This study examines barriers for circular ecosystems in literature, and identifies 11 enabling factors for collaboration in circular ecosystems. Based on a web-based analysis of 763 European CE projects, the study analyses how factors are addressed in practice. Collaborative processes, trust building, and technological enablers were most frequent, supporting relational foundations via digital tools. Projects often signal collaboration but rarely detail governance or ecosystem orchestration. Findings highlight design capabilities to foster shared-value creation in circular ecosystems.

E-scooters have cemented their position as a convenient transport solution in urban areas, with hundreds of millions of e-scooter trips completed globally each year. This study investigates and presents useful tyre performance data for 12 e-scooter tyres, including three novel 3D printed tyres made from 90A TPU. The results highlight the potential of 3D printed tyres to provide comparable performance to existing e-scooter tyres. The information presented in this study is useful to better understand the energy losses associated with these devices.

Small and medium-sized enterprises often lack the time, expertise, and tools for effective scenario management. This paper proposes a modular, AI-enabled scenario architecture integrating a guided wizard and expert environment on a shared knowledge backbone. The design aims to reduce effort and tool fragmentation while preserving human judgment, structural quality, explainability, and traceability. The proposed pattern outlines a provenance-aware foresight pipeline with human-in-the-loop capabilities that aims to transform one-off projects into reusable organizational knowledge.

This article motivates the use of MBSE and SysML for organizational development and argues for a model-based integration of sustainable leadership (SL) into sustainable manufacturing (SM). We discuss whether modeling requirements resulting from SM and SL literature can be met by SysML and introduce an initial black box perspective and meta-model. The work is part of a larger research project aiming to transfer findings from SM and SL research into a model-based integrated SM in order to support a human-centered perspective. This work shows that SysML is suitable for organizational use cases.

Current funeral materials prioritise preservation over ecological integration, perpetuating extractive practices that damage environments while reinforcing cultural death denial. Extending the emerging trajectory of regenerative death care, this paper proposes regenerative biomaterials using post-mortem resource recovery via alkaline hydrolysis (water cremation). Effluent burial vessels and bone-ash tree guards demonstrate life-centred design methodologies, positioning soil ecosystems and native vegetation as design stakeholders. The research reveals how biomaterials designed for ecological wellbeing create regenerative infrastructure addressing both human grief and landscape healing needs. Biodesign materials are designed to nurture soil microbiomes and support native plant establishment over 24-month decomposition cycles to challenge industrial death care’s resistance to natural cycles. This work contributes a methodological deepening of regenerative death care beyond harm reduction, establishing methodologies for designing with more-than-human agencies through speculative material experimentation. The project reimagines death not as waste requiring disposal, but as a resource that contributes to ecosystem regeneration.

Human-Centered Design focuses on individuals who struggle to grasp the relational aspects crucial in designing for care. This proposes a relational framework that visualizes the relational expectation misalignments between stakeholders’ perceptions. We extend the Theory of Planned Behavior to model dyadic care relationships. Expert interviews and autoethnographic analysis evaluated the model. Our findings reveal two layers of misalignments: the model’s ability to describe the structure of conflict and its potential as a reflective tool for stakeholders to resolve conflicts.

Chatbot-based surveys offer low-burden, in-situ data collection, yet unconstrained LLMs often drift from research aims. We conducted 359 ultra-short, post-experience voice interviews in a public venue to compare a framework-guided LLM, an unconstrained LLM, and fixed questions. The guided approach produced significantly longer responses than fixed questions and yielded the richest diversity of process-specific accounts. These findings show that probe control is essential for eliciting actionable, experience-grounded feedback in real-world, time-limited settings.

Variant management faces increasing complexity that challenges traditional rule-based configuration approaches. This contribution explores how AI can support the generation of configuration rules (1) by comparing two solution concepts – a deterministic Python-based and an LLM-based approach. Following a structured early-stage AI system development methodology, the research investigates (2) how AI can be methodically integrated into variant management and (3) how implementation factors differ between both approaches. The results reveal distinct trade-offs between transparency and efficiency.

This paper proposes a methodical framework for developing functional surfaces and coatings for circular automotive applications. It addresses three gaps: the missing classification of surface mechanisms, limited empirical PSPP models, and the lack of an integrated link between microstructural surface design and system-level development. The framework connects top-down design with bottom-up materials engineering, introduces working-principle analogues in design catalogues, and offers the use of DoE and sensitivity analysis to build predictive PSPP models.

Custom manufacturers of engineered products face growing challenges in managing complex and variant Bills of Materials (BOMs). This paper proposes a visualization-driven framework for structuring and analyzing overcomplete (150%) BOMs in Engineer-to-Order environments. The framework integrates configurator rule logic, generic BOM structures, and metadata to enable explicit traceability and diagnostic analysis of variant-specific BOMs. A proof-of-concept prototype evaluated in a European fibre-laser manufacturer demonstrates support for variant validation, error detection, and alignment.

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.