Digital transformation has reshaped the manufacturing sector, driving innovation and new business models. Simultaneously, sustainability pressures and stricter regulations push companies to adopt circular economy (CE) principles, focusing on reducing, reusing, and recycling materials. This transition requires adapting business models, product design, and management while integrating processes such as reverse logistics. Digital technologies play a crucial role by enabling data generation, processing, and analysis, optimizing production, and reducing resource use. However, many companies face knowledge gaps regarding how to implement these technologies effectively for CE. This study addresses these challenges through a systematic literature review, offering a framework that links digital technologies to CE principles, focusing on slowing, narrowing, and closing material loops.

Humans, with their various social identities, form an important part of engineering design. Therefore, designers must reflect on the implications of social identity when designing products. However, little research has examined the quality and content of student designers’ reflections on the importance of social identity in design, and we aim to explore this research gap. The results of our study revealed higher frequencies of responses related to personal experiences and design/action among designers with minoritized social identities. Designers with minoritized identities also provided higher-quality reflections than those in the majority group. These results suggest that designers with different social identities may vary in their ability to critically reflect on the impact of social identity in design and call for the need for new reflective design tools and educational approaches.

Structured reflection can initiate learning, increase team performance and support engineering teams in adapting their engineering design activities or methods. Engineering teams with limited reflection experience use reflection often not effectively. Therefore, additional support in the implementation of reflection, guiding and structuring reflection and in providing goal-related reflection guiding questions is needed. To improve the quality of reflection and enable engineering teams to reflect, a chatbot-supported reflection concept to assist engineers is proposed in this contribution. For this purpose, the potential and challenges of existing chatbot approaches are analyzed and classified. Based on the reflection process and tools from preliminary work, use cases and an initial architectural reflection chatbot concept are developed and presented in this paper.

Product Line Engineering (PLE) and Systems Engineering (SE) are critical for developing complex systems, yet current methodologies inadequately address the integration of variability across multiple layers of system design. This study introduces an integrated variability modeling framework based on FODA and aligned with ARCADIA’s MBSE method, addressing operational, functional, and constructional viewpoints. Validation using Renault’s Advanced Driver-Assistance Systems (ADAS) showcased reduced design time and enhanced configuration adaptability. Key challenges, such as aligning feature models and managing dependencies, were addressed through a modular, layered strategy. The proposed approach ensures flexibility, scalability, and system integrity, offering a robust framework for diverse domains.

Long-term projections are the bedrock of any analysis looking at the sustainability of public finances. This paper computes the changes in economic growth in individual European Union countries needed for government debt-to-GDP ratios to stay on their baseline trajectories (taken from the European Commission’s Debt Sustainability Monitor 2023) under high life expectancy, low-fertility, low-migration, and high-migration scenarios. These scenarios are provided in the Commission’s Ageing Report (2024). We find that deviations of migration from the baseline entail the largest effect on the required rate of economic growth. The effects of the low-fertility scenario are most pronounced in the very long run and sometimes exceed those of low migration. Our findings inform policymakers about the potential role of higher productivity growth in alleviating the public finance consequences of demographic shocks. The importance of higher productivity growth is increased by the fact that in some countries demographic projections tend to be optimistic.

In the 1980s and 1990s, many Latin American countries transitioned from dictatorships to democracies, paving the way for the structural redesign of their foreign policies. In response to sustained feminist mobilization in civil society, by the 2000s several of these countries had established gender divisions in their Ministries of Foreign Affairs. These divisions prioritized the incorporation of gender equality norms in their national and international legal obligations and established protocols to implement gender equality measures. As part of this process, there was also a push for increased participation of women in the foreign policy arena, especially in Argentina, Brazil, Costa Rica, and Uruguay (Fuentes-Julio et al. 2022).

Climate change and rapid urbanisation constitute wicked problems to which the design community must respond. This paper focuses on hybrid smart Nature Based Solutions (NBS) which combine digital, engineered and natural components. Based on case studies and interviews, this paper presents a model to enable manufacturing organisations to navigate the complexities of designing and commercialising such complex systems, focusing on the inter-organisational partnerships required and mitigation techniques to address complexities throughout the project lifecycle. This work challenges existing concepts of hybrid, complex systems to account for NBS and their unique complexities. We argue that smart Nature Based System is a more apt way to conceptualise these solutions which incorporate digital twin, A.I and weather data to deliver urban resilience and sustainability.

Problem framing is a foundational aspect of the engineering design process, shaping how designers perceive challenges and potential solutions. Qualitiative methods, such as protocol analysis, have provided valuable insights about problem framing but are labor-intensive and time consuming. This study explores the use of a NLP technique BERTopic, to analyze framing in design conversations. BERTopic retains contextual nuances, offering a tool for uncovering the diversity and uniqueness of concepts explored by design teams while also making the analysis process more efficient. The results provide one representation of eight design group’s processes, highlighting the different and changing topic representations that emerge throughout a design session. The findings highlight the potential of NLP tools for enhancing our understanding of framing in design cognition and team dynamics.

This study explores the use of agile methods to support Additive Manufacturing (AM) in transitioning from R&D to production. Using a consumer goods company division as a case study, the research examines how agile methods facilitate flexibility, collaboration, and innovation despite challenges such as the materiality of products methods inconsistencies. Findings reveal how tailored agile practices designed for Additive Manufacturing enhance technology readiness and identify areas for improvement, including stakeholder engagement and role alignment. Recommendations are proposed to refine an Agile Design Process Model for Additive Manufacturing and improve technology maturation.

The marine industry is increasingly adopting platform and modular design strategies while facing growing sustainability regulations and emission constraints. This paper proposes an approach that integrates scope 3 upstream CO2 emissions (i.e., procurement) into a Decision Support Environment (DSE) for design space exploration of alternative modular ship design concepts. The DSE, deployed in the conceptual design stage, enables simultaneous testing of various cruise ship configurations regarding CO2 emissions using a bottom-up approach with parametric CO2 models. It leverages data-driven models from existing databases or AI-generated data exemplified in a case study on the hotel system of a cruise ship illustrates how parametric design variables influence CO2 emissions, demonstrating a preliminary result of a prescriptive study in collaboration with a major international ship manufacturer

Gradually transforming abstract, conceptual ideas into physical assemblies is seen as one of the key competences of design engineers. Despite the general recognition of the Embodiment Design task as essential phase of every development process, a general methodical support seems either not available or, at least, not influential. Instead, Embodiment Design is often considered an expert task. In this context, our paper offers a discussion of embodiment design from a design methodology perspective. Drawing from a review of relevant literature, we explain why embodiment might be better understood as the representation of the physical artifact rather than a design phase, provide properties and characteristics of good embodiment solution, and give initial guidance for the transition from the creative exploration of concepts to the actual search for satisfactory, or even optimal, embodiments.

Robust Design (RD) is crucial in product development to ensure that products maintain reliable performance under varying conditions. Design knowledge is fundamental to RD. However, current methods lack a systematic approach to support design engineers in building design knowledge for RD. This paper addresses this gap by introducing a hypothesis-based method for systematically building design knowledge for RD. RD hypotheses are specifically developed for this purpose and are tested through a five-step method. The application of this method is demonstrated in a case study involving a hand-operated coining machine. The results show that the proposed method supports building specific design knowledge through two RD hypotheses. By employing this method, design engineers are systematically supported in making design decisions, leading to more robust product concepts.

Bahiagrass, guineagrass, and vaseygrass are dominant weeds in bermudagrass pastures. Chemical control of these weeds is difficult, as some herbicides damage bermudagrass. The objectives of this study were to assess the effect of glyphosate and glyphosate mixes with imazapic and nicosulfuron + metsulfuron on bahiagrass control and to evaluate the effect of glyphosate and/or imazapic and nicosulfuron + metsulfuron on guineagrass and vaseygrass control under greenhouse conditions. Bahiagrass field trials were conducted in Citra and Ona, FL, in 2016 and 2018, respectively, while greenhouse experiments were conducted in Ona in 2017 and 2018. Glyphosate tank mixes reduced bahiagrass biomass in Ona, whereas at Citra, biomass reduction did not differ between treatments, although visual estimates of control were lowest with glyphosate at 0.28 kg ae ha−1. Results from the greenhouse experiment show that 0.38 and 0.50 kg ae ha−1 of glyphosate were needed to achieve 80% (ED80) control at 30 d after treatment (DAT), whereas 0.60 and 0.47 kg ae ha−1 were required to reduce 80% biomass of guineagrass and vaseygrass at 60 DAT, respectively. Vaseygrass needed lower imazapic rates (0.05 and 0.19 kg ae ha−1) for ED80 control (visual estimates) and biomass reduction, respectively, whereas guineagrass required higher doses (0.31 and 0.28 kg ae ha−1 for visual estimates of control and biomass reduction, respectively). Glyphosate at 0.56 kg ae ha−1, glyphosate + imazapic, or nicosulfuron + metsulfuron reduced guineagrass biomass, whereas imazapic only, glyphosate tank mixes, and nicosulfuron + metsulfuron resulted in the highest vaseygrass biomass reduction. Glyphosate and glyphosate tank mixes were consistent in controlling all grasses, yet imazapic was effective at higher rates for guineagrass.

This paper introduces a method for developing a knowledge graph aimed to enhance collaboration and information management in virtual product development. The proposed methodology integrates data from diverse sources, including CAD models and geometry, requirements and user-related data to construct a knowledge graph that enhances the retrieval and organization of information. Use-cases, such as information retrieval, tracking changes, and user-issue management, are explored to illustrate the potential of the knowledge graph. The paper details the steps of building the knowledge graph, from defining the ontology to implementing the graph using a structured data format. The structured method presented demonstrates significant potential to enhance collaboration and support the virtual development process, potentially leading to reduced development times and costs.

This study examines the effects of linguistic elements in Vocaloid BGM on creativity, fluency and originality, aiming to design sound environments that enhance creative performance. Experiments were conducted under three BGM conditions: voiced-meaningful (VF), voiced-meaningless (VL), and non-voiced (NV). VF utilized the original Vocaloid song with lyrics, NV excluded lyrics entirely, while VL replaced lyrics with the syllable “la.” Results revealed that VF BGM could disrupt concentration and reduce creativity, while VL and NV conditions enhanced relaxation and improved originality. These effects became more pronounced as tasks progressed. A positive correlation was identified between mind-wandering tendencies and creativity, particularly with VF BGM. The findings highlight the importance of tailoring sound environments to cognitive modes and personal characteristics.

Prospective consent in neonatal research poses significant challenges, particularly during urgent, time-sensitive clinical windows of study enrollment. This is especially true at referral centers for large geographic regions. A partial waiver of consent offers a potential translational science approach to enhance access to research participation in critically ill neonates. We compared enrollment rates in a study evaluating pulse oximetry accuracy across neonates with varying skin pigmentation before and after implementing a partial waiver of consent. Overall enrollment increased significantly without creating a racial disparity in enrollment, thereby improving generalizability and efficiency in neonatal clinical research.