This study presents an AI-driven method for generating preinventive structures - initial precursors to creative design concepts - using the Geneplore model as a theoretical framework. Multimodal AI is leveraged to derive preinventive structures from combinations of components of an existing product. This method is evaluated by comparing AI-generated structures of a product to those reverse identified from real repurposing solutions for the same product (IKEA hacks). The appearance of AI-generated preinventive structures in the repurposed designs suggests that this method can inspire and lead to viable design concepts. Implications extend to sustainable design, creative ideation, and the theory-driven development of design methods that support design in constrained solution spaces. Future work can refine these approaches and investigate broader applications in diverse design contexts.

Engineering design is inherently a collaborative process that requires active engagement and effective communication. Project-based Learning (PBL) is increasingly recognized for fostering these essential skills. However, instructors face challenges in objectively monitoring interactions and providing process-oriented feedback, particularly in large-scale settings where free-riders and disengaged participants affect team dynamics. This study introduces a generative AI approach to deliver real-time, scalable, and empathetic feedback that enhances team collaboration. Findings highlight the potential of AI-driven systems to improve student engagement and learning outcomes, though limitations remain in providing context-specific advice. A secure framework for AI integration in collaborative learning environments is also proposed.

Design teams commonly need to explain the rationale or logic behind how they frame design challenges and develop a particular design concept and not others. This paper explores the use of Design Logic Visualizations (DLV) as a boundary object to enhance understanding and communication in convergent interdisciplinary engineering design environments. We developed the DLV as a new design tool, building upon existing design process visualizations like design signatures, and provide a case study from our NASA team. We then use a reflection-based autoethnographic and collaborative inquiry approach to reflect on how the DLVs influenced our team, our process, and our decision-making. The findings suggest DLVs can serve as a succinct storytelling tool, support shared understanding across disciplines and levels of leadership, and, ultimately, influence design outcomes.

In the product development process, the way in which different departments collaborate and communicate affects the challenges faced by employees, their level of motivation, and the time and cost of development. This paper examines the collaboration and communication in technical drawings based on the Geometrical Product Specifications (GPS). The idea of different types of technical drawing documents (ISO/TS 21619:2018) is explained. Based on a survey, a comparison with the industrial application is made. The current status of communication in the departments is analyzed and challenges, potentials and possible measures are considered. The results show that the document types and their possibilities are rather unknown (43%). Another insight was that there is a significant difference between standardization and the (working) reality, in which collaboration plays a major role.

Due to rising product and system complexities, design and engineering have become a team effort that requires well planned and synchronized activities to achieve a high degree of process efficiency and effectiveness. Inspiring high school children to pursue a carreer in this field and preparing undergraduate as well as graduate students for what they will face in practice remains a challenge for societies and institutions worldwide. To overcome this situation, in this paper we present our experience from conducting two courses for Master students and one workshop for high school children based on an online collaboration platform and the digital LEGO framework. We provide insights into the organization of the different formats, the various backgrounds and profiles of their participants, the work results produced by the individual teams, as well as the participants’ learning experience.

With the increasing amount of data in collaborative engineering research, the need for effective and efficient data management is growing. This paper uses a maturity-based process model to examine the implementation of research data management (RDM) in engineering projects. A process model visualizes a research-supported implementation of RDM and helps researchers evaluate their data management strategies through maturity level assessment. For this approach, activities are assigned to different maturity levels based on a maturity level characteristic providing a differentiated view of the implementation of RDM. An example from an ongoing project shows the application and support of the developed maturity-based process model. The work emphasizes the importance of standardized and quality-assured data management for the success of research projects and their contribution to the scientific community

Legumes offer valuable agricultural and nutritional properties to face the urgent need for food system changes. To eco-design legume-based products, the value chains need to consider the constraints of their stakeholders, from farmers to consumers. This article describes an eco-innovation approach combining collaborative value mapping with KCP® workshops to design sustainable legume-based foods. This eco-innovation approach led to the emergence of expected concepts linked to the properties of products and more disruptive concepts related to dynamics in the value chain. Existing knowledge and knowledge gaps were identified. The results highlight the value of articulating value mapping and KCP® workshops. The approach proved to foster innovative, systemic solutions that consider both stakeholders’ needs and sustainability.

The paper proposes an approach called proactive design for sustainability (DfS) in the context of Industry 5.0, for human-centred innovation and environmental sustainability, combined with the technological focus of Industry 4.0. Computer Aided Design (CAD) must integrate sustainability considerations into product development, with the use of Artificial Intelligence (AI), Digital Twins (DTw) and the Internet of Things (IoT) to dynamically monitor and optimise environmental impacts during the design process, with the integration of Key Sustainability Indicators (KSI) into the CAD interface to enable informed decision-making, aligning design parameters with resource availability and environmental constraints. A case study of an autonomous mobile robot (AMR) will show how operational data from the product lifecycle, combined with AI predictions, can reduce energy consumption and emissions.

The advent of virtual reality (VR) enables immersive visualization, evaluation, and interaction with 3D models. Efforts have been made to integrate parametric solid modeling into VR, but efficient 3D solid model processing and intuitive user interface (UI) design remain challenging. This work proposes an architecture, which, unlike existing approaches, integrates the geometric modeling kernel Open CASCADE directly into the game engine Unreal Engine allowing standalone operation on a VR device without external hardware or software. Our prototype supports creating and editing primitives, and applying topological algorithms. 3D models in STEP format can be imported, edited, and exported ensuring compatibility with conventional computer-aided design (CAD) applications. A foundation for CAD in VR is established, focusing on a customizable UI design to enhance interaction in future developments.

Anatomical variations in the upper airway significantly impact the effectiveness of video laryngoscope blades. Existing literature on upper airway dynamics and blade design lacks a comprehensive framework to address these variations. The proposed model uses the extent of mouth opening with three demographic features and three anatomical features in the closed-mouth state to predict the anatomical features in the open-mouth state, which can support the design of a laryngoscope blade. Pearson’s correlation was studied to understand the correlation between the features, and the ordinary least square method was used to develop a model. For all three outputs, a separate model was developed, which gave R-squares of 0.98,0.74 and 0.94. The findings highlight the potential of data-driven approaches to optimize laryngoscope blade designs.

Undisciplined Design (UD) is an emerging approach suited for experiment-driven innovation and creative processes, allowing fluid disciplinary engagement in engineering design. However, its openness and adaptability also introduce challenges, particularly when integration, evaluation, and risk mitigation mechanisms are absent. This paper examines the Google Glass project through the lens of boundary objects, identifying two key dangers in UD: overconfidence in technological inevitability and unintended consequences. The analysis highlights the need for structured checkpoints to manage epistemic uncertainty while preserving UD’s exploratory potential. To address these challenges, we propose incorporating participatory design methods to facilitate cross-disciplinary negotiation and present a decision-making checklist to guide UD projects in product design and innovation.

Traditional design automation enables parameterized customization but struggles with adapting to abstract or context-based user requirements. Recent advances in integrating large language models with script-driven CAD kernels provide a novel framework for context-sensitive, natural-language-driven design processes. Here, we present augmented design automation, enhancing parametric workflows with a semantic layer to interpret and execute functional, constructional, and effective user requests. Using CadQuery, experiments on a sandal model demonstrate the system’s capability to generate diverse and meaningful design variations from abstract prompts. This approach overcomes traditional limitations, enabling flexible and user-centric product development. Future research should focus on addressing complex assemblies and exploring generative design capabilities to expand the potential of this approach.

Organizational design implementations frequently fail, with existing dominant frameworks and tools, such as the ever-present maturity assessments, falling short in addressing the complex, nonlinear nature of socio-technical systems (STS). This paper introduces PhylOrg, a methodology leveraging phylogenetic analysis to guide organizational design by mapping evolutionary pathways of socio-technical traits (STTs). By identifying coherent and efficient sequences of change, PhylOrg minimizes resistance and aligns initiatives with organizational contexts. Grounded in theories of complex adaptive systems (CAS) and evolutionary processes, PhylOrg proposes to offer prescriptive, context-sensitive guidance to Organizational design leaders. A pilot study demonstrates PhylOrg’s potential, highlighting foundational evolutionary traits as prerequisites for more advanced capabilities.

The circular economy has long been regarded as a fundamental strategy for achieving sustainable development. Most recently, it has also been acknowledged as an effective approach to crisis response. This study contributes to this nascent literature by introducing a dual hierarchy of 6Rs strategies as an inspiring framework for circular post-disaster recovery and reconstruction, supporting the “Build Back Better” principle through circular initiatives. The key distinction between the proposed hierarchy and the traditional 6Rs framework lies in the two-vector operationalization of each strategy, addressing both past and future considerations. Also, this article examines the case of war-torn Ukraine as one of the most severe man-made disasters. The study explores Ukraine’s potential for circular recovery within the framework of European Union policies in the construction sector.

Sustainability is no longer just a trend for companies, but is now seen as a mandatory measure for the environmentally friendly and responsible use of existing resources. The Digital Product Passport (DPP) is a transformative tool that aims to increase transparency and promote sustainability throughout the product lifecycle. This paper presents the 150% Information List, a comprehensive framework to help companies identify mandatory and optional data for the DPP. Using a systematic literature review, grey literature analysis and interviews with industry stakeholders, the study compiles 148 data points grouped by product relevance, availability and life cycle phase. The findings highlight the flexibility of the list to adapt to different industries and underline its potential to optimise resource use, meet regulatory requirements and drive innovation in product development.

The transition to renewable energy and the urgent need to reduce greenhouse gas emissions highlight green hydrogen’s role in decarbonizing various sectors. To address the increasing demand, the research initiative H2Giga FertiRob focuses on automating the production of hydrogen electrolyzers, emphasizing PEM stack assembly. Existing stack designs are often incompatible with automation and hinder scalable production. This paper introduces an adapted Design for Automation approach for PEM stacks. Through the evaluation of a reference stack, key design limitations are identified, leading to the development of an optimized stack with reduced part diversity, improved handling, and enhanced automation compatibility. The methodology provides a systematic framework to advance the automated production of PEM stacks, supporting the scalability of green hydrogen in the global energy transition.

This systematic review examines how generative design enhances communication and collaboration in multidisciplinary engineering teams. Using the PRISMA framework and CASP evaluation program, we analyzed 1,105 sources to assess its role in improving workflows, facilitating collaboration, and reducing communication gaps through CAD, algorithmic modeling, and AI-driven platforms. The findings show that generative design supports teamwork, optimizes design processes, and strengthens interdisciplinary collaboration. While widely used in architecture, aerospace, and automotive industries, its adoption in product design remains limited, presenting opportunities for further research and innovation. These insights contribute to a better understanding of how generative design can bridge communication barriers in engineering projects.

Medical phantoms are models used for imaging and therapy, enabling research, quality assurance, and training without human test subjects. Their development relies on selecting tissue-mimicking materials, however the lack of a holistic overview to guide this process poses challenges. This work presents a comprehensive design catalogue for phantom materials, offering a structured overview of materials and their imaging properties for computed tomography (CT), magnetic resonance imaging, and ultrasound, including parameters such as CT numbers, relaxation times, and acoustic properties. It is implemented as a digital tool with filtering options, enhancing usability and decision-making. Despite limitations from incomplete data in the literature, the catalogue establishes a groundwork for a standardized, expandable resource to support future phantom design.