Mass collaboration efforts can increase innovation and design possibilities. Incorporation of open innovation into the product development process allows for a vast array of unique perspectives and ideas. However, with the broad expansion of design possibilities, coordination of these development processes is paramount. To best make use of open innovation in product development, increased organizational efforts must be considered. The mass collaboration of individuals must account for individual intellectual abilities (competencies), working experience and even personality traits or idiosyncrasies. Approaches to this problem require the fusion of social network analysis with quantifiable design impacts. This work proposes a simulation framework that evaluates the design potential of a project team based on individual attributes and the team network structure. The overall contribution of this work comes from the exploration of team structure, focusing on network composition metrics such as centrality and network density, while attempting to understand the role of individual ability and positioning on the success of the design process. This work aims to garner a more thorough understanding of how the network structure of design teams correlates with their potential performance through a generalized simulation framework, applicable to future crowd and design initiatives.

Prototyping constitutes a major theme of design education and an integral part of engineering design academic courses. Physical prototypes and the model building process, in particular, have been proved to boost students’ creativity and resourcefulness and assist in the better evaluation of concepts. However, students’ usage of prototypes has still not been explored in depth with the aim of being transformed into educational guidelines. This paper presents an investigation of students’ reasoning behind prototyping activities based on the concept of Purposeful Prototyping, developed in the authors’ previous work. This is performed by identifying instances of prototype use in students’ design projects and by discovering which types of prototyping purposes they apply and to what extent, as well as by studying the relationships between purposes, early design stages, academic performance and project planning. The analysis of the results shows that prototyping can support students’ learning objectives by acting as a project scheduling tool and highlights the contribution of early-stage prototyping in academic performance. It is also confirmed that students’ limited prototyping scope prevents them from gaining prototyping’s maximum benefits and that they require strategic guidelines tailored to their needs. A new, improved list of prototyping purposes is proposed based on the study’s results.

The use of metal Additive Manufacturing (AM) has increased in recent years with potential benefits for novel design solutions and efficient manufacturing. In order to utilise these potentials, engineers need to address uncertainties related to product design and the AM process. This paper presents a design process utilising product-specific AM Design Artefacts (AMDAs) to assess uncertainties identified during design. The process emphasises the importance of concurrently developing the product and AM knowledge. Based on a research collaboration with industry, three case studies describe the use of this process in the development of products for AM. In total, six different types of AMDAs show how AM-related uncertainties are resolved to provide confidence in design solutions and manufacturability. The contributions of this paper are: (i) a design process where AMDAs are used as support in evolving and defining an AM design specification, (ii) an example of how Design for AM (DfAM) is practiced in industry and of typical AM uncertainties that are encountered and addressed, and (iii) an example of how collaborative research can facilitate new knowledge for both industry and academia. The practical implication is a DfAM process for engineers to use and adapt according to existing AM knowledge.

Design fixation refers to blind adherence to a set of ideas, which can limit the output of conceptual design. Engineering designers tend to fixate on features of pre-existing solutions and consequently generate designs with similar features. The objective of this study is to leverage functional magnetic resonance imaging (fMRI) to study the brain activity of engineering designers during conceptual design in order to understand whether/where design fixation can be detected in a person’s brain when solving design problems. Design solutions indicated that fixation effects were detectable at a statistically significant level. fMRI results show increased activation in areas associated with visuospatial processing when comparing ideation activities using an Example solution to No Example solution. Activation was found in the right inferior temporal gyrus, left middle occipital gyrus, and right superior parietal lobule regions. The left lingual and superior frontal gyri were found to be less active in the example condition; these gyri are close in proximity to the prefrontal cortex, associated with creative output. The spatial patterns of activation provide evidence that a shift in mental resources can occur when a designer becomes fixated. For designers, the timing of ideation relative to the timing of benchmarking existing solutions should be considered.

This paper proposes a task-related electroencephalogram research framework (tEEG framework) to guide scholars’ research on EEG-based cognitive and affective studies in the context of design. The proposed tEEG framework aims to investigate design activities with loosely controlled experiments and decompose a complex design process into multiple primitive cognitive activities, corresponding to which different research hypotheses on basic design activities can be effectively formulated and tested. Thereafter, existing EEG techniques and methods can be applied to analyse EEG signals related to design. Three application examples are presented at the end of this paper to demonstrate how the proposed framework can be applied to analyse design activities. The tEEG framework is presented to guide EEG-based cognitive and affective studies in the context of design. Existing methods and models are summarized, for the effective application of the tEEG framework, from the current literature spread in a wide spectrum of resources and fields.

Pahl and Beitz’ ‘Systematic Approach’ is generally seen as a prescriptive model of designing based on observations of professional design practice. In this paper, we examine whether this model can be used as a predictive model. This is done by testing its predictive capacity for the design behaviour of students that are formally taught design and design methods. The behavioural observations used in this study are based on protocols of 15 design sessions involving mechanical engineering students after their first year of design education and 31 design sessions of the students using various concept generation methods. The design protocols and the Systematic Approach are coded uniformly using the Function–Behaviour–Structure (FBS) design issue schema. Cumulative occurrence analysis is used to derive qualitative and quantitative measures as a basis for comparison between the Systematic Approach’s prediction and the students’ design behaviour. The results indicate that the Systematic Approach can predict some but not all of students’ design issue behaviour.

Outside of community-led design projects, most participatory design processes initiated by a company or organisation maintain or even strengthen power imbalances between the design organisation and the community on whose purported behalf they are designing, further increasing the absencing experience. Radical participatory design (RPD) is a radically relational answer to the coloniality inherent in participatory design where the community members’ disappointment is greater due to the greater expectations and presencing potential of a ‘participatory design’ process. We introduce the term RPD to show how research and design processes can be truly participatory to the root or core. Instead of treating participatory design as a method, a way of conducting a method, or a methodology, we introduce RPD as a meta-methodology, a way of doing any methodology. We explicitly describe what participation means and compare and contrast design processes based on the amount of participation, creating a typology of participation. We introduce ‘designer as community member’, ‘community member as designer,’ and ‘community member as facilitator’ models and provide characteristics for the meta-methodology of RPD.

This paper builds on the author’s keynote address to the Design Society’s 21st International Conference on Engineering Design in 2017 and in doing so provides a personal perspective to the question of the title. It begins by describing the engineering experience of the author which led to an understanding of the importance of taking a systems approach to the development of engineering products and services. This is followed by reflections on the development of a research portfolio focused on the design of complex engineering systems, inclusive design and healthcare improvement. The paper then reports on the recent work of engineers, clinicians and healthcare leaders, who came together under the guidance of the author, to explore how an engineering systems approach could be described that might simultaneously meet the needs of patients, carers and healthcare staff. It discusses the challenges associated with the translation of this narrative description of a systems approach (What?) into a practical implementation guide or toolkit (How?), supported by evidence of its effective use in health and care improvement practice. Finally, the paper reflects on the lessons to be learned from this process and their possible repercussions for design research and the practice of design.

Computational modeling of the human sequential design process and successful prediction of future design decisions are fundamental to design knowledge extraction, transfer, and the development of artificial design agents. However, it is often difficult to obtain designer-related attributes (static data) in design practices, and the research based on combining static and dynamic data (design action sequences) in engineering design is still underexplored. This paper presents an approach that combines both static and dynamic data for human design decision prediction using two different methods. The first method directly combines the sequential design actions with static data in a recurrent neural network (RNN) model, while the second method integrates a feed-forward neural network that handles static data separately, yet in parallel with RNN. This study contributes to the field from three aspects: (a) we developed a method of utilizing designers’ cluster information as a surrogate static feature to combine with a design action sequence in order to tackle the challenge of obtaining designer-related attributes; (b) we devised a method that integrates the function–behavior–structure design process model with the one-hot vectorization in RNN to transform design action data to design process stages where the insights into design thinking can be drawn; (c) to the best of our knowledge, it is the first time that two methods of combining static and dynamic data in RNN are compared, which provides new knowledge about the utility of different combination methods in studying sequential design decisions. The approach is demonstrated in two case studies on solar energy system design. The results indicate that with appropriate kernel models, the RNN with both static and dynamic data outperforms traditional models that only rely on design action sequences, thereby better supporting design research where static features, such as human characteristics, often play an important role.

Within the last few years, a need for renewed product personalisation has been observed in some markets such as consumer electronics, fashion to meet the exact demands of the customers. Product customisation emphasises the fulfilment of explicit requirements of a defined market segment, but product individualisation targets at satisfying the particular needs of a customer. Mass Individualisation (MI) is a new product design approach comprising of an open hardware platform and multiple modules to be integrated with the platform. It gives freedom to end-users to integrate different modules into the platform as per their choice. Technological and strategic integration of all actors involved in the design process is the primary focus of this research. This paper identifies key areas which need to be focussed on to realise this approach and convert it into an industrial practice by an explorative study of existing product design and customisation approaches. An industrial survey was conducted, and results for the industrial implication and insights on this approach are presented. The findings show that the end product from product design for MI will be more creative and innovative by the networking of all actors, and offers more individualised and technologically advanced products.

Prior studies on design ideation have demonstrated the efficacy of using patents as stimuli for concept generation. However, the following questions remain: (a) From which part of the large patent database can designers identify stimuli? (b) What are their implications on ideation outcomes? This research aims to answer these questions through a design experiment of searching and identifying patent stimuli to generate new concepts of spherical rolling robots. We position the identified patent stimuli in the home, near and far fields defined in the network of patent technology classes, according to the network’s community structure and the knowledge proximity of the stimuli to the spherical rolling robot design. Significant findings are: designers are most likely to find patent stimuli in the home field, whereas most patent stimuli are identified in the near field; near-field patents stimulate the most concepts, which exhibit a higher average novelty; combined home- and far-field stimuli are most beneficial for high concept quality. These findings offer insights on designers’ preferences in search for patent stimuli and the influence of stimulation distance on ideation outcomes. The findings will also help guide the development of a computational tool for the search of patents for design inspiration.

The construction of future technological systems in work domains that do not yet exist, known as the envisioned world problem, is an increasingly important topic for designers, particularly given the rapid rate of technological advancement in the modern era. This paper first discusses the theoretical underpinnings of using cognitive work analysis (CWA) for developing a decision support system (DSS) situated within the envisioned world problem and recasts the problem as pathway-dependent processes. Using this pathway-dependent framework, each stage of the envisioning process is described to reveal how human factors experts can link existing work domains to envisioned instances. Finally, a case study example of the envisioning process that incorporates CWA modelling is demonstrated as it pertains to the advancement of the human spaceflight domain. As a result, this paper provides a unified treatment of the envisioned world problem with an end-to-end example of one approach to designing future technologies for future work domains.

Significant challenge exists in the effective monitoring and management of engineering design and development projects. Due to traits such as contextual variation and scale, detailed understanding of engineering projects and activity are difficult to form, with monitoring hence reliant on interpretation of managerial personnel and adherence to defined performance indicators. This paper presents a novel approach to the quantitative monitoring and analysis of engineering activity through computational topic identification and analysis of low-level communication data. Through three metrics of communication activity, this approach enables detailed detection and tracking of activity associated with specific project work areas. By application to 11,832 emails within two industry email corpora, this work identifies four distinct patterns in activity, and derives seven characteristics of communication activity within engineering design and development. Patterns identified are associated with background discussion, focused working, and the appearance of issues, supporting detailed managerial understanding. Characteristics identified relate to through-process norms against which a manager may compare and assess. Such project-specific information extends the ability of managers to understand the activity within their specific project scenario. Through detailed description of activity and its characteristics, in tandem with existing toolsets, a manager may be supported in their interpretation and decision-making processes.

This research presents a pilot study that explores the use of quantified Gestalt principles of symmetry, parallelism, and continuity as design variables to evaluate the aesthetics of three-dimensional product representations. To this end, a virtual reality (VR)-based discrete choice experiment was conducted to elicit subjects’ preferences among pairs of bottle forms with diverse Gestalt values. While immersed in the VR environment, 42 participants were able to visually explore the whole forms, thus capturing more information to develop their judgment. Further analysis of the choice data using standard and mixed logit regression with hierarchical Bayes estimation provides initial details on the aesthetic utility of the Gestalt principles in question, their distribution among the sample participants, and the correlation between estimates. Due to the small sample size, the results are not expansible and they only apply to the data set gathered during the experiment. Nevertheless, it is an initial proof of concept which could suggest that symmetry and continuity have a positive aesthetic effect over people, and that parallelism could have opposite aesthetic utilities for women and men. This methodology allows designers to delve into the integration of aesthetics as a quantifiable property in the product development process.

To better understand the impact of early versus late design decisions, a study was undertaken on the root causes of missed requirements in new product development and their impact on development cost through rework activities. The context is the industrial development of unmanned aerial vehicles. The aim is to understand the occurrence rate of missed requirements, their root causes, and their relative impact. A quantitative approach of counting requirements changes and using engineering documentation enabled traceability from observation back to root cause origin. The development process was partitioned into sequential program segments, to categorize activities to before and after concept and design freeze. We found that there was a significant difference in the rate of design defects arising before and after concept freeze; and found there was a significantly higher number of corrective activities required for design defects arising earlier before concept freeze. The revision rate of concept phase decisions was over 50%, and the rework multiplier if detected late was over 10X. In combination, design decisions made before design freeze accounted for 86% of the total expected program cost, and 34% was determined before concept freeze. These results quantify and support the anecdotal 80–20 impact rule for design decisions.

This study deals with the role of mental models in the coordination of team activities during design problem-solving. The work centers on the sharedness of mental models in a design team setting, mainly on the interaction between an architect and two clients. A major goal is to gain insight into how modifications in mental models affect coordination, and how sharedness develops through the process. Our focus is to explore, through a case study, the individual contributions of the architect and the clients to coordination of the work process, and how sharedness of the development of the team mental model evolves in the early stage of concept generation. Our claim is that work teams develop a certain degree of sharedness of the mental models of individual team members during information exchange. This team mental model can be insufficient or even wrong, but as long as the team members feel agreement in the team, they coordinate their work on that basis. Thus, sharedness of mental models is believed to be a powerful team asset, especially when it is reached in the earlier phases of the design process. Our findings suggest that in order to attain sharedness among design team members, design activities related to the task mental model should be encouraged, specifically the generation of new ideas and the analysis of solutions. Implications for practice and education are suggested.

Bisociative knowledge discovery is an approach that combines elements from two or more ‘incompatible’ domains to generate creative solutions and insight. Inspired by Koestler’s notion of bisociation, in this paper we propose a computational framework for the discovery of new connections between domains to promote creative discovery and inspiration in design. Specifically, we propose using topic models on a large collection of unstructured text ideas from multiple domains to discover creative sources of inspiration. We use these topics to generate a Bisociative Information Network – a graph that captures conceptual similarity between ideas – that helps designers find creative links within that network. Using a dataset of thousands of ideas from OpenIDEO, an online collaborative community, our results show usefulness of representing conceptual bridges through collections of words (topics) in finding cross-domain inspiration. We show that the discovered links between domains, whether presented on their own or via ideas they inspired, are perceived to be more novel and can also be used as creative stimuli for new idea generation.

Travelers interact with a large number and variety of products and services during their journeys. The quality of a travel experience depends on a whole urban mobility system considered in space and time. This paper outlines the relevant concepts to be considered in designing urban mobility. The goal is to provide a language and insights for the early stages of a design process. A literature review sheds light on the complexity of urban mobility from technical, sociotechnical, and user experience perspectives. Observations of experiences in urban areas provide data for describing and understanding travel experience patterns and issues. The paper proposes a conceptual model to describe and analyze different facets of traveler experience and categorizes problems that travelers face when they interact with an urban mobility system. A case study is reported illustrating the use of the conceptual model in identifying travel problems for a demand-responsive transport service.

The terms design and innovation are intuitively related, but the relationship between these two concepts is more complex and subtle than it appears at first sight. Few authors have made rigorous attempts to explore this relationship in depth, and the contributions present in the literature generally suffer the specialist backgrounds on which they are grounded. Consequently, this paper provides a high-level synthesis of the innovation management domain and defines an original framework that allows the positioning of the concepts from Innovation Management that are most relevant for scholars and practitioners operating in the Design domain. Specifically, this framework provides a concise representation of the typologies of innovation activities along the technology lifecycle, and associates them to their business implications and to technical and organizational implications on the design process. This framework allows scholars and practitioners from both fields to identify the typical design challenges that are inherent to each type of innovation activity, and to evaluate the suitability of specific support methods and tools.

This article explores the ability of ChatGPT to function as a virtual colleague in helping to design materials for higher education design students. Using a self-study methodology, two university educators attempted to collaborate with ChatGPT to create course materials targeted at higher education design students, before reflecting on its strengths and weaknesses during the process. Contextualising ChatGPT as the latest acute example of digital disruptors that design practices and processes have faced, the authors evaluated its current and potential threats and opportunities for the creation of design-focused learning content. The authors found that ChatGPT was a competent partner with regard to saving time, structuring textual content and documentation, and as a brainstorming tool. However, ChatGPT’s weaknesses included content generation that was often generic, usually requiring much human prompting, cajoling, and manual editing to produce desirable outcomes. Overall, ChatGPT was found to excel at its stated functionality as a language model, with some potentially useful functionality for the creation of higher education design course materials and outlines, as well as limitations. The reflections discussed can be used to inform design educators who may want to work with ChatGPT when designing course materials. However, acknowledging limitations and potential ethical challenges, the authors’ caution that educators may have to evaluate for themselves whether ChatGPT’s potential advantages outweigh its disadvantages.