The strength of biomimetics comes from its ability to draw from life mechanisms and strategies to design innovative solutions. In spite of recent methodological progresses, more specifically on tools and processes, biomimetics' implementation still faces strong difficulties. Among other things, design teams have a hard time finding and selecting relevant biological strategies. Facing these challenges, we consider an alternative, yet well recognized, approach: the integration of profiles having a training in natural science within biomimetic design teams. As biologists aren't used to work in design teams, there is a need for a process actually guiding their practice in biomimetics and determining the way they will interact with the “traditional” design team. After studying the literature and asking for experts' opinion on the matter, we introduced a biomimetic design process considering this new profile as an integral part of biomimetic design teams. With the final goal of making biomimetics implementable, this proposed theoretical process is currently tested in both a student and an industrial project in order to optimize our methodological contribution with practical feedbacks.

The implementation of Digital Twins has become a common task for many industrial companies to ensure a sufficient digitization of their products and maintain competitiveness. This results in the question of how to compensate additional effort caused by designing Digital Twins. With this paper, an approach for this compensation is presented by creating Digital Twin behaviour through utilizing SysML diagrams and directly derivate usable code from them for a further implementation. This offers a part solution of lowering the threshold for using MBSE and increasing its benefits.

Speculative and Critical Design (SCD) confronts traditional design practice. Instead of reproducing and reinforcing contemporary perceptions of products and services, SCD seeks to change them, with the goal to spur a public debate e.g. on what is a preferable societal development. SCD methods comprise among others speculative narratives and design of critical objects. However, the theoretical fundament of SCD is feeble, and concepts and methods are upheld of mere examples.

The article aims to present the features, methods, and practice of SCD, and locate it in the design field. Following the introduction, section 2 presents features and SCD methods and practices. Section 3 links SCD to traditional design and identifies benefits and challenges relating to its role as a supplement to today's design practice. The final section suggests topics for further SCD research.

The article benefits designers in search for alternatives to commercially oriented design approaches. Findings indicate that SCD can contribute to creating new societal roles for designers, foster innovation in the relationship between designers and users, and encourage creativity through imaginative aesthetics.

The interest in the Circular Economy (CE) has grown in recent years. Digital technologies (DTs) have demonstrated a potential synergy to achieve circular goals at the micro, meso, and macro-level. Although several studies in literature explore DTs and CE linkage, they have not been identified according to their primary research themes. This paper aims to identify the main research streams addressing CE and DTs. From a Systematic Literature Review and Content Analysis, we reviewed 40 articles and classified three primary research streams. (1) Industry 4.0 (I4.0) focuses on the relevance and role of I4.0 in the transition to a CE. (2) The Business research stream evaluated the connection between digital transformation and business. (3) The Sustainability research stream discusses sustainability issues such as waste management and smart cities. Based on the analyzed studies' purposes and gaps, we provide a research agenda for further research. Additionally, we explain the implications of DTs and CE to research on engineering design. Our paper guides researchers in their future research to focus on gaps that have not been answered and position their studies according to their research streams.

ABSTRACT

While extensive modelling - both physical and virtual - is imperative to develop right-first-time products, the parallel use of virtual and physical models gives rise to two interrelated issues: the lack of revision control for physical prototypes; and the need for designers to manually inspect, measure, and interpret modifications to either virtual or physical models, for subsequent update of the other. The Digital Twin paradigm addresses similar problems later in the product life-cycle, and while these digital twins, or the “twinning” process, have shown significant value, there is little work to date on their implementation in the earlier design stages. With large prospective benefits in increased product understanding, performance, and reduced design cycle time and cost, this paper explores the concept of using the Digital Twin in early design, including an introduction to digital twinning, examination of opportunities for and challenges of their implementation, a presentation of the structure of Early Stage Twins, and evaluation via two implementation cases.

Driven by networked Electronic Health Record systems, Artificial Intelligence, real-time data from wearable devices with an overlay of invisible user interfaces and improved analytics, Health 4.0 is changing the healthcare industry. The focus on collaboration, coherence, and convergence that will make healthcare more predictive and personalised. Furthermore, Health 4.0 realises the value of data more consistently and effectively. It can pinpoint areas of improvement and enable more informed decisions. What it also does is help move the entire healthcare industry from a system that is reactive and focused on fee-for-service to a system that is value-based, which measures outcomes and ensures proactive prevention.

In this paper, the authors will first explore the realm of the emerging area of Health 4.0 and identify its opportunities and challenges. This includes understanding the relevant base technologies as well as the design principles for the realization of smart healthcare product, systems and product-service-systems of the future. Following on from there, the authors focus on the role of design in the specific context of healthcare.

Originally developed for the software industry, agile development is being applied in the hardware field nowadays as well due to its benefits when having to deal with volatile, uncertain, complex and ambiguous (VUCA) conditions. However, certain complications arise when applying the concept of agility in the hardware. In this publication, based on the challenges identified by Ovesen in 2012, the current challenges of agile development for hardware are gathered using an embedded design approach, ensuring its actuality based on the latest surveys and empirical data. The current state regarding the challenges is displayed and its interrelations as well as their advancements compared to seven years ago is discussed. Moreover, an attempt to explain the difficulties of applying agile development is given by a hardware-related complexity model.

Additive manufacturing (AM) opens new possibilities for innovative product designs. However, due to a lack of knowledge and restrained creativity because of design fixations, design engineers do not take advantage of AM's design freedom. Especially multi-material AM provides new opportunities for functional integration that hardly considered in ideation. To overcome barriers in the development of solution ideas and utilizing such new design potentials, new design methods and tools are needed. Therefore, in this contribution, a methodological approach for a function-oriented provision of solution principles specific to material extrusion is presented. A tool is developed to facilitate effective guidance in developing solution ideas and to foster a realistic concretization by providing a combination of opportunistic and restrictive AM knowledge. Besides general levers of AM, process-specific design opportunities support the design engineers in exploiting AM's potentials, especially those who are not familiar with Design for AM. Finally, the applicability of the methodological approach is evaluated in an academic study by means of redesigning a hand prosthesis with a grab function.

3D printed heterogeneous lattice structures are beam-and-node based structures characterised by a variable geometry. This variability is obtained starting from a periodic structure and modifying the relative density of the unit cells or by combining unit cells having different shapes. While several consolidated design approaches are described to implement the first approach, there are still computational issues to be addressed to combine different cells properly. In this paper, we describe a preliminary experimental study focused on exploring the design issues to be addressed as well as the advantages that this second type of heterogeneous structures could provide. The Three-Point-Bending test was used to compare the behaviour of different types of heterogeneous structures printed using the Fused Deposition Modeling (FDM) technology. Results demonstrated that the possibility of combining multiple unit cells represents a valid strategy for performing a more effective tuning of the material distribution within the design space. However, further studies are necessary to explore the behaviour of these structures and develop guidelines for helping designers in exploiting their potential.

Generative AI algorithms that are able to generate creative output are progressing at tremendous speed. This paper presents a research agenda for Generative AI-based support for designers. We present examples of existing applications and thus illustrate the possible application space of Generative AI reflecting the current state of this technology. Furthermore, we provide a theoretical foundation for AI-supported design, based on a typology of design knowledge and the concept of evolutionary creativity. Both concepts are discussed in relation to the changing roles of AI and the human designer. The outlined research agenda presents 10 research opportunities for possible AI-support to augment the designer of the future. The results presented in this paper provide researchers with an introduction to and overview of Generative AI, as well as the theoretical understanding of potential implications for the future of the design discipline.

In recent years, the air transport market has quickly grown, creating new civil aircrafts demand, challenging the actual production rate of aerospace industries. The bottleneck of the current civil aircrafts production rate lies in the capability of the manufacturing and assembly facilities in relation to the aircrafts architecture design.

The aim of this work is to develop a methodology and a related mathematical model that can be used at the conceptual design phase for the assessment of criticalities related to the product assemblability. The methodology allows to recognize modules and/or interfaces which are mostly affecting the assembly time providing a design tool for the comparison and evaluation of product architecture alternatives.

A preliminary application has been done on the nose-fuselage of a civil aircraft for passenger transport. The test case provides interesting outcome in the identification of modules and module interfaces which are strongly affecting the assembly phase and required a re-arrangement (new architecture design) for the process improvement.

Human-computer hybrid teams can meet challenges in designing complex engineered systems. However, the understanding of interaction in the hybrid teams is lacking. We review the literature and identify four key attributes to construct design research platforms that support multi-phase design, hybrid teams, multiple design scenarios, and data logging. Then, we introduce a platform for unmanned aerial vehicle (UAV) design embodying these attributes. With the platform, experiments can be conducted to study how designers and intelligent computational agents interact, support, and impact each other.

Early detection and correction of defects are critical in additive manufacturing (AM) to avoid build failures. In this paper, we present a multisensor fusion-based digital twin for in-situ quality monitoring and defect correction in a robotic laser-directed energy deposition process. Multisensor fusion sources consist of an acoustic sensor, an infrared thermal camera, a coaxial vision camera, and a laser line scanner. The key novelty and contribution of this work are to develop a spatiotemporal data fusion method that synchronizes and registers the multisensor features within the part's 3D volume. The fused dataset can be used to predict location-specific quality using machine learning. On-the-fly identification of regions requiring material addition or removal is feasible. Robot toolpath and auto-tuned process parameters are generated for defect correction. In contrast to traditional single-sensor-based monitoring, multisensor fusion allows for a more in-depth understanding of underlying process physics, such as pore formation and laser-material interactions. The proposed methods pave the way for self-adaptation AM with higher efficiency, less waste, and cleaner production.

Prototypes are a common feature of many product design and development endeavours. An ever widening range of prototyping options are available to designers and engineers. May particular options be superior to others, or more appropriate for particular endeavours? This paper reviews current literature on the nature of what constitutes a prototype and the benefits they offer to the discipline. They principally facilitate communication, aid learning, help gain and provide feedback, inform decision making and generally provide superior design outcomes. In order to determine if any particular manner of prototype is preferable for achieving these benefits a comparative study of some of the contemporary prototyping methods is subsequently conducted: A 3D printed prototype (physical prototype), a CAD prototype (represented using a computer monitor), an augmented reality prototype (represented using a tablet device) and a virtual reality prototype (represented using a stereo projector and polarised glasses). The results indicate that while all provide benefits, overall the physical prototype performs best and the augmented reality prototype performs most poorly.

We introduce the concept of social sustainability, intertwined with ecological and economic aspects, to the field of service robots and comparable automation technology. It takes a first step towards a comprehensive guideline that operationalizes and applies social sustainability. By applying this guideline to the project MURMEL we offer a concept that collects and rates social key issues to visualize their individual importance. Social sustainability is an important and often overlooked aspect of sustainable technology development which should be considered in the early development phase.

A neurointerventional training model called HANNES (Hamburg ANatomical NEurointerventional Simulator) has been developed to replace animal models in catheter-based aneurysm treatment training. A methodical approach to design for mass adaptation is applied so that patient-specific aneurysm models can be designed recurrently based on real patient data to be integrated into the training system.

HANNES’ modular product structure designed for mass adaptation consists of predefined and individualized modules that can be combined for various training scenarios. Additively manufactured, individualized aneurysm models enable high reproducibility of real patient anatomies. Due to the implementation of a standardized individualization process, order-related adaptation can be realized for each new patient anatomy with modest effort. The paper proves how the application of design for mass adaptation leads to a well-designed modular product structure of the neurointerventional training model HANNES, which supports quality treatment and provides an animal-free and patient-specific training environment.

This paper reviews the literature on risk management practices and methods in product design and development. Based on an expert workshop by the Risk Management Processes and Methods in Design Special Interest Group within the Design Society and literature review, three key areas are discussed: risk identification, assessment, and mitigation. In each area, researchers have described practices that are used in product development organizations, proposed new methods to support risk management processes and decision-making, and generated evidence to evaluate the effectiveness of these activities.

There have been growing uses of semantic networks in the past decade, such as leveraging large-scale pre-trained graph knowledge databases for various natural language processing (NLP) tasks in engineering design research. Therefore, the paper provides a survey of the research that has employed semantic networks in the engineering design research community. The survey reveals that engineering design researchers have primarily relied on WordNet, ConceptNet, and other common-sense semantic network databases trained on non-engineering data sources to develop methods or tools for engineering design. Meanwhile, there are emerging efforts to mine large scale technical publication and patent databases to construct engineering-contextualized semantic network databases, e.g., B-Link and TechNet, to support NLP in engineering design. On this basis, we recommend future research directions for the construction and applications of engineering-related semantic networks in engineering design research and practice.

Metal additive manufacturing (AM) is revered for the design freedom it brings, but is it environmentally better or worse than conventional manufacturing? Since few direct comparisons are published, this study compared AM data from life-cycle assessment literature to conventional manufacturing data from the Granta EduPack database. The comparison included multiple printing technologies for steel, aluminum, and titanium. Results showed that metal AM had far higher CO2 footprints per kg of material processed than casting, extrusion, rolling, forging, and wire drawing, so it is usually a less sustainable choice than these. However, there were circumstances where it was a more sustainable choice, and there was significant overlap between these circumstances and aerospace industry use of metal AM. Notably, lightweight parts reducing embodied material impacts, and reducing use-phase impacts through fuel efficiency. Finally, one key finding was the irrelevance of comparing machining to AM per kg of material processed, since one is subtractive and the other is additive. Recommendations are given for future studies to use more relevant functional units to provide better comparisons.

Maier and Fadel pioneered Affordance-Based Design (ABD) based on Gibson's revolutionary theory of affordances and Norman's deployment of the concept in his book, “The Design of Everyday Things”. Gibson (1979) introduced the affordance concept into the discipline of Ecological Psychology to address the interactions between an object and an agent. The Ecological approach includes the direct perception of affordances for the user along with a consideration of the users’ biomechanics. However, as the concept of affordance was imported and utilized in different disciplines, including engineering design, some important aspects of Ecological theory were omitted.

This paper is an attempt to review the definitions and different utilizations of the affordance concept focusing on the design of usable products to identify the different views and the missing elements. After addressing the divergent viewpoints of affordances, we provide recommendations to improve the usability aspects in ABD by considering direct perception and ergonomics. We claim that a design (based on affordances) that fails to address both criteria may result in a product that is less usable.