM extraction performance.

Metamodels are replacing costly validation simulations and experiments in clinch joint design. If materials or conditions change, existing metamodels may no longer be reliable. This paper presents an approach that uses model uncertainty, the Coefficient of Prognosis and the R2 score to decide if a model should be reused or recalibrated, or if fine-tuning is needed. Two case studies show that the framework can provide sufficient recommendations and reused, recalibrated and fine-tuned models can match new models while reducing simulation and training effort.

During the transition to CAD/PLM software, key users underwent guideline-based training aligned with company workflows. This practical approach, which linked tool functions to real design practices, accelerated the acquisition of skills, ensured modelling consistency, and improved understanding of digital engineering. The study identifies key users as knowledge multipliers and reveals how such methods develop competence. The findings emphasise the significance of problem-solving training and the relevance of guideline-based methods for industrial practice and design education.

This review synthesizes the current state-of-the-art knowledge on pure mycelium materials (PMMs) as sustainable design solutions, mapping their essential structural, chemical, and mechanical characteristics, and the factors that drive or hinder their performance in design contexts, while also identifying application fields. Finally, this paper points to gaps in taxonomy and standardized characterization, resulting in a duality between scientists and designers and industry. Therefor, future research is derived to reinforce the synergy between design and material science for PMM adoption.

This study examines how ChatGPT support influences verbal communication in synchronous collaborative CAD activities. Using a verbal protocol analysis of teams solving an embodiment design task, the results show that ChatGPT-supported teams communicated less, devoted less verbal communication to problem- and analysis-related communication, and shifted toward process and solution synthesis, indicating a shortened design co-evolution cycle in which teams move more quickly toward generating solutions. Future work should integrate these findings with broader teamwork and taskwork analyses.

Sustainability is a central challenge in engineering. Early architectural design decisions strongly influence a product’s ecological footprint and long-term sustainability potential. Addressing these aspects in the concept phase is therefore essential. This paper analyses how architecture decisions - such as modularity, standardisation, redundancy, and updateability - affect ecological sustainability. The qualitative assessment helps practitioners to anticipate environmental impacts and foster sustainability awareness in product architecture development.

This paper presents a methodical investigation of ten types of contacts for electrically conductive polymer composites manufactured using additive manufacturing. The study examines the suitability of three different bonding agents for reducing contact resistance and measures the contact resistance of the contact systems as well as the tensile strength. Based on these results, design guidelines and a design catalogue are developed. The results show that although each contact type is fundamentally suitable, they should be adapted to the respective application using the derived design guidelines.

Implementing circular business models (CBMs) like Product-as-a-Service entails high uncertainty, necessitating costly and prolonged business experimentation. To efficiently mitigate this uncertainty, Bayesian Optimal Experimental Design is applied to the CBM context, selecting conditions that maximize the Expected Information Gain for unknown CBM parameters. Applied to an air conditioner subscription case study, the method successfully identified optimal conditions from 124 candidates. This approach facilitates CBM implementation by efficiently minimizing uncertainty under limited resources.

This study aimed to detect designers’ motivations (Personal Identity, Conformity, Life Efficiency, and Information) in using Generative AI in AI-assisted design and how these motivations related to post-design evaluations of AI (Attitudes, Satisfaction, and Continuance Intention). The results showed that personal identity, conformity, and efficiency motives can predict attitudes and satisfaction for the use of Generative AI in AI-assisted design. No motivation indicated in the study can predict continuance intention, which suggests that long-term AI usage depends on factors beyond motivation.

Adolescence is a critical period for establishing oral health habits, yet motivating young people remains challenging. This paper presents a pilot intervention in the Norwegian Public Dental Service, developed through co-design and guided by salutogenic and hope theory. The intervention consisted of three touchpoints: an SMS invitation, an in-clinic goal-setting dialogue, and a follow-up SMS embedded in routine care. Based on interviews with clinicians and adolescents, we explore how hope-oriented communication can be enacted within everyday clinical practice.

Additive Manufacturing (AM) faces process limitations such as build-volume restriction and thermal distortion. While AM favors integral design, certain restrictions can be overcome by combining differential design with subsequent joining technologies (JT). Yet little is known about suitable JT selection in AM. To bridge this gap, established JT selection frameworks from conventional manufacturing (CM) were examined and adapted to AM. The resulting framework supports JT selection in AM based on joint design and AM-specific criteria while remaining applicable to CM and enabling combined designs.

This study examines how designers’ experiences with text-to-image GenAI relate to their interaction patterns during a design hackathon. Survey data and two contrasting cases show that positive experiences align with shifting prompts and broader command use as designers move from exploration to refinement, while negative experiences correlate with fixed prompting and limited variations. The study demonstrates how interaction data can inform adaptive GenAI support across design phases, offering opportunities to enhance both practice and tool development.

The aim of this exploratory pilot study is to examine the subjective user experience of operating a pillar drilling machine and a minting machine. Clustering show three recurring perception profiles: predominantly positive, negative/demanding, and mixed. Operator posture strongly influences experience, while individual factors such as gender are less predictive. Ground-level, medium-reach positions get the most favourable ratings. The findings provide a first basis for extending behaviour cards with perception-based “experience cards” to support user-centred ergonomic design.

This paper proposes a practical reframing design thinking as early as possible in the design process, so that sustainability is treated as integral rather something to be retrofitted. We present the broadened context phase as the first part of the Impact Design process. This iterative set of steps help designers exploring environmental problem spaces before commiting to a target group. We evaluated the approach with university students, in a sustainability course and a master project. Findings indicate that the method helps select the most impactful problem to address.

This study explores how designing reuse models for clinical trial packaging can stimulate circular transitions in healthcare logistics. Using a Design Inclusive Research approach, four reuse models were explored, developed and evaluated through a Product-Service System lens together with stakeholders from the value chain. Findings underline the complexity of implementing RPSs in the clinical trial context. Implementing circular solutions therefore demands an added design layer focused on quality assurance, along with new protocols, digitalisation, partnerships, scale, and standardization.

Printed circuit boards (PCBs) fix and connect electrical components and are widely used. Current design methods emphasise mature products and do not leverage the potential of PCBs as prototyping tools. Accordingly, an alternative approach using PCBs for prototyping electrical and mechatronic solutions is evaluated through three case studies. Insights formed five concrete recommendations for designers: Increase fidelity deliberately, design for prototyping, iterate incrementally, parallelise prototyping, and prototype and test early. These aim to make prototyping with PCBs more accessible.

Ontogenetic change is a major source of phenotypic variation among members of a species and is often of greater magnitude than the anatomical differences that distinguish closely related species. Ontogeny has therefore become a problematic confounding variable in vertebrate paleontology, especially in study systems distant from extant crown clades, rendering taxonomic hypothesis testing (a fundamental process in evolutionary biology) rife with difficulty. Paleontologists have adopted quantitative methods to compensate for the perception that juvenile specimens lack diagnostic apomorphies seen in their adult conspecifics. Here, I critically evaluate these methods and the assumptions that guide their interpretation using a μCT dataset comprising growth series of American and Chinese alligator. I find that several widespread assumptions are scientifically unjustifiable and that two popular methods—geometric morphometrics and cladistic analysis of ontogeny—have unacceptably high rates of type II error and present numerous procedural difficulties. However, I also identify a suite of ontogenetically invariant characters that differentiate the living species of Alligator throughout ontogeny. These characters overwhelmingly correspond to anatomical systems that develop before (and play a signaling role in) the development of the cranial skeleton itself, suggesting that their ontogenetic invariance is a consequence of the widely conserved vertebrate developmental program. These observations suggest that the architecture of the cranium is fixed early in embryonic development and that ontogenetic remodeling does not alter the topological relationships of the cranial bones or the soft tissue structures they house. I propose a general model for future taxonomic hypothesis tests in the fossil record, in which the hypothesis that two specimens are different ontogenetic stages of a single species can be falsified by the discovery of character differences that cannot be attributed plausibly to ontogenetic variation.