This article explores a new approach to anticipate the social impacts of disruptive products, using autonomous vehicles (AVs) as a case study. It highlights the limitations of current methods in predicting the social effects of new products and proposes that futures studies and strategic foresight can provide better techniques. The main hypothesis is that experts in social sciences can anticipate long-term social impacts by considering contextualized future product usages. The authors propose a new model called Representation–Usage–Impact (RUI), which combines expert knowledge from sociology and other fields. The article presents a detailed structure for the model and describes how experts can contribute their knowledge. Sessions were organized with experts to link AV usages with potential social impacts. The results demonstrate that social science experts can identify a wide range of potential long-term social impacts. The article suggests that the RUI model should be integrated and tested into design and decision-making tools to enhance the understanding of product impacts in practical contexts.

Early robust design (RD) can lead to significant cost savings in the later stages of product development. In order to design systems that are insensitive to various sources of deviation in the early stages, specific design knowledge (SDK) plays a crucial role. Different design situations result in higher or lower levels of derivable SDK, which leads to different activities to achieve the development goal. Due to the variety of design situations, it is difficult for design engineers to choose a more robust concept to avoid the costly iterations that occur in the later development stages. Existing RD methods often do not adequately support these differences in design situations. To address the problem, this paper outlines an adaptive modeling method using the Embodiment Function Relation and Tolerance model. The method is developed in two contrasting design situations, each with a high and low level of derivable SDK, and evaluated in another two corresponding case studies. It has a consistent structure with five stages and gates. At each stage, the derivable SDK is taken into account and the individual modeling steps are adapted. This method provides design engineers with concrete support for early robustness evaluation of a product concept in different development scenarios.

Social impact has been widely discussed by the engineering community, but studies show that there is currently little systematic consideration of the social impact of products in both academia and in industry beyond social impacts on health and safety. While Failure Mode and Effect Analysis (FMEA) is useful for evaluating health and safety risks, new developments are needed to create an FMEA-style evaluation that can be applied to a wide range of social impacts for engineered products. The authors describe necessary modifications to traditional FMEA that transform it into a tool for social impact analysis. The modification of FMEA involves the introduction of positive and negative impacts, the inclusion of discrete and continuous impacts, the consideration of various stakeholder types, and the inclusion of uncertainty in place of detectability. This modified FMEA is referred to in this paper as Social Impact Effects Analysis (SIEA). The paper describes how SIEA is performed and articulates the potential benefits of SIEA.

The radical innovation design (RID) comparator is an unprecedented method for design comparison. It overcomes the limitations of traditional methods with a nuanced, structured approach that emphasizes detailed analysis over simple grading. At its core, the RID comparator employs a novel ontology based on the RID building blocks, enabling a precise alignment of activities and solutions. This alignment is deepened through the innovative “quantities of pain” metric, a tool that allows for a refined evaluation and comparison of solutions, facilitating the calculation of effectiveness indicators in a data-driven manner. The true impact of the method is demonstrated through an industrial use case on solutions for cleaning solar panels. The RID comparator demonstrates its practical efficacy in addressing complex, multifactorial design challenges, by constructing a cognitive model of the cleaning activity not only encapsulating the myriad aspects of the design problem but also generating a wealth of discussion and consensus-building among stakeholders. The resultant cognitive model serves as a pivotal tool in redefining the process of generating innovation briefs, deeply rooted in the actual needs and constraints of real-world scenarios. In essence, the RID comparator method significantly enhances the efficiency and quality of innovation processes, particularly in complex industrial contexts.

Our emotions do not always surface into our awareness, making it difficult to manage them and communicate them to others. Even when emotions do not reach our awareness, they still express themselves as physiological changes, often unperceived by ourselves and others. To aid in emotion self-regulation and increase the bandwidth of emotion communication, I designed a programmable affective sleeve that translates physiological aspects of emotions into material haptic action. The affective sleeve has been developed as a case study for Affective Matter. Affective Matter suggests a method for human-material interaction that enhances health and wellbeing.

I first discuss the three foundations of Affective Matter underlying the design of the affective sleeve: Embodiment, Entrainment, and Material Intelligence. I then proceed to the methods and results of an exploratory study I developed and conducted that tests the psychophysiological impact of the sleeve on 36 participants. The study results suggest that the pace of the affective sleeve’s haptic action can be programmed to regulate the wearer’s breathing pace to either have a calming or a stimulating impact on the wearer. The results also show varied affective responses to distinct haptic stimuli. Discussion of the results suggests future research directions and therapeutic applications for the benefit of individuals with mental health and neurodevelopmental disorders.

Society’s most well-intended efforts to solve sustainability challenges have not yet achieved the expected gains due to rebound effects (i.e., negative consequences of interventions arising from induced changes in system behaviour). Rebound effects offset about 40% of potential sustainability gains, but the understanding of design as a key leverage point for preventing rebound effects is still untapped. In this position paper, three fundamental scientific gaps hampering the prevention of rebound effects are discussed: (1) limited knowledge about the rebound effects triggered by efficiency–effectiveness–sufficiency strategies; (2) the influence of the counterintuitive behaviour of complex socio-technical systems in giving rise to rebound effects is not yet understood and (3) the bounded rationality within design limits the understanding of rebound effects at a broader systemic level. To address the aforementioned gaps, novel methodologies, simulation models and strategies to enable the design of reboundless interventions (i.e., products, product/service-systems and socio-technical systems that are resilient to rebound effects) are required. Building on the strong foundation of systems and design theory, this position paper argues for the need to bridge the interdisciplinary gap in the interplay of design and rebound effects, qualitative and quantitative models, engineering and social sciences, and theory and practice.

Product architecture decisions are made early in the product development process and have far-reaching effects. Unless anticipated through experience or intuition, many of these effects may not be apparent until much later in the development process, making changes to the architecture costly in time, effort and resources. Many researchers through the years have studied various elements of product architecture and their effects. By using a repeatable process for aggregating statements on the effects of architecture strategies from a selection of the literature on the topic and storing them in a systematic database, this information can then be recalled and presented in the form of a Product Architecture Strategy and Effect (PASE) matrix. PASE matrices allow for the identification, comparison, evaluation, and then selection of the most desirable product architecture strategies before expending resources along a specific development path. This paper introduces the PASE Database and matrix and describes their construction and use in guiding design decisions. This paper also provides metrics for understanding the robustness of this database.

Self-instructional media in education has the potential to address educational challenges such as accessibility, flexible and personalised learning, real-time assessment and resource efficiency. The objectives of this study are to (1) develop programmed instructions to teach design thinking concepts and (2) investigate its effects on secondary school students’ understanding of these concepts. A design thinking workshop was conducted with secondary school students; subsequently, their understanding of design thinking concepts gained through digital programmed instructions was evaluated. The study involved 33 novice secondary school students from grades 6 to 9 in India, who worked in teams to find and solve real-life, open-ended, complex problems during the workshop using the design thinking process. Data on (i) the individual performance in understanding design thinking concepts and (ii) team performance in design problem finding and solving were collected using individual tests and teams’ outcome evaluations, respectively. Students’ perceptions of the effectiveness of the programmed instructions for supporting understanding of the concepts were also captured. Results show the positive effects on students’ understanding of design thinking concepts as well as on their problem-finding and solving skills. The results justify the use of programmed instructions in secondary school curricula to advance design thinking concepts. The current version of programmed instruction has limitations, including the absence of branching mechanisms, a detailed feedback system, multimodal content and backend functionalities. Future work will aim to address these issues and overcome these shortcomings.

Loneliness and social isolation are prevalent concerns among older adults and can lead to negative health consequences and a reduced lifespan. New technologies are increasingly being developed to help address loneliness and social isolation in older adults, including monitoring systems, social networks, robots, companions, smart televisions, augmented reality (AR) and virtual reality (VR) applications. This systematic review maps human-centered design (HCD) and user-centered design (UCD) approaches, human needs, and contextual factors considered in current technological interventions designed to address the problems of loneliness and social isolation in older adults. We conducted a scoping review and in-depth examination of 98 papers through a qualitative content analysis. We found 12 studies applying either an HCD or UCD approach and observed strengths in continuous user involvement and implementation in field studies but limitations in participant inclusion criteria and methodological reporting. We also observed the consideration of important human needs and contextual factors. However, more research is needed on stakeholder perspectives, the functioning of applications in different housing environments, as well as studies that include diverse socio-economic groups.

Evaluation approaches are needed to ensure the development of effective design support. These approaches help developers ensure that their design support possesses the general design support characteristics necessary to enable designers to achieve their desired outcomes. Consequently, evaluating design support based on these characteristics ensures that the design support fulfils its intended purpose.

This work reviews design support definitions and identifies and describes 11 design support characteristics. The characteristics are applied to evaluate a proposed design support that uses additive manufacturing (AM) design artefacts (AMDAs) to explore design uncertainties. Product-specific design artefacts were designed and tested to investigate buildability limits and the relationship between surface roughness and fatigue performance of a design feature in a space industry component. The AMDA approach aided the investigation of design uncertainties, identified design solution constraints, and uncovered previously unknown uncertainties. However, the results provided by product-specific artefacts depend on how well the user frames their problem and understands their AM process and product. Hence, iterations can be required. Based on the evaluation of the AMDA process, setting test evaluation criteria is recommended, and the AMDA method is proposed.

Project-based learning (PBL) has gained widespread acceptance as a cutting-edge teaching approach in universities, particularly for imparting engineering design skills. PBL allows students to showcase their design skills and put into practice the theoretical concepts acquired through instruction. Throughout the various phases of the design process and project execution, students prepare design artifacts, which serve as tangible indicators of their design skills – an essential competency for engineers. The objective of this research is to evaluate and compare the application of engineering design skills among first-year and third-year engineering students as evidenced by their design artifacts. This comparative analysis aims to pinpoint areas of strength and opportunities for growth, thereby offering a holistic view of student development in design proficiency throughout their undergraduate education. Employing a standardized rubric to evaluate these artifacts allows for an unbiased assessment of the students’ design process acumen. The findings offer insights into the design skill proficiency of two student groups at different points in the design process. It is imperative for engineering educators to strategically highlight every aspect of the design process within PBL, ensuring the comprehensive development of design competencies.

Incorporating contextual factors into engineering design processes is recommended to develop solutions that function appropriately in their intended use contexts. In global health settings, failing to tailor solutions to their broader context has led to many product failures. Since prior work has thus far not investigated the use of contextual factors in global health design practice, we conducted semi-structured interviews with 15 experienced global health design practitioners. Our analysis identified 351 instances of participants incorporating contextual factors in their previous design experiences, which we categorized into a taxonomy of contextual factors, including 9 primary and 32 secondary classifications. We summarized and synthesized key patterns within all the identified contextual factor categories. Next, this study presents a descriptive model for incorporating contextual factors developed from our findings, which identifies that participants actively sought contextual information and made conscious decisions to adjust their solutions, target markets and implementation plans to accommodate contextual factors iteratively throughout their design processes. Our findings highlight how participants sometimes conducted formal evaluations while other times they relied on their own experience, the experience of a team member or other stakeholder engagement strategies. The research findings can ultimately inform design practice and engineering pedagogy for global health applications.

Product engineering in general and advanced systems engineering in specific are highly complex and unique processes that strive to deliver innovations – successful new products. To reduce risk and time, product engineers refer to existing (socio-)technical systems or subsystems. These references are part of the reference system. A great variety of elements can be used as reference system elements in engineering projects, but the different types of reference system elements and their roles are not yet characterized. However, this is a necessary prerequisite to model and conduct product generation engineering effectively. Here, we show how reference system elements can be categorized into three types that differ regarding their intended application in the actual engineering project. Therefore, we introduce three subsystems: reference system of objectives, reference operation system, and reference system of objects. Furthermore, we provide definitions for all subsystems to specify the allocation. We believe these results will form the basis for a continuous description and continuous engineering of consecutive and parallel product generations based on model-based systems engineering. Furthermore, the results will be the starting point for the development of design supports to assist engineers in designing their specific reference systems and to make the reference system part of efficient engineering processes.

Universities face a critical crossroads, in need of swift, targeted, and efficient actions to address future challenges. This necessities a strategic approach to updating and assessing engineering design education. Efforts to improve teaching and learning require systematic change in many universities, yet research on structuring such change is scarce. Few studies have combined a systems perspective with a functional operational level. This research embeds design thinking to structure to isolated actions. Drawing from an extensive literature review of educational change frameworks and several illustrative cases, this article demonstrates the potential of design-driven change. It highlights how dynamic interrelations can facilitate educational transformations across diverse academic levels. By presenting an educational ecosystem as a framework for systematic educational change, design thinking functions as a catalyst for educational transformation. The article also presents case findings that strengthen supportive actions ingrained in existing change research frameworks connecting, them to a transparent approach for sustainable and careful decision-making.

Testing prototypes with users is essential when developing new products. This qualitative study examines and organizes users’ (children) feedback on physical toy prototypes at various fidelity levels; the data collected comes from a multidisciplinary design studio class tasked with developing wooden toys for the company PlanToys. In this research, we use an organizational framework to categorize stakeholders’ feedback, which includes affirmative feedback, convergent critical feedback, and divergent critical feedback. In our analysis, the children’s feedback was compared by prototype fidelity in terms of both form and function, as well as by the feedback categorization. Findings suggest that form fidelity may bias children toward giving more divergent feedback, that function fidelity may have little impact on feedback given, that children tend to give more types of feedback on lower fidelity than higher fidelity models, and that play value, form, interaction, and function were the highest reported categories of feedback. Based on our observations, we encourage toy designers to be aware of their goals for testing with children before beginning to prototype. This paper is a resource for designers to understand how to prototype for children, as well as resource for researchers studying how specific end users influence the product design process.

Evaluating the algorithmic behavior of interactive systems is complex and time-consuming. Developers increasingly recognize the importance of accountability for their algorithmic creations’ unanticipated behavior and resulting implications. To mitigate this phenomenon, developers not only need to concentrate on the observable inaccuracies that can be measured quantitatively but also the more subjective outcomes that can perpetuate social bias, which are challenging to identify. We require a new approach that involves humans in scrutinizing algorithmic behavior. It leverages a combination of quantitative and qualitative methods to support an ethical, value-aligned design and a system’s lifecycle, informed by users’ perception and values. To date, the literature lacks an agreed-upon framework for such an approach. Consequently, we propose an oversight framework, Modular Oversight Methodology (MOM), which aids developers in assessing the behavior of their systems by involving a carefully crowdsourced society-in-the-loop. The framework facilitates the development and execution of an oversight process and can be tweaked according to the domain and application of use. Through such an oversight process, developers can assess the human perception of the algorithmic behavior under inspection, and extract valuable insights that will aid in assessing its implications. We present the MOM framework, as a first step toward tailoring more robust, domain-specific solutions to exercise human oversight over algorithms, as a means for software developers to keep the generated output of their solutions fair and trustworthy.

The reorientation to remote teaching due to the impact of COVID-19 restrictions proved to be both challenging and compromising, particularly in the context of delivering practice-based design education. Central to the challenges faced by many design tutors was the loss of the design studio as a focal point for engagement and learning. However, delivering teaching remotely through a period of enforced separation also proved that through adversity comes new insights, with the accelerated use of emergent technologies to support distributed working revealing new behaviours and opportunities for learning to take place. In response to COVID-19 restrictions, Miro, the digital whiteboard platform was widely adopted within the UK creative industries and universities alike to facilitate remote engagement. Following a return to campus-based delivery through the Autumn/Fall of 2021, it became evident that some of the pragmatic approaches adopted through necessity had the potential to hold lasting value beyond crisis modes of teaching. This position paper presents a series of reflective studies gathered over three academic years with the aim of (1) understanding the impacts of remote learning as experienced by design students (2) establish clear benefits for the application of online platforms within a blended campus-based delivery and (3) identify emergent characteristics in students’ navigation of the post-COVID design studio.

By making building instructions freely accessible to everyone, open-source machine tools (OSMTs) promise to democratize manufacturing by enabling users in marginalized settings to build machines tools by themselves. There is, however, a lack of empirical evidence of the replicability of OSMT designs in low-resource contexts. This article explores OSMT replicability through qualitative and empirical methods to answer the central research question: Are designs that are fully open source also globally replicable? A comparative experiment was carried out by replicating an open-source 3D printer in two different locations: in Germany (resource-rich) and in Oman (resource-poor). The experiment aimed to determine the barriers faced with the replication in each location. It was significantly more challenging to replicate the 3D printer in Oman, primarily due to difficulties in sourcing and manufacturing, necessitating extensive modifications, which demanded greater skills and dexterity from users compared to those in Germany. Qualitative interviews found that limited digital literacy posed a significant barrier for microenterprise owners in replicating OSMT. Finally, design guidelines were proposed to enhance the global replicability of contextualized OSMT designs.

Mixed Reality enables individuals to visualise and interact with artefacts and environments through a combination of physical and virtual assets. It has received increased interest from the design community as a means to accelerate, enrich and enhance prototyping activities. This article concerns MR’s ability to deceive an individual through the combination of virtual and physical assets and their underlying traits (e.g., mass, size), and a user’s cognitive ability to ‘join the dots’. If properly implemented, MR could save time and resources by reducing the required prototype fidelity and the need to fully realise variants. However, there is a gap in understanding how the traits of physical and virtual assets and cognition combine to form reality. This article presents a study investigated the role mass, virtual and physical model size played on users perception of an MR prototype. The relative impact of these factors was determined by varying these parameters and assessing the user’s perceived change. The key finding from this study was that the virtual model size had a far greater influence on prototype perceived by the user. This suggests that the required physical fidelity of an MR prototype can be lower than the virtual. Furthermore, exploring size design variants can be achieved exclusively through changes to the virtual model.

First-of-a-kind engineered systems often burst with complexity – a major cause of project budget and time overruns. Our particular concern is the structural complexity of nuclear fusion devices, which is determined by the amount and entanglement of components. We seek to understand how this complexity rises during the development phase and how to manage it. This paper formulates a theory around the interplay between a problem-solving design process and an evolving design model. The design process introduces new elements that solve problems but also increase the quantifiable complexity of the model. Those elements may lead to new problems, extending the design process. We capture these causal effects in a hierarchy of problems and introduce two metrics of the impact of design decisions on complexity. By combining and incorporating the Function-Behavior-Structure (FBS) paradigm, we create a new problem-solving method. This method frames formulation, synthesis and analysis activities as transitions from problems to solutions. We demonstrate our method for a nuclear fusion measurement system. Exploring different design trajectories leads to alternative design models with varying degrees of complexity. Furthermore, we visualize the time-evolution of complexity during the design process. Analysis of individual design decisions emphasizes the high impact of early design decisions on the final system complexity.