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.

This paper operationalizes ISO 59020 for product-level circularity by implementing the Holistic Product Circularity Analysis (HPCA) with fixed boundaries and explicit reporting rules. HPCA enables consistent assessment and targeted optimization by combining qualitative ratings with quantitative flows across all stages of the product lifecycle. The approach is demonstrated on a children’s balance bike by comparing a reference scenario with an optimized circular scenario and deriving decision-relevant improvement levers.

This study examines neural differences between high- and low-performing designers using EEG. Participants viewed an image of IKEA furniture and created alternative designs. Performance was evaluated based on the composite of fluency, flexibility and originality scores. Results reveal that high-performing designers exhibited greater beta and gamma frequency band power in frontal and right-frontal regions compared to low-performers. Although these differences did not remain significant after multiple-comparison correction, their large effect sizes suggest meaningful neural distinctions.

This study examines how CAD geometry variations affect finite element (FE) crash simulations for automotive front rail assembly and motivate the use of combined impact measures that better reflect the physical response. Based on these insights, we outline a machine learning formulation that links geometric modifications to their simulation effects. The study centers on geometric representation, employing UVbased graph encodings to capture local shape changes and provide the basis for advancing and validating the full prediction pipeline.

In the early phases of product development, cost estimation is crucial for supporting design decisions. When cost estimates are inaccurate or delayed, design engineers cannot assess economic viability and may pursue concepts that later prove too costly. In this context, artificial intelligence (AI) offers new possibilities for more accurate and timely cost estimates, yet adoption in practice remains limited. Based on an interview study with 22 cost engineers and an online survey of 102 respondents, this study examines practices, challenges, and expectations for AI-assisted cost estimation.

Despite the many circular economy (CE) design frameworks, implementation is limited. This study interviews six Swedish design firms (producers/consultancies, small/large) to compare CE barriers. Results show small producers face more value chain challenges, while large producers focus on design. Consultancies emphasize economic/legal factors. Organizational silos and perceived costs are universal barriers. The findings highlight the need for tailored CE approaches: SMEs require resources to influence suppliers, while large firms need better methodologies for internal organizational change.

Conventional user research with human participants faces significant challenges, including substantial time and resource requirements, and limited scalability. In response, this study presents an efficient, cost-effective workflow driven by large language models (LLMs) for simulating user research with synthetic participants (SPs) at scale. In a case study in design augmented reality for education, SPs’ open-ended answers were plausible and comprehensive, yet semi-open and closed items diverged from those of humans. SPs can augment early qualitative work, but cannot replace human studies.

To design effective behaviour changing interventions, behavioural designers need to generate ideas that combine both technical and behavioural aspects. However, little is still known about the creative output of ideation in behavioural design. Taking an exploratory approach, this study examines the creative characteristics of brainstormed behavioural design ideas using the Behavioural Design Space (BDS) as creative assessment framework. The findings show uneven distributions across all BDS parameters indicating fixation and lost creative opportunities.