Natural Language Processing (NLP) has been widely applied in design, particularly for analyzing technical documents like patents and scientific papers to extract engineering design knowledge. This work aims to enhance this process by integrating the Axiomatic Design methodology with NLP techniques applied to patent texts. The objectives are to (1) extract Functional requirements (FRs) and Design parameters (DPs), and (2) identify how FRs and DPs are related in text (Axiomatic relations). The second objective is particularly challenging due to limited focus on understanding semantic relations in literature, and previous studies often extract Axiomatic relations in an unstructured way. The approach achieves 60% precision for the first objective and 30-50% for the second. Moreover, a case study shows the practical application of this methodology to assist the work of designers.

A roadmap for advancing sustainable and circular designs within the automotive industry is proposed. The emphasis is on the critical role of collaborative ecosystems following the increased transparency and traceability underway in regulations. Emerging Digital Product Passports are central means in Europe’s Green Deal and expects to drive transformation of practices in the automotive ecosystem. The study, conducted by researchers in collaboration with a global truck manufacturer, identifies key areas for action, including data quality, stakeholder value, and communication strategies, to facilitate the circular and sustainable transformation. The vision and actions proposed were refined in workshops with automotive suppliers and service providers. By addressing these challenges, the automotive industry can leverage from data accessibility and accelerate its shift towards sustainability.

Robust Design is essential for developing high-quality products by minimizing their sensitivity to variation and uncertainties from diverse sources. Despite the wide range of approaches from industry and research, it faces challenges due to their siloed usage. Motivated to gain a better understanding of these challenges and to derive implications for how to overcome them, this paper discusses different viewpoints on Robust Design, taking into account different life cycle phases, domains, and system levels. This highlights the challenges of enhanced product complexity and shifting focuses, for instance, when it comes to cyber-physical systems or sustainable design, and the need for collaboration. Accordingly, the vision of a collaborative approach to Robust Design in a team is presented, in which the actors’ strengths are combined to further increase efficiency and significance.

Generative Design (GD) tools can produce high-performing components with complex geometries that are challenging to conceive via traditional methods. While potentially disruptive, GD tools have yet to achieve widespread use in industry. One reason is that current GD tools are limited to manufacturing methods capable of producing intricate geometries that GD often creates such as 3D printing. To overcome this barrier, this paper quantifies the benefit of altering generatively designed parts to use standardized elements like wire stock and sheet metal via processes such as CNC bending and water jet cutting. Using a parametric cost model, we show that parts incorporating standard components can halve the unit price for production volumes of only 4 parts. Finite Element Analysis (FEA) reveals that replacing up to 60% of part volume has minimal impact on performance. Our findings highlight a gap and opportunity in existing GD research.

This study evaluates a framework for translating user scenarios into engineering specifications with AI integration. We conducted workshops with AI-assisted and non-AI teams to assess AI’s impact on usability, efficiency, and collaboration. We collected data through surveys, interviews, and observations. Results indicate the framework is moderately to highly usable. While AI improved efficiency, it did not enhance output comprehensiveness or collaboration. Information overload and limited contextual understanding hindered AI integration. The study highlights AI’s potential as a technical consultant and interdisciplinary bridge, emphasizing the need for domain-specific training and enhanced interactivity capabilities to optimize human-AI collaboration. These findings underscore AI’s role in engineering design, contributing to scalable methods for developing user-centered specifications.

Design method validation is fundamental to ensure that design methods achieve their objectives in the intended situations and are accepted in practice. Although various method validation approaches have been developed, there is still a lack of practical guidance for planning validation studies based on project characteristics. To address this, an intensity map of the validation effort is presented as the core of a scenario-based planning approach. It categorizes projects according to the novelty of the method and the state of research on the problem or the research area, enabling the required validation studies, their sequence and validation criteria to be identified. Thereby, researchers can plan validation studies and estimate the required effort situation-based, allowing for a better alignment with their individual project characteristics before starting studies.

Current quantitative methods for estimating product-related environmental emissions face limitations in supporting sustainable design, particularly in second-life product strategies. This paper highlights challenges in accurately assessing emissions and environmental impacts under existing regulations, which often fail to reward designs enabling circularity. Through examples of current practices, it underscores methodological ambiguities and regulatory gaps, proposing a research agenda for improved tools and frameworks. These advancements aim to better support the design, production, and certification of sustainable, second-life-ready solutions, fostering more effective environmental impact reduction. Additionally, the paper emphasizes the need for regulatory adaptation to incentivize circular design practices, ensuring a fair evaluation of products conceived for second-life applications

This paper introduces a novel approach to analysing design protocols using a combination of methods. It describes an approach using a synthesis of concept extraction (using an LLM), semantic analysis (using word vectors and conceptual clustering), and network analysis (following graph construction). It suggests that the resulting measures are useful for studying design framing and for aiding qualitative analysis. It demonstrates this technique with data from a study of 17 designers addressing two design problems. The method enables the comparison of designers working on the same problem as well as the study of individual designers’ use of concepts over time during a think-aloud study.

The increasing number of accidents involving electric vehicles (EVs) and pedestrians underscores the need of enhancing pedestrian safety. Autonomous vehicles (AVs), which have been introduced to mitigate traffic injuries caused by human error, still miss pedestrian trust due to the absence of a human driver. To improve pedestrian perceptions, EVs and AVs must integrate communication interfaces. This study administers two questionnaires to assess pedestrians’ emotional responses when crossing in front of EVs and AVs, and their preferences of modes of interaction. Vehicles’ ability to communicate their intentions through visual signals results crucial for pedestrians. Finally, findings regarding signals effectiveness when interacting with EVs and AVs allow for guidelines to emerge for the design of EAVs interfaces, offering valuable insights for the development of such vehicles.

The complexity and dynamism of global markets is driving the manufacturing industry to evolve from product-based business models to solution providers by integrating smart services. This shift poses challenges, particularly for the organizational design of technical service organizations that deliver these services. Despite the growing importance of servitization, research on the organizational impact of smart services remains limited. Combining a systematic literature review and case study approach with expert interviews, this study examines how smart services affect organizational design of technical service organizations, in the following dimensions: structure, people, processes, and reward systems. The findings offer initial design approaches for manufacturers transitioning to smart service delivery and advance theoretical and practical insights in this field.

Spatial Computing (SC), the use of technology to blur the boundaries between physical and digital into an efficient, intuitive, high performance set of tools, holds huge promise for engineering design. With dramatic and accelerating industry prominence but little research in the design field, there is a need to generalize and frame SC for design. This paper contributes an operational framework for Spatial Engineering (SE) systems highlighting the roles of physical and digital users, objects, environments, and data, and five capabilities required for implementation. It then identifies value propositions for SE evidenced from review of the design field, including design activities in which value is generated. Finally, it presents research opportunities centered on good practice, system interaction and technology, and balancing overhead with the value that these systems provide.

Technical standards provide order and consistency in application domains; however, standards development organizations produce large families of related documents containing significant amounts of information that can be difficult to access, evaluate, and produce consistently. We describe standards as linguistically, socially, and conceptually dynamic constructs using theory drawn from systems engineering and linguistics to create a model of standards documents that can be updated, evaluated, and queried to retrieve information reliably. We describe the theoretical basis for this model from multiple perspectives and explain broadly how it can be used to retrieve relevant information from standards.

Topology optimization is a powerful tool for the development of light and strong structures. Due to the preliminary nature of the resulting design proposals, a geometry reconstruction process is required. This primarily serves the purpose to create a functional design. In doing so, parameterization of the geometry and the option to modify are demanded in product development as well as automation. A specific medial axis based reconstruction method not only facilitates the automation, but also the intervention with several possibilities for modification of an optimized design proposal. In this paper, we examine at an examplary use case, how this practice could reduce design iteration cycles, although intermediate new design requirements emerge. We discuss the advantages and limitations of this approach.

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.

This research addresses the critical need for designing alternative healthcare monitoring systems that support health benefiting parent-child interactions during hospital stays, especially in neonatal intensive care units (NICUs). We developed a HIPAA-compliant, remote healthcare monitoring system designed to facilitate positive interactions between parents and their infants such as skin-to-skin contact. To evaluate the proposed system, we conducted a proof-of-concept experiment using video and sensor data collection to assess the system’s feasibility and usability with adult participants. Additionally, we examined participants’ subjective experiences through post-interaction surveys and interviews. Overall, the system was perceived as helpful in supporting caregiver-patient interactions. Future improvements can address concerns about continuous monitoring and data management.

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.

Uncertainty in coping with sustainability demands poses a challenge to decision makers concerned with manufacturing companies’ product engineering. Therefore, our paper reports on a newly developed guide to address their uncertainty and support them in initiating targeted sustainability action. The guide, based on an interview study (n = 25; 4 company cases and 1 consultancy) and a systematic literature review, addresses decision makers in product engineering and beyond. It was initially applied and evaluated in company workshops. The guide provides success criteria and reflection questions for each step toward targeted sustainability action: understanding, operationalizing, and implementing. This paper outlines the main concepts behind the guide and contributes to the literature by suggesting a novel approach to sustainability action in product engineering by addressing uncertainty.

Additive manufacturing is enabling on-demand fabrication of desirable polymer designs. Due to the technology’s widespread use, there is a need to ensure sustainable design approaches are practiced. Here, thermoplastics for fused deposition modeling is reviewed for life-cycle stages, mechanical properties, and design strategies. Life-cycle stages assessed include formulation, processing, applications, and end-of-life as well as recycling processes. Mechanical properties are considered for recyclable thermoplastics, with fillers to enhance functionality. Finally, design methods are considered to create mechanically efficient designs, such as metamaterials, that reduce material usage and processing time. The review highlights the great potential for creating sustainable designs with additively manufactured polymers, and their mechanical capabilities for broad applications.

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.

AI is increasingly used for systems and companies are integrating Machine Learning methods as well as Generative AI into modern products. For Systems Engineering this leads to new challenges, for example due to the increasing importance of data quality, data privacy or new legislation. This article highlights key challenges arising from the integration of AI components into technical systems and discusses the impact on classical role models for Systems Engineering. The paper presents results from a literature review as well as a view on how the development of AI-based systems is transforming traditional Systems Engineering from perspective of design teams. New demands on data quality assurance and legal risk management as well as establishing new roles in Systems Engineering are discussed. In addition, theses for shaping the future of Systems Engineering are presented.