The success of complex product development projects strongly depends on the clear definition of target factors that allow a reliable statement about the fulfilment of the product requirements. In the context of tolerancing and robust design, Key Characteristics (KCs) have been established for this purpose and form the basis for all downstream activities. In order to integrate the activities related to the KC definition into product development as early as possible, the often vaguely formulated requirements must be translated into quantifiable KCs. However, this is primarily a manual process, so the results strongly depend on the experience of the design engineer.

In order to overcome this problem, a novel computer-aided approach is presented, which automatically derives associated functions and KCs already during the definition of product requirements. The approach uses natural language processing and formalized design knowledge to extract and provide implicit information from the requirements. This leads to a clear definition of the requirements and KCs and thus creates a founded basis for robustness evaluation at the beginning of the concept design stage. The approach is exemplarily applied to a window lifter.

While volume-driven industries such as automotive are characterized by a high degree of data backflow across all production cycles, there is still a certain residue in the planning and construction of process plants. This is firstly due to the high proportion of customer-specific requirements and secondly to the significant amount of value added on site during construction. To handle recurring project-specific process plants as time- and cost-efficiently as possible, optimal information exchange among contractors of various disciplines and the plant developer is a prerequisite. For this purpose, a holistic digital representation of the plant is created, which consolidates all relevant information in one place serving as a foundation of multiple digital twins. An approach to identify and define relevant information depending on their subsequent use is developed. On this basis, a framework is proposed to enable a multipliable BOM-based automatic definition of information backflow to instantiate digital representations in parallel to the planning and construction process. Furthermore, project-specific contextual information will be captured and referenced in a structured form preventing their loss for subsequent similar projects.

Endotracheal intubation is performed to provide ventilatory support to a patient of any age. Every medical procedure that requires general anesthesia requires intubation, and for this reason, it is a life-saving procedure. This maneuver is a challenge in pediatric patients between 0 months and 12 years of age, since their anatomy and oxygen consumption differ compared to an adult.

In patients with difficult airways, where there is no good visibility of the structures, a videolaryngoscope is used. It has higher success rates compared to a conventional laryngoscope. Its use has become widespread since the COVID-19 pandemic, as it reduces exposure to respiratory secretions.

This article presents the design, manufacture and testing of a low-cost pediatric videolaryngoscope, for patients between 6 and 12 months, and which are intended to respond to the low availability of this type of equipment in Colombian health care centers. The BioDesign Innovation Process methodology was adapted for its creation. The prototypes were manufactured using 3D printing. Validation was performed by 28 experts using simulators and the results were promising, obtaining a success rate of 98.8% for the designed device.

Various aspects of the design process often lead to stress. This study used pre- and post-task surveys to gather information regarding the designer's cognitive experience, physiological response, and perceived sources of stress during concept generation, concept selection, and prototyping. Results confirmed that design is highly cognitive, and that mental stress is present. Variability in the results also suggests that a physiological stress component might be present. Additionally, perceived sources of stress were examined, and recommendations were offered for instructors of design courses.

Conventional failure analysis ignores a growing challenge in the responsible implementation of novel technologies into engineered systems - unintended consequences, which impact the engineered system itself and other systems including social and environmental systems. In this paper, a theory for unintended consequences is developed. The paper proposes a new definition of unintended consequences as behaviors that are not intentionally designed-into an engineered system yet occur even when a system is operating nominally, that is, not in a failure state as conventionally understood. It is argued that the primary cause for this difference is the bounded rationality of human designers. The formation of unintended consequences is modeled with system dynamics, using a specific real-world example, and bifurcation analysis. The paper develops propositions to guide research in the development of new design methods that could mitigate or control the occurrence and impact of unintended consequences. The end goal of the research is to create a new class of failure analysis tools to manage unintended consequences responsibly to facilitate engineering design for a more sustainable future.

Nowadays, companies operate in increasingly competitive and dynamic markets with fast-changing customer needs. Simultaneously, major advances are being made in information and communication technologies, and the digitization of products is progressing. Based on these economic and technological trends, smart product-service systems (PSS) are emerging as a new form of business model. Recent studies show that the transition to developing smart PSS is a major challenge for companies and that they require methodological support, as their internal structures are undergoing significant changes.

In order to provide a sound basis for support, we have undertaken a comprehensive study to identify requirements for a smart PSS development framework. 24 interviews and 5 workshops with companies that have recently focused on the development of smart PSS provide a rich set of empirical data to explore the challenges faced by companies today. We systematically analyzed the data and evaluated the results with our respondents. To increase the robustness and generalizability of our findings, we performed a contextual literature review and analyzed additional cases. This led us to a set of 17 requirements for a smart PSS development framework.

Combinatorial Design such as configuration design, design optioneering, component selection, and generative design, is common across engineering. Generating solutions for a combinatorial design task often involves the application of classical computing solvers that can either map or navigate design spaces. However, it has been observed that classical computing resource power-law scales with many design space models. This observation suggests classical computing may not be capable of modelling our future design space needs.

To meet future design space modelling needs, this paper examines quantum computing and the characteristics that enables its resources to scale polynomially with design space size. The paper then continues to present a combinatorial design problem that is subsequently represented, constrained and solved by quantum computing. The results of which are the derivation of an initial set of circuits that represent design space constraints. The study shows the game-changing possibilities of quantum computing as an engineering design tool and is the start of an exciting new journey for design research.

The objective of this paper is to explore challenges identified for implementation of scrum for hardware development intersect with agile principles found in the literature. A series of comparative analyses are done at the textual level, through logical intersections, and through thematic analysis. It is shown that there are five underlying themes found across two sets of scrum challenges (constraints of physicality and the 13 principles). These five themes include: flexiblity, chunkability, scalability, endurability, and teamability. These five themes further are found related to the defining principles of the agile manifesto. Using this understanding, future efforts will include empirical case study work to determine the impact that these have on application of scrum methods and tools. Additionally, guidelines should be developed to help hardware product engineers in applying scrum.

Laser Powder Bed Fusion (LPBF) brings the possibility to manufacture innovative near-net-shape part designs. But unfortunately, some designed surfaces suffer from rough surface finish due to characteristics of the LPBF process. This paper explores trends in managing surface roughness and through a space industry case study, a proposed process that uses Additive Manufacturing Design Artefacts (AMDAs) is used to investigate the relationship between design, surface roughness and fatigue. The process enables the identification of design uncertainties, however, iterations of AMDA's can be required.

This paper presents the re-design approach of an urban motorcycle helmet to prevent users bypassing the strap fastening system. Related studies show that although a full-face helmet provides the maximum protection to a rider, in practice, full-face helmeted riders in urban traffic tend to improperly fasten it. On that notion, the design goal was to conceive a helmet that combines the advantages of different helmet types while responding to urban driving needs. During design ideation possible solutions were examined focusing on different ways of accessing and fixating the helmet on a rider’s head, without using a strap fastening system. Preliminary concept development produced three design concepts, that were evaluated using two sets of prototypes: (a) the 3D printing method under a 1:2 scale was used to detect any design faults, while the 3D modeled concepts were evaluated in four different crash impacts regarding total deformation and von-Mises stress, and (b) 1:1 models of the three concepts were used by experienced riders to assess possible usability issues during helmet placement/removal. Results of the two-phase evaluation of the three concepts and design issues for further development of them are discussed.

Robust Design offers a coherent and widely appreciated approach for the parametric exploration of the design space by means of simulation or experimentation, which is well-established in the quality-by design domain. From the perspective of design research, however, this only addresses a relatively narrow part of the design process and is not fully integrated with other design decisions such as concept exploration, the suitable configuration of system elements, or the design of interfaces. Particularly in light of the growing importance of developing technologically advanced and “smart” systems, it seems that a new methodical perspective on Robust Design is needed. Against this background, this paper consolidates knowledge and insights from different research fields and industry sectors. On this basis, new angles to the discussion on product robustness in different domains are explored in order to suggests directions for action and new research areas, both with respect to a methodical RD approach as well as the question of systematic research procedures.

Enhancing the appearance of physical prototypes with digital elements, also known as mixed prototyping, has demonstrated to be a valuable approach in the product development process. However, the adoption is limited also due to the high time and competence required for authoring the digital contents. This paper presents a content authoring tool that aims to improve the user acceptance by reducing the specific competence required, which is needed for segmentation and UV mapping of the 3D model used to implement a mixed prototype. Part of the tasks related to 3D modelling software, in fact, has been transferred to simpler manual tasks applied onto the physical prototype. Moreover, the proposed tool can recognise these manual inputs thanks to a computer-vision algorithm and automatically manage the segmentation and UV mapping tasks, freeing time for the user in a task that otherwise would require complete engagement. To preliminarily evaluate effectiveness and potential of the tool, it has been used in a case study to build up the mixed prototype of a coffee machine. The result demonstrated that the tool can correctly segment the 3D model of a physical prototype in its relevant parts and generate their corresponding UV maps.

Over the last years, academic literature has made significant progress on the development of key concepts, identifying circular product typologies, developing assessment methods, and exploring the synergies with manufacturing trends such as digitalisation or environmental management. Nevertheless, less attention has been paid on describing process model changes necessary for the implementation of circular product development. For this reason, this paper presents the circular Sustainable Product Development (cSPD) morphological field, aimed at providing implementation guidance to business and industry. It describes possible reconfigurations of the Sustainable Product Development (SPD) process model to further integrate circularity R-strategies, design scopes, design guidelines, inter- and intra-organisational actors and criteria for evaluation. With this framework, we intend to identify the most defining parameters in the process model and assign them a discrete number of categorical values so that different combinations explain the generation of prevalent circular product typologies in the manufacturing of durable goods.

The design of an active seat suspension for a mid-class passenger vehicle based on the given set of requirements is considered a combination of four subsystems; the carrier, the actuator, the spring, and the damper. The design of the former two is considered through the 10 and 16 concepts for each, respectively. Two overall designs are proposed for further development. One based on a dual Scott-Russell mechanism and one based on Sarrus mechanism. The first one is evaluated to have high stiffness, the second to be more cost-effective. The detailed design of the first concept is presented.

This research focuses on evaluating a user interface (UI) for an autonomous vehicle (AV) with the goal to determine the most suitable layout for persons with visual acuity loss. The testing procedure includes a Wizard of Oz AV for simulating an automated ride. Several participants are included in the study and the visual impairments are simulated by specially designed glasses. The conclusions help to determine the optimal graphic design of the UI that can be independently used by persons with blurred vision. The results can be applied to improve the inclusiveness and ergonomics of vehicle UIs.

This study provides insights into the capabilities and performance of generative AI, specifically ChatGPT, in engineering design. ChatGPT participated in a 48-hour hackathon by instructing two participants who acted out its instructions, successfully designing and prototyping a NERF dart launcher that finished second among six teams. The paper highlights the potential and limitations of generative AI as a tool for ideation, decision-making, and optimization in engineering tasks, demonstrating the practical applicability of generating viable design solutions under real-world constraints.

Individual traits strongly impact team composition and the biases arising from them can also impact design activities. One such bias highlighted in the study is the familiarity bias (i.e., a bias that might be present between the two individuals due to their prior acquaintance). In order to detect the familiarity bias, participants from 4 universities who evaluated their peers and rated them for (1) their perceived degree of influence, (2) trust, (3) the amount of agreement they had with the other team member and (4) the amount of agreement the other individual in the team had with them. It was found that familiarity bias exists in collaborative teams. Its impact on the four variables, especially on influence, was discovered. In the end, the study briefly highlighted the importance of studying the factors (like the one revealed in this study) that affect influence in design teams as it eventually impacts design outcome. It was found that the individuals who explore most idea clusters, are less likely to be perceived influential and teams having the most influence produced a smaller number of idea clusters. Overall, the study contributes to understanding the factors affecting human cognition and behaviour in the design teams.

The design of topologically optimized structures is straightforward, although the main problem is really to derive the correct structure in each instance. During the development of structures for additive manufacturing in particular, saving weight is crucial because weight is proportional to cost.

In this contribution firstly, different approaches to topological optimization are presented and discussed. While computer-assisted tools provide high accuracy and demand defined conditions, approaches utilizing a pen and paper can be conducted relatively quickly, although these only provide little guidance.

Secondly, a new approach is presented which is advantageous with regard to effort and affordability, yet which maintains an accuracy of results. To support the designer, an artificial neural network is trained to adapt suitable Michell structures within a given design area. These structures depict optimal paths to conduct the loads through a component and provide guidance in designing an appropriate topology.

Evaluation has demonstrated that this new approach is capable of supporting designers in achieving lightweight structures.

This study exhibits that there exists generative ethics in which ethical thinking will allow us to change our perspectives to consider the artifacts’ social effects in design, thereby enhancing our activity to generate novel and practical design ideas.

As an example of practicing the generative ethics, a case for addressing the increasing requirement to properly introduce “artificial intelligence” (AI) systems in society was considered. We applied the ethical design theory to promote the practice of ethical AI design by engineers. To achieve this, we implemented a creativity support tool that can be used based on the knowledge base of AI ethics.

To confirm the validity of the theory and the tool, we conducted user experiments in which the AI research students had to consider the effects of their own research projects with using the tool. We could confirm that the tool actually induced the users to consider social impacts. Some students revealed in response to the questionnaire that the experiment provided them with an opportunity to reconsider their own research theme.

In this study, the ethical design theory and tool will be briefly reviewed, and the experiments will be discussed.

Research funded projects are often concerned with the development of proof-of-concept products. Consequently, activities related to verification and validation testing (VVT) are often not considered in depth, even though various design iterations are carried out to refine an idea. Furthermore, the introduction of additive manufacturing (AM) has facilitated, in particular, the development of bespoke medical products. End bespoke products, which will be used by relevant stakeholders (e.g. patients and clinicians) are fabricated with the same manufacturing technologies used during prototyping. As a result, the detailed design stage of products fabricated by AM is much shorter. Therefore, to improve the market-readiness of bespoke medical devices, testing must be integrated within the development from an early stage, allowing better planning of resources. To address these issues, in this paper, a comprehensive VVT framework is proposed for research projects, which lack a VVT infrastructure. The framework builds up on previous studies and methods utilised in industry to enable project key experts to capture risks as early as the concept design stage.