This study investigates the mechanical performance of PA6-CF and PLA components fabricated with desktop material extrusion additive manufacturing. To define the geometry, low-cost 3D scanning was used in combination with Generative Design in Autodesk Fusion 360. PA6-CF outperformed PLA by 25% in pre-failure peak load (1.85 kN vs. 1.47 kN), despite the datasheet values suggesting a 450% advantage in interlayer strength. Poor interlayer bonding of PA6-CF is attributed to low layer temperatures (87–136 °C) during the printing process, indicating that a chamber temperature of 60 °C is inadequate.

As systems become increasingly data-centric, interdisciplinary engineering design faces growing complexity and interdependencies. This paper investigates how a combined Design Structure Matrix (DSM) and graph-based modeling approach supports interdisciplinary decision-making by revealing critical data dependencies, compared to standalone DSM or graph models. Based on a case study on autonomous public transportation and expert input, the results illustrate complementary insights enabled by the combined approach and discuss its implications for industrial system design.

Life cycle assessments identify environmental hotspots, yet translating these insights into design actions remains slow and expert-dependent. Existing AI tools lack a dynamic link to current research. Here, we present an LLM-driven pipeline that interprets LCA hotspots, mines recent literature, and extracts feasible, research-backed design alternatives. In a case study on a headlamp control unit, the method produced relevant and applicable improvements, indicating its value for accelerating sustainable product design.

The study documents the approaches, processes, methods, and tools used by 11 start-ups to develop their smart products, while focusing on the sustainable concepts and techniques (SCTs) adopted. Although the majority of start-ups demonstrate awareness of the environmental impacts of their products and tend to implement relevant practices, the results indicate a lack of formalised SCT usage. Several start-ups have therefore recognised the value of a bespoke “eco-design toolbox” and aim to work towards reducing the environmental impacts of their later product versions.

Cities play a major role in designing future mobility plans. Our question is how to contribute to sustainable mobility design while effectively accounting for social equity, health, and wellbeing considerations. After defining a list of mobility-related social issues, two stakeholder-based workshops with mobility users from two major cities, namely Paris and Cairo, were conducted. Participants explored mobility problems through eighteen purposive persona models in total. In Cairo, participants mainly reported safety and security issues while in Paris, mobility stress was dominant.

The increasing digitalization and connectivity of development processes are forcing companies to transform their engineering comprehensively. The presented engineering reference capability map provides a structured framework for this transformation. The capability map is a four-level hierarchical model, contains essential engineering capabilities and is inspired by the periodic table of elements. Standardized profiles describe the characteristics and dependencies of each capability. The map serves as a reference framework for identifying gaps, potential, and development needs in engineering.

This study examines how AI can support the development of Leading Sustainability Criteria in sustainable product development, comparing AI-generated outputs with human-facilitated workshop results from four Swedish companies. Results highlight AI’s ability to accelerate and broaden sustainability framing, but emphasize that contextual relevance and legitimacy depend on participatory inputs. The findings suggest that AI is most effective when integrated into hybrid workflows that preserve human insight and stakeholder engagement—offering practical guidance for future implementation.

This work investigates the development of sneakers designed under Design for Disassembly principles and supported by additive manufacturing to promote a more sustainable and circular product life cycle. By responding to the limitations of traditional footwear assembly, the study identifies and organises 35 technical requirements derived from consumer needs. The proposed model offers a clear and adaptable framework that enhances decision-making in early design stages, guiding the creation of innovative, recyclable and environmentally responsible footwear solutions.

This study investigates how product attributes shape user interpretation of unfamiliar products in terms of functions and context of use. This was made possible through an experiment involving 71 participants who were administered three unfamiliar end-use products without any additional cue. Findings reveal that visual cues, material semantics, and contextual imagination shape understanding, with misinterpretations often arising from analogical reasoning and partial cue activation. Designers should harmonize cues and leverage material symbolism to guide user perception and acceptance.

Additive manufacturing (AM) eases conventional manufacturing (CM) constraints allowing new design freedom. Yet designers still rely on experience and face AM high energy demand and variable waste benefits. This paper introduces an ecodesign approach to AM workflow through a tool comparing AM and CM via lifecycle metrics. The tool anticipates design and sustainability challenges providing environmental insights already at initial stages. This is highlighted with two use scenario: a new design and a redesign task. Future work involves tool development and validation with industrial case studies.

Designers use GenAI tools during bioinspired design (BID) process to understand biological inspiration. We investigate the influence of using ChatGPT with BID on their creative thinking. We present BID stimuli to 30 designers in three modes: BID only, ChatGPT only, and BID + ChatGPT; and record their EEG data across four design phases. Their creativity is analyzed through convergent and divergent thinking (CT and DT), measured by average β and α TRP, respectively. Results show that BID stimuli’s influence on CT and DT is mode and phase dependent, indicating CT and DT as continuous processes.

In a circular economy, repurposing extends product lifecycles and reduces resource use. However, identifying feasible repurposing opportunities remains challenging. This study therefore evaluates the capability of large language models to identify such repurposing scenarios and their relevant properties, using documented repurposing cases from peer-reviewed literature. Three models were tested, revealing potential in identifying repurposing scenarios, but also highlighting the need for structured methods and further research due to systematic limitations in property identification.

This study presents a lean experimental method for investigating Proofs of Concept (PoCs) in early product development. By adapting and extending Design of Experiments (DoE) with complementary frameworks, the method enables efficient identification of minimal functional parameter sets. Based on a cube-oriented model and iterative one-factor-at-a-time (OFAT) testing, the design space is systematically refined. Experimental validation on a smart shaft–hub connection demonstrates the method’s effectiveness in reducing required samples while ensuring feasibility.

Generative AI and additive manufacturing (AM) are shifting orthotic design from generic devices to data-driven, patient-specific solutions. This paper presents a systematic review of Generative AI in Design for AM (DfAM) for orthotic devices. It examines how AI-driven methods generate customised, lightweight orthoses via 3D printing, improving both design efficiency and anatomical fit. The review identifies biomechanical and workflow challenges that hinder adoption and outlines how Generative AI can advance orthotic DfAM, providing a conceptual workflow and suggestions for future research.

Digital platforms for food and mobility offer sustainability and convenience, but their global adoption is context-dependent. This paper analyzes eight platforms in Turkey, contributing to the discourse on sustainable consumption. The analysis reveals diverse platform configurations and identifies key consumer barriers to widespread adoption, including trust issues, platform misuse, power imbalances, and limited service. The paper concludes with recommendations for motivating Turkish users, managing stakeholder trust dynamics, and leveraging existing consumption habits in new platform design.

The following article explores an emerging theoretical framework for ‘sound-based material theatre’, a form of post-instrumental, post-puppetry performance practice. Whitehead’s ‘philosophy of the organism’ is employed as a foundational vocabulary to describe the modes of interaction and synthesis of entities in an intermedial ecology. Drawing on instrument design theory, the discussion connects processes of embodied learning, mediation and distributed agency with a collaborative ‘animist’ approach to composition and performance. Challenges of mediation in intermedial practice are examined in relation to the perceived separation of senses and disciplines. Foucault’s analysis of the pre-classical epistemology of resemblance is used as a model for describing different types of cross-modal relations between materials, applied as a ‘nexus’ method of orchestration towards an ideal of a ‘living’ organism of intermedia.

This paper presents a pedagogical tool for the co-design of systemic and resilient Nature-based Solutions for carbon removal. Tested with nine participants, it significantly improved understanding of NbS dynamics. Wilcoxon tests showed higher scores for all thinking skills derived from Bloom’s taxonomy (p < 0.05), with notable gains for higher-order skills. Participants reported that the tool was intuitive and engaging, fostering collaborative learning. Results confirm its educational value and potential to engage creative and resilient NbS design.

The market for transcranial direct current stimulation (tDCS) expands. tDCS is a non-invasive technique that delivers a weak direct electrical current to the scalp via electrodes. It is used for enhancing cognitive functions and mood. Existing research addresses technical aspects; yet, understanding users’ perceptions and broader design issues are crucial for acceptance and usability. This paper investigates the perceptions of tDCS practitioners, volunteers, and designers on commonly used electrode fixation methods. It presents design dimensions and recommendations for novel tDCS designs.

Children with Developmental Language Disorder (DLD) often experience difficulties with morphosyntax and discourse processing, which hinder their ability to establish referential coherence. While pronoun resolution has been extensively studied in typically developing (TD) children, little is known about how children with DLD process pronouns in real time, especially in Spanish—a language with rich morphology and flexible word order. This study investigated how Spanish-speaking children with DLD interpret third-person subject pronouns during sentence comprehension, examining their use of semantic and syntactic cues in reference resolution. Across three eye-tracking experiments, we tested children’s reliance on semantic gender cues in overt pronouns (Experiment 1), on syntactic cues such as grammatical role and order of mention in overt pronouns (Experiment 2), and on these same cues in null pronouns (Experiment 3). Participants were 48 Spanish–Catalan bilingual children: 16 with DLD, 16 age-matched TD peers, and 16 younger TD children matched by mean length of utterance. Eye movements during a visual world task were analyzed using growth curve and mixed-effects models. Results showed that children with DLD used semantic gender cues when available and relied on first-mentioned or subject referents when such cues were absent, suggesting compensatory use of structural heuristics in pronoun resolution.