Data-driven design is expected to change design processes and organizations in significant ways. What actions should design managers take to ensure the best possible outcomes in this new data-driven design environment? This paper employs an interdisciplinary literature survey to distill key impacts that data-driven design may have on designers, design teams, organizations and product users. Findings reveal that designers may need a broader set of skills to be successful. For data-driven design to be most effective, design managers will be challenged with many integration tasks, including the integration of AI-based tools into design teams, the closer integration of interdisciplinary teams, the integration of qualitative design thinking methods with new data-driven design paradigms, and the integration of data and algorithms into traditional human-centred design practice, in an effort to overcome cognitive limitations and augment human skill. This paper identifies gaps in the literature at the intersection of data-driven design and design management, design thinking, and systems thinking.

With the increasing implementation of artificial intelligence (AI) in the design process, it is crucial to understand how users will accept AI-designed products. This work studies how the public currently perceives an AI's design capability as compared to a human designer's capability by conducting an online survey of 205 people via Amazon Mechanical Turk. The survey collects the respondents' perception on 16 specific bicycle design goals, demographic information, and self-reported level of design and AI/ML knowledge. Findings reveal that people think an AI would perform worse than a human designer on most design goals, particularly the goals that are user-dependent. This work also shows that the higher people's self-reported level of knowledge in design and the older they are, the more likely they are to think an AI's design capability would exceed a human designer's capability. The insights from this work add to the understanding of user acceptance of AI-designed products, as well as human designers' acceptance of AI input in human-AI teams.

Human-AI collaboration (HAIC) is a promising strategy to transform engineering design and innovation, yet how to design artificial intelligence (AI) to boost HAIC remains unclear. Accordingly, this paper provides a new, unified, and comprehensive scheme for classifying AI roles. On this basis, we develop an AI design framework that outlines expected AI capabilities, interactive attributes, and trust enablers across various HAIC scenarios, offering guidance for integrating AI into human teams effectively. We also discuss current advancements, challenges, and prospects for future research.

Materials experience in design involves the meanings that materials convey to users through its expressive characteristics. Such meaning evoking patterns are influenced by parameters such as context, product (e.g.shape) and user. Consequently, there is a need to standardise experiential material characterisation and large-scale data collection, by means of a meaning-less or ‘neutral’ demonstrator to objectively compare materials.

This paper explores the conception of this neutrality and proposes two opposing strategies: neutrality through complexity or through simplicity. In a pre-study with 20 designers, six associative pairs are selected as neutrality criteria, and shaped in 240 forms by 20 (non) designers in a main workshop. Following the simplicity strategy, these forms are averaged out in three steps by a team of five designers, based on a consensus on of delicate-rugged, aggressive-calm, futuristic-calm, masculine-feminine, traditional-modern, and toylike-professional, resulting in a selection of four averaged neutral forms.

Finally, future research will focus on complexity to increase interactivity, so that consumers might be triggered in extensive material exploration.

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.

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.

It is essential to graduate students to contribute researching in their academic field. Although it leads to the success of academic career path, the students are more at high risk of mental health problems. Thus, this study attempted to reveal underlying causes of the problems, figure out coping techniques and explore design interventions that can improve of graduate students’ mental health quality. We conducted interviews with one health professional expert and twenty-five graduate students. Design Sheet was created to elicit design solution ideas and distributed to ten professional designers. From the research, we have found out that graduate students are suffering from multiple reasons however there are unmet mental health needs among graduate students. By the end of the paper, we propose five design guidelines for designers to make products or services to promote mental health of graduate students.

The rise in the number of people living with long-term conditions is precipitating a shift towards the development of wearable technologies that can monitor our health remotely. This shift makes it possible to rethink the healthcare structure towards awareness and proactive prevention instead of treatment through empowering users, e.g. patients for self-management of their health. In a sector towards individual specialization and relying on personal healthcare management, design has a key role in user participation and engagement. This paper reports a co-design study that empowered the participants as designers to design human-centred interventions that foster sun protection behaviour in young men. The findings from this study show the following: 1) sun protection concepts to enhance young men's engagement in sun protection behaviour, 2) the integration of gender-aware design in digital health wearables contributes towards better user engagement in wearable technologies of the future.

The breadth of media and approaches used when prototyping are vast, with each holding inherent properties that vary their suitability for a given prototyping activity.

While several have established classifications of types and purposes of prototypes, there is little by way of guidance for designers on how select and strategise prototyping given their activity needs, or how the prototype chosen may influence their process, success or efficiency.

This paper presents nine affordances of prototypes derived from literature, together characterising the properties of prototyping media or approaches that affect their suitability across prototyping activities.

The affordances are illustrated through application to physical and digital classes of prototypes and four real prototype cases, showing descriptive capability, inherent differences between the media, and enabling direct and consistent comparison.

By mapping affordances across many media and approaches, this work enables better method selection to align with activity needs, better description and comparison of media and approaches, and the ability the broadly interrogate and direct future development of prototyping technologies.

Additive manufacturing enables new possibilities for the design of end products. These are rooted in the potentials of the manufacturing technology, such as flexible, tool-free production. These potentials can be used for the economic and flexible production of customized products. To support the use of the potentials, a development method was created which identifies optimization areas within a product. Therefore, the complexity is reduced by using of product functions. Characteristic functions and structural configurations are used to identify optimization areas. This contribution describes the application of the new development method to an existing mechanical transtibial prosthesis. In doing so optimization areas are identified which may make use of the potentials provided by additive manufacturing. One area is the interface between the prosthesis and the ground. By analyzing walking environments and the gait cycle the need for walking assistance on deformable surfaces was identified. Significant improvements were achieved through a functional integrated, additive manufactured foot sleeve.

This paper presents an EEG (Electroencephalography) study that explores the correlation between the EEG variation across design stages and the quality of the design outcomes. The brain activations of 33 volunteers with engineering backgrounds were recorded while performing a design task using a morphological table to develop an amphibious bike. The EEG variations from the analysing/selecting stage to the illustrating stage were analysed based on the EEG frequency band and channel sets. A significant correlation between the detail level of the design outcome and the power variation mode was observed in theta, alpha and gamma bands, each involving different channel sets. Compared to the assessment results from two evaluators, using EEG variations as a proxy of the detail level of the design outcome could reach a maximum accuracy of 0.727, precision of 0.765, and recall of 0.889. These results also provide suggestions on the selection of the frequency bands and channel sets to achieve better prediction performance according to each metric.

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.

Customer preference modeling provides quantitative assessment of the effects of engineering design attributes on customers’ choices. Utility-based approaches, such as discrete choice model (DCM), and network analysis approaches, such as exponential random graph model (ERGM), have been developed for customer preference modeling. However, no studies have compared these two approaches. Our objective is to identify the distinctions and connections between these two approaches based on both the theoretical foundation and the empirical evidence. Using the vehicle preference modeling as an example, our study shows that when network structure effects are not considered, results from ERGM are consistent with DCM in most of the test cases. However, in one case where customers have varying choice set with multiple alternatives, inconsistencies are observed, possibly due to the discrepancies of the two models in taking different information when calculating choice probabilities. The insights will lead to valuable guidance for choosing the technique for customer preference modeling and co- developing the two frameworks to support engineering design.

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.

Sketching ideas and building physical prototypes are common in early stage product development. They are used for learning, testing ideas, proving concepts and sharing knowledge. Laser cutting is a popular tool for making physical prototypes due to its accuracy, robustness and speed. Computer aided design and vector graphics software are the main tools used for designing parts for laser cutting. Several sketch- based interfaces have been developed to support the process, using tools such as stylus pens with intuitive sketch-like commands.

A proof-of-concept prototype for capturing a hand drawn sketch and converting it to a laser cuttable file has been developed. In this pilot study we attempt to discover when drawing design by hand on paper can be better or more efficient than conventional methods, for developing physical prototypes with laser cutting in the context of early stage product development. This includes testing the accuracy of the tool, a pilot experiment comparing drawing speed and accuracy, example use cases utilizing pencil and paper, and a simple design challenge experiment.

Behavioural design has emerged as an important domain of design practice and research due to its ability to deliver the desired outcomes beyond technical designs. Research on behavioural design is not successful in discerning it from other design domains, which is important for theory building. This paper discerns the unique characters of behavioural design by tracing the emergence of behaviour in design. Twelve interviews from six behaviour design cases belonging to four firms has been used to further discern the unique characteristics resulting into the conceptual model of behavioural design

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.

Within the scope of Design for Sustainable Behaviour, the connection between behavioural change strategies and design idea generation has received limited attention. This paper highlights metaphorical thinking in product design to stimulate sustainable behaviour. In particular, the current study proposes a metaphor-based design method to guide designers on how to associate product features with behavioural and experiential cues through metaphors. We next report two design cases to evaluate this method. In the end, the shortcomings of current research and future developments are also discussed.

The use of serious games is more and more popular in the medical filed, mainly for home-based rehabilitation therapy. In this context, some design principles were already proposed. Designing serious game for evolution diseases assessment is challenging and necessitates a new approach of this principles. Working with physiotherapists at the origin of the Motor Function Measurement assessment scale, the development of a dedicated serious game is proposed based on new contextual principles.

As digitization progresses, the integration of information and communication technologies in technical systems is constantly increasing. Fascinating value potentials are emerging (e.g. autonomous driving), but also challenges in the system development. The constantly increasing product complexity and degree of networking require a systemic development, which is fulfilled by established approaches of Model-Based Systems Engineering (MBSE). To ensure the reliability of tomorrow's systems, an integrative and early consideration of security and safety is additionally required. In order to show the possibility and consequences of failures and attacks, the paper develops a modeling language that links established and partly isolated security and safety approaches within a consistent metamodel. The developer is enabled to synthesize system architectures transparently on an interdisciplinary level and to analyze attack and failure propagation integratively. The approach uncovers synergetic and especially contrasting goals and effects of architectural designs in terms of safety and security in order to make adequate architectural decisions based on trade-off analyses.