The use of system models within model-based systems engineering (MBSE) is essential for improved communication or system documentation. Previous publications have investigated further reuse of these system models, for example, transforming them directly into discipline-specific models for reuse. The authors refer to this as the term “Utilization” of system models. It aims the compensation of modelling efforts and a further integration of linked models within MBSE. Motivated by a lack of common understanding of this term, a systematic literature review of the state of the art is presented. With this systematic overview, a definition and classification system for different use cases and system life cycle stages are created. These are key results to support engineers and researchers in adopting existing or discovering new utilization approaches. This supports the mission of advanced systems engineering and aims the identification of new research directions coming along with SysML v2 and the advanced systems engineering methods.

The importance of intangible code modularity in open-source software, as well as of tangible product modularity in proprietary hardware, is widely acknowledged. Nevertheless, modularity in open-source hardware (OSH) remains under-researched. This article first describes qualitatively different types of modularity based on two OSH case studies and then quantifies each type of modularity, following a unified network-based approach. The results are discussed and compared within each case to test the ‘mirroring hypothesis’, and between cases to evaluate the impact of physical against intangible modularity types. The ultimate goal is to prompt a discussion into a wide but under-explored subset in OSH.

The 4th industrial revolution (IR) requires new products and business models adjusted to the rapidly changing market conditions, which calls for evolutions in design engineering. In this context, smart design engineering is here defined as a methodology used during the analysis and design of a product or a system, which can be composed by hardware, software and/or services, and that explicitly considers exploiting the technologies and opportunities from the 4th IR. This work contributes to both design theory and practice: (i) it deepens the understanding about the necessary smart design engineering features and shows how these features impact the product design and development process’s (PDDP) key dimensions (procedures, people and tools); (ii) it maps the features’ impact on PDDP’s phases, thus providing practical direction for process improvement. To accomplish these results, a survey was performed on the initial features presented in the literature, which helped to identify new features and to confirm their relation to the 4th IR and their impact on the PDDP. These features were then analyzed against the 4th IR environment perspectives and core technologies, which led to understanding how they can be used to improve the PDDP.

Complexity in product design increases with little understanding of cause and effect. As a consequence, the impact of design decisions (or changes) on the product is difficult to predict and control. This article presents a model of cause and effect for design decisions that avoid circular dependencies: the so-called attribute dependency graph (ADG) models complex system behaviour and properties, and increases transparency by carefully distinguishing between what is realised and what is required. An ADG is a polyhierarchy, with design variables (directly controllable) at the bottom, quantities of interest (not directly controllable) on the top, and intermediate attributes. The dependencies represent causality in a simple sense: assigning values to design variables, representing the cause, will determine the values of the dependent attributes, representing the effect. ADGs do not account for what is required, but for what effects emerge by design activity. A set of rules makes them independent of designers’ views. They provide the structure for so-called INUS conditions, that is, insufficient but necessary parts of unnecessary but sufficient conditions that can be used for requirement development. The modelling approach is applied to one simple synthetic and then to two real-world design problems, the design of a water hose box and a passenger vehicle.

During the design stage, quick and accurate predictions are required for effective design decisions. Model developers prefer simple interpretable models for high computation speed. Given that deep learning (DL) has high computational speed and accuracy, it will be beneficial if these models are explainable. Furthermore, current DL development tools simplify the model development process. The article proposes a method to make the learning of the DL model explainable to enable non–machine learning (ML) experts to infer on model generalization and reusability. The proposed method utilizes dimensionality reduction (t-Distribution Stochastic Neighbour Embedding) and mutual information (MI). Results indicate that the convolutional layers capture design-related interpretations, and the fully connected layer captures performance-related interpretations. Furthermore, the global geometric structure within a model that generalized well and poorly is similar. The key difference indicating poor generalization is smoothness in the low-dimensional embedding. MI enables quantifying the reason for good and poor generalization. Such interpretation adds more information on model behaviour to a non-ML expert.

Engineering design research has focused on developing and refining methods and evaluating design education in design education, design research and design in practice. One important aspect that is not thoroughly investigated is the influence of bias on design within these spaces of design. Bias is known to impact the interpretation of information, decision-making and practices in all areas. These factors are vital in engineering design education, practice and research, emphasizing the importance of investigating bias. The first goal of this study is to highlight and synthesize existing bias research in design education, research and practice. The second goal is to identify areas where bias may be under-researched or under-reported in design. To achieve these goals, a comparative analysis is performed against a comparable field: medicine. Many parallels exist between both fields. Patient–provider and designer–end-user relationships are comparable. Medical education is comparable to design education with the cooperative, inquiry-based and integrated learning pedagogy approaches. Lastly, physicians and design engineers both solve cognitively complex systems-oriented problems. Leveraging research on bias in medicine enables us to highlight gaps in engineering design. Recommendations are made to help design researchers address these gaps.

This paper critically reviews literature about design framing to clarify an understanding of what is meant by the construct of a design frame. It describes the origins of the term design frame and characterises three distinct definitions that can be found within the literature. It reviews empirical studies of design framing to highlight definitional confusion between studies. It discusses the significance of Dorst’s propositional model of design frames and juxtaposes design frames with other related constructs. It clarifies ways that the resolution of nomenclature for describing design framing might lead to a more coherent body of empirical research into this topic. It suggests that there is value in developing a better cognitive model of design framing and outlines potential steps towards such a model.

Research Through Design (RTD) needs to reconsider the meaning of “designing” in the research process of “through design.” We propose Research Through Co-design (RTC) as a new application of Control System Theory (CST) that includes a research problem assigned to a co-design process in RTD. It embeds the participatory paradigm through collaborative design practice and makes the research a collaborative process for learning from all the participants. To sustain the RTC theory, we present a cognitive model of RTC. It is a “model for” – rather than a “model of” – describing how the co-design, as a neural network process, works through its nodes’ collaboration to find co-designed solutions and the research answer. Diversity increases as non-experts and non-designers with different backgrounds participate. This is valuable for the RTC learning system. The discussions highlight the possibility of considering (i) the RTC model as useful for describing a robust RTD process through CST; (ii) RTC as a cognitive model for explaining the value of co-design in research processes; and (iii) RTC as a strategy for applying the participative paradigm in formal research. Finally, new insights and implications are highlighted, including using RTC as a predictive tool through artificial intelligence.

Several concepts and types of procedures for assessing novelty and related concepts exist in the literature. Among them, the two approaches originally proposed by Shah and colleagues are often considered by scholars. These metrics rely on well-defined novelty types and a specific concept of novelty; however, more than 20 years after the first publication, it is still not clear whether and to what extent these metrics are actually used, why they are used and how. Through a comprehensive review of the papers citing the main work of Shah, Vargas-Hernandez & Smith (2003a, 2003b) (the main study where the metrics are comprehensively described and applied), the present work aims to bridge this gap. The results highlight that only a few of the citing papers actually use the assessment approach proposed by Shah et al. and that a nonnegligible number uses a modified or adapted version of the original metrics. Furthermore, several criticalities in the application of the metrics have been uncovered, which are expected to provide relevant information for scholars involved in reliable and repeatable novelty assessments.

Idea evaluation is used to identify and select ideas for development as future innovations. However, approaching idea evaluation as a decision gate can limit the role of the person evaluating ideas, create fixation bias, and underutilise the person’s creative potential. Although studies show that during evaluation experts are able to engage in design activities, it is still not clear how they design and develop ideas. The aim of this study was to understand how experts develop ideas during evaluation. Using the think-aloud technique, we identify different ways in which experts develop ideas. Specifically, we show how experts transform initial idea concepts using iterative steps of elaboration and transformation of different idea components. Then, relying on concept-knowledge theory (C-K theory), we identify six types of reasoning that the experts use during idea evaluation. This helps us to distinguish between three different roles that experts can move between during evaluation: gatekeeper, designer managing fixation, and designer managing defixation. These findings suggest that there is value in viewing idea evaluation as a design process because it allows us to identify and leverage the experts’ knowledge and creativity to a fuller extent.

Traditional aerospace design methods offer quick and efficient ways to generate new designs, but such that often resemble previous ones. For truly innovative design, however, a different approach is needed. This paper suggests that a general conceptual design method called ‘parameter analysis’ (PA) may be used for teaching and practicing innovative aerospace design. To support this proposition, we investigate four diverse, innovative and unique case studies, all carried out by very experienced aerospace designers: the ‘dam busting’ bouncing bomb of World War II, the Gossamer Condor human-powered plane of the 1970s, the asymmetric Boomerang twin-engine plane of the 1990s and the SpaceShipOne suborbital spacecraft of the early 2000s. The paper elaborates on how the methodology of case-study research has been adapted and applied to provide the evidence supporting the research hypothesis, and presents the results of analyzing the case studies. It shows that the expert aerospace designers followed a thought process similar to PA, even if unknowingly, where the similarity was measured by counting the number of PA characteristics that could be shown to exist in the case studies. Advantages and limitations of the research methodology are also discussed.

Much of the literature on biologically inspired design makes two, often unstated and largely unexamined, assumptions: (i) The process of biologically inspired design is independent of the biological domain, and (ii) the design process leads to multifunctional designs. In this paper, we perform a meta-analysis of 74 case studies of biologically inspired design in the Design Study Library. We begin by noting that biologically inspired design has two core processes: problem-driven design and solution-based design. We find that the first assumption about the domain independence of these design processes is questionable. Our analysis indicates that the problem-driven process of biologically inspired design is more prevalent in some domains, whereas the solution-based design process is more common in other domains. Our analysis also indicates that the solution-based process leads to multifunctional designs more often than the problem-driven process. These findings may have useful implications not only for building information-processing theories of biologically inspired design, but also for developing pedagogical techniques for teaching about the paradigm and computational tools for supporting its practice.

Sustainability considerations are traditionally difficult to trade-off with technical and business requirements in an early design phase. Hence, design teams need support to reflect early on in the process, on how sustainability may affect profitability and customer value fulfilment in the long term. The commoditisation of modelling and simulation techniques points to gamification and serious gaming as emerging approaches to raise awareness among the design team – as well as users and stakeholders – of the expected behaviour of a solution along its life cycle. The objective of this paper is to explore how serious games can be used to inform decision-makers about the value versus cost implications of being (or not being) ‘sustainability compliant’ when designing products and systems. The paper initially presents the findings from a descriptive study focused on the definition of ‘design support’ intended to raise sustainability awareness through serious gaming. It further describes the development, application and testing of one of such games for material selection in the aerospace industry.

Open Innovation (OI) supports companies in systematically collaborating with external partners, offering various advantages. However, companies still face several challenges when applying OI, e.g., identifying relevant OI partners, collaboration methods, and project risks. Often, insufficient planning is the reason for subsequent deficits in OI projects. The analysis of relevant context factors (‘situation’) is important, which affect and constrain OI. To date, a general approach for analyzing (open) innovation situations or guidelines for developing one do not exist. Usually researchers develop their own situation analysis, including extensive literature reviews and experiencing similar challenges. This publication sets the basis for successfully planning OI projects. It focuses on developing an analysis approach for OI situations and supports other researchers in developing their own analysis approaches. The resultant objectives of the publication are to: (1) provide a list of potential situation analysis criteria; (2) provide a guideline for developing a situation analysis; (3) provide initial indications of relevant OI-specific situation criteria. The criteria were derived from the literature and qualitatively evaluated by three industry partners to assess their usability. Although this work is exploratory, and the results are not automatically generalizable, it is an important contribution for ensuring the success of OI, and for analyzing enablers and barriers to knowledge transfer from academia to industry.

Although nanoparticles have been shown to have clear technological advantages, their use in some consumer products remains controversial, particularly where these products come in direct contact with our bodies. There has been much discussion about using metal oxide nanoparticles in sunscreens, and numerous technology assessments aimed at predicting the type, size and concentration of nanoparticles and surface treatments that will be best for consumers. Yet, the optimal configuration is ultimately the one that people actually want and are willing to pay for, but until now consumer preferences have not been included in model predictions. We describe and discuss a proof of concept study in which we design and implement a hypothetical sunscreen product configurator to predict how people tradeoff sun protection factor (SPF), product transparency and potential toxicity from reactive oxygen species (ROS) in configuring their most preferred sunscreen. We also show that preferred nanoparticle sizes and concentrations vary across demographic groups. Our results suggest that while consumers choose to reduce or eliminate potential toxicity when possible, they do not automatically sacrifice high SPF and product transparency to avoid the possibility of toxicity from ROS. We discuss some advantages of using product configurators to study potential product designs and suggest some future research possibilities.

User experience (UX) application in the practice of engineering and product design is still limited. The present paper provides insights into research on UX design and recommendations for design practitioners by pointing out common criticalities. These outcomes are achieved through a literature review on how UX relates to design. First, issues in benefitting from UX understanding in design are identified with a specific focus on theoretical contributions. Second, experimental papers investigating UX and design are analysed in relation to previously identified issues. Although issues are present to some extent in all the contributions, the empirical studies dealing with UX in design are overall valid. The results highlight UX’s support in revealing design requirements, but its capability of steering design processes is arguable, as concrete guidelines for practitioners are not well described. Based on identified issues, the authors propose a checklist to make UX studies in design more reliable and their outcomes more comparable.

Electric vehicles (EVs) are very quiet at low speed, which can be hazardous for pedestrians, especially visually impaired people. It is now mandatory (since mid-2019 in Europe) to add external warning sounds, but poor sound design can lead to noise pollution, and consequently annoyance. Moreover, it is possible that EVs are not sufficiently detectable in urban areas because of the masking effect from the background noise. In this paper, we propose a method for the design of warning sounds that takes into account both detectability and unpleasantness. The method implements a multiobjective interactive genetic algorithm (IGA) for the optimisation of the characteristics of synthesised sounds. An experiment is proposed to a first panel of participants in order to define a set of Pareto efficient sounds. At the individual level, sounds obtained with the IGA are compared to different sound design proposals. Results show that the quality of the sounds designed by the IGA method is comparable to those provided by a sound designer. From the sounds of the Pareto set, a design recommendation method based on the probability distributions of the sounds’ characteristics is proposed. An external validation with a second panel of participants shows that these recommended sounds constitute relevant trade-offs when compared to other design proposals.

‘Openness’ is one of the key concepts brought forward by postindustrial narratives questioning the modern repartition of roles between industries and customers. In these narratives, citizen participation in design and intellectual property management based on open source principles are the promise of more sustainable production models. In this context, openness in product design and development has been the object of growing interest and experimentation from academia, businesses and grassroots communities. As a result, numerous concepts emerged that attempt to grasp the essence of this phenomenon, unfortunately leading to overlapping, conflicting or speculative depictions. In this article, we share the understanding we gained throughout 6 years of research on Open Design and Open Source Hardware and attempt to make the difference between myths and facts. We depict an enthusiastic but realistic picture of Open Design and Open Source Hardware practices as we could observe them and deliver a structured framework to situate concepts and their differences. From this, we share seven observations leading to seven corresponding research questions and establish a research agenda to stimulate further investigations into this socially relevant and potentially ground-breaking phenomenon.

The uncertainties and variation of additive manufacturing (AM) material properties and their impact on product quality trouble designers. The lack of experience in AM technologies renders the experts’ assessment of AM components and the establishment of safety margins difficult. Consequently, unexpected qualification difficulties resulting in expensive and lengthy redesign processes might arise. To reduce the risk of qualification failure, engineers might perform copious time-consuming and expensive specimen testing in early phases, or establish overconservative design margins, overriding the weight reduction benefits of AM technologies. In this article, a model-based design method is proposed for the conceptual design of AM space components with affordable test phases. The method utilizes fuzzy logics to systematically account for experts’ assessment of AM properties variation, and to provide an early estimation of a product qualification likelihood related to design parameters of interest, without the need for copious testing. The estimation of qualification likelihood can also point out which are the unique AM material uncertainties that require further specific testing, to enable the design of a product with a better performance and more affordable test phases. The method is demonstrated with the design for AM gridded of ion thrusters for satellite applications.

Consumers’ choice of services and the product platforms that deliver them, such as apps and mobile devices, or eBooks and eReaders, are becoming inextricably interrelated. Market viability demands that product–service combinations be compatible across multiple producers and service channels, and that the producers’ profitability must include both service and product design. Some services may be delivered contractually or physically, through a wider range of products than others. Thus, optimization of producers’ contingent products, services, and channel decisions becomes a combined decision problem. This article examines three common product–service design scenarios: exclusive, non-exclusive asymmetric, and non-exclusive symmetric. An enterprise-wide decision framework has been proposed to optimize integrated services and products for each scenario. Optimization results provide guidelines for strategies that are mutually profitable for partner–competitor firms. The article examines an example of an eBook service and tablet, with market-level information from four firms (Amazon, Apple, Barnes & Noble, and Google) and conjoint-based product–service choice data to illustrate the proposed framework using a scalable sequential optimization algorithm. The results suggest that firms in market equilibrium can markedly differ in the services they seek to provide via other firms’ products and demonstrate the interrelationship among marketing, services, and product design.