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.

The implementation of services into complex systems is not well understood in design. We explore this issue by interviewing 24 design professionals with experience in implementing digital services in healthcare. We asked when they consider such services as implemented, and how they view the relation between design and implementation. Results reveal diverse perspectives on both topics. Given the wide dispersion in views, we propose two categories to describe implementation goals (impact on, and integration with systems), and to view design as a contributor to the implementation phase.

This paper presents the pedagogical frame of the Master’s Programme Design Ecologies, a design-driven higher education initiative that integrates ecoliteracy principles and relational approaches to material cultures, striving to create a design practice that is life-affirming. Responding to the ecological crises shaped by extractive, anthropocentric design paradigms, the programme cultivates an ecocentric orientation grounded in our interdependence with other-than-human beings, systems thinking, and political awareness. Drawing on ecoliteracy principles, design is explored as a practice that shapes and is shaped by multispecies relations, material flows, and planetary boundaries. This is examined through two student projects and the conceptual work guiding the programme.

The paper argues that reorienting design education toward ecological relationality contributes critically to the field of Biodesign by proposing situated responses that acknowledge not only the biological aspects of design, but also issues of power, cohabitation, and the ethical responsibilities of intervening in complex ecological systems.

This study presents a method to design sustainable structural parts of a Rechargeable Energy Storage Systems using Design for CE and Computational Optimization. Principle solutions are developed and combined with sustainability criteria being a key factor in the concept evaluation. The battery tray, a subsystem of REESS, serves a case study in which intrusion, mass, and LCA are optimized by varying the recyclate, UD tapes and design. The resulting Pareto front reveals trade-offs between intrusion, mass and LCA results and highlights the potential to reduce environmental impact in early design.

AI in Requirements Engineering (RE) relies on industrial data, yet safety and privacy risks limit its use. While the GDPR distinguishes only between anonymization and pseudonymization, we use neutralization as a semantics-preserving technique. In AI-supported RE, data heterogeneity and cross-domain variability impede model training. We propose guidelines for semantics-preserving preprocessing for RE datasets based on ISO 29148 criteria, showing that neutralization does not compromise semantics. The approach enables industry–academia collaboration through AI-assisted RE in product development.

For industries transitioning to circular economy, understanding the business case is essential. This paper highlights key business model factors for remanufacturing within a heavy truck manufacturer. Twenty-six interviews were held, the barriers to profitability were identified as cost structure, key resources and cores and key activities. Applying systems engineering principles can help translate business needs into requirements, mitigate complexity and align stakeholders for effective transformation. Recommended future research is to investigate partnerships, profitability, and model design.

We build an experiment to uncover the bandit-like nature of consumer behavior usually masked by the product and time aggregation of consumption data. Subjects make repeated choices between musical styles (either all familiar or unfamiliar), and post-choice satisfaction is observed. We estimate Bayesian bandit models of learning taste by consuming with satiation. Our best model features decreasing random exploration, with openness being associated with higher exploration. Early exploration is more intensive in the unfamiliar treatment and persists throughout the experiment in both treatments. Overall, subjects make choices that deviate from their best prediction 61.5% of the time in the unfamiliar treatment versus 44.7% in the familiar treatment. Our model offers a rational interpretation of random utility in discrete consumer choices which does not rest on perception and/or decision errors.