Design processes require the joint effort of many people to collaborate and work on multiple activities. Effective techniques to analyse and model design processes are important for understanding organisational dynamics, for improving collaboration, and for planning robust design processes, reducing the risk of rework and delays. Although there has been much progress in modelling and understanding design processes, little is known about the interplay between people and the activities they perform and its influence on design process robustness. To analyse this interplay, we model a large-scale design process of a biomass power plant with $100+$ people and ${\sim}150$ activities as a bipartite network. Observing that some people act as bridges between activities organised to form nearly independent modules, in order to evaluate process fragility, we simulate random failures and targeted attacks to people and activities. We find that our process is more vulnerable to attacks to people rather than activities. These findings show how the allocation of people to activities can obscure an inherent fragility, making the process highly sensitive and dependent on specific people. More generally, we show that the behaviour of robustness is determined by the degree distributions, the heterogeneity of which can be leveraged to improve robustness and resilience to cascading failures. Overall, we show that it is important to carefully plan the assignment of people to activities.

This paper proposes the Uncertainty Driven Action (UDA) model, which unifies the fragmented literature on design activity. The UDA model conceptualises design activity as a process consisting of three core actions: information action, knowledge-sharing action, and representation action, which are linked via uncertainty perception. The foundations of the UDA model in the design literature are elaborated in terms of the three core actions and their links to designer cognition and behaviour, utilising definitions and concepts from Activity Theory. The practical relevance and theoretical contributions of the UDA model are discussed. This paper contributes to the design literature by offering a comprehensive formalisation of design activity of individual designers, which connects cognition and action, to provide a foundation for understanding previously disparate descriptions of design activity.

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.

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.

Automakers are interested in creating optimal car shapes that can visually convey environmental friendliness and safety to customers. This research examined the influence of vehicle form on perceptions based on two subjective inference measures: safety and perceived environmental friendliness (PEF). A within-subjects study was conducted in 2009 (Study 1) to study how people would evaluate 20 different vehicle silhouettes created by designers in industry. Participants were asked to evaluate forms on several scales, including PEF, safety, inspired by nature, familiarity, and overall preference. The same study was repeated in 2016 (Study 2). The results from the first study showed an inverse relationship between PEF and perceptions of safety. That is, vehicles that appeared to be safe were perceived to be less environmentally friendly, and vice versa. Participants in the second study showed a similar trend, but not as strongly as the 2009 participants. Several shape variables were identified to be correlated with participants’ PEF and safety ratings. The changes in the trend of participants’ evaluations over seven years were also discussed. These results can provide designers with insights into how to create car shapes with balanced PEF and safety in the early design stage.

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.

Invention arises from novel combinations of prior technologies. However, prior studies of creativity have suggested that overly novel combinations may be harmful to invention. Apart from the factors of expertise, market, etc., there may be such a thing as ‘too much’ or ‘too little’ novelty that will determine an invention’s future value, but little empirical evidence exists in the literature. Using technical patents as the proxy of inventions, our analysis of 3.9 million patents identifies a clear ‘sweet spot’ in which the mix of novel combinations of prior technologies favors an invention’s eventual success. Specifically, we found that the invention categories with the highest mean values and hit rates have moderate novelty in the center of their combination space and high novelty in the extreme of their combination space. Too much or too little central novelty suppresses the positive contribution of extreme novelty in the invention. Furthermore, the combination of scientific and broader knowledge beyond patentable technologies creates additional value for invention and enlarges the advantage of the novelty sweet spot. These findings may further enable data-driven methods both for assessing invention novelty and for profiling inventors, and may inspire a new strand of data-driven design research and practice.

Technologies are created through the collective efforts of individual inventors. Understanding inventors’ behaviors may thus enable predicting invention, guiding design efforts or improving technology policy. We examined data from 2.8 million inventors’ 3.9 million patents and found that most patents are created by ‘explorers’: inventors who move between different technology domains during their careers. We mapped the space of latent relatedness between technology domains and found explorers were 250 times more likely to enter technology domains that were highly related to the domains of their previous patents, compared to an unrelated domain. The great regularity of inventors’ behavior enabled accurate prediction of individual inventors’ future movements: a model trained on just 5 years of data predicted inventors’ explorations 30 years later with a log-loss below 0.01. Inventors entering their most related domains were associated with patenting up to 40% more in the new domain, but with reduced citations per patent. These findings may be instructive for inventors exploring design directions, and useful for organizations or governments in forecasting or directing technological change.

Among the different phases of complex design processes, early design is the most dynamic and unpredictable stage since it involves a great deal of uncertainty, concurrency of activity streams, collaborative design iterations, and distributed and adaptive decision-making behaviour in response to both organizational commitments and to the occurrence of unforeseen events. This paper argues that current activity-based modelling approaches have limited ability to capture the dynamics of complex early design processes and explores novel modelling approaches. The development of an Agent Model for Planning and rEsearch of eaRly dEsign (AMPERE) aiming to capture various facets of uncertainty, iteration, collaboration and adaptation is described. The model was developed to tackle early design phases of complex systems, with the ability to deal with changes in requirements coming in and affecting the subsequent design evolution while design tasks are on-going. Initial results from agent-based simulations are presented, showing how the agent-based approach can support industrial organizations evaluating likely early design project performance and understanding complex cause–effect relationships that may affect project outcomes. Early design planning support from the agent model is demonstrated through an investigation to the likely project performance for varying levels of externally driven requirements change.

Educational mapping is the process of analyzing an educational system to identify entities, relationships and attributes. This paper proposes a network modeling approach to educational mapping. Current mapping processes in education typically represent data in forms that do not support scalable learning analytics. For example, a curriculum map is usually a table, where relationships among curricular elements are represented implicitly in the rows of the table. The proposed network modeling approach overcomes this limitation through explicit modeling of these relationships in a graph structure, which in turn unlocks the ability to perform scalable analyses on the dataset. The paper presents network models for educational use cases, with concrete examples in curriculum mapping, accreditation mapping and concept mapping. Illustrative examples demonstrate how the formal modeling approach enables visualization and learning analytics. The analysis provides insight into learning pathways, supporting design of adaptive learning systems. It also permits gap analysis of curriculum coverage, supporting student advising, student degree planning and curricular design at scales ranging from an entire institution to an individual course.

In the last few years, numerous approaches have been introduced for supporting design engineers in developing more sustainable products. However, so far, these efforts have not led to the establishment of a commonly acknowledged standard methodology for Sustainable Product Development (SPD). This brings into question the relevance of developing new methods and calls for more efforts in testing the available ones. This article provides a reflection about the benefits and obstacles of applying existing SPD approaches to a real product development project. It reports the results of a project aimed at developing a new mobility solution under the constraints of sustainability-related targets. This project has led to the development of a new pedelec concept, focusing on the substitution of small passenger cars with the help of three SPD methods – Design for Sustainability Guidelines, Product Sustainability Index, and Life Cycle Sustainability Assessment. These methods have proved to be generally beneficial, thanks to a combination of qualitative and quantitative perspectives. However, the multitude of criteria offered by the methods put forth difficulties in evaluating which sustainability aspects are relevant and therefore lead to higher effort for information retrieval analysis and decision processes. Furthermore, the methods still lack an integrated perspective on the product, the corresponding services and the overarching system.

This paper presents a new crowdsourcing approach to the construction of patent clusters, and systematically benchmarks it against previous expert and algorithmic approaches. Patent databases should be rich sources of inspiration which could lead engineering designers to novel solutions for creative problems. However, the sheer volume and complexity of patent information means that this potential is rarely realised. Rather than the keyword driven searches common in commercial systems, designers need tools that help them to understand patents in the context of the problem they are considering. This paper presents an approach to address this problem by using crowd intelligence for effective generation of patent clusters at lower cost and with greater rationale. A systematic study was carried out to compare the crowd’s efficiency with both expert and algorithmic patent clusters, with the results indicating that the crowd was able to create 80% more patent pairs with appropriate rationale.

Serious gaming is the use of games for purposes beyond entertainment. In this paper, we investigate the use of serious gaming as a tool for research into decision-making in engineering systems design. Serious gaming provides a fully controllable environment in which to study the decision-making behavior of engineers in simulated design scenarios. However, given the nature of games and their inherent association with entertainment, it is possible that gaming environments themselves induce unexpected, or unrepresentative behavior. We present two experiments in which we investigate serious gaming as a research tool. Both experiments deal with design decisions in the presence of sunk costs and compare two approaches for communicating the decision-making scenario: (1) an interactive game and (2) a written narrative. The written narrative approach for communicating decision-making scenarios is a widely used and accepted technique for decision-making research. We find that behavior observed in the game variants did not significantly differ from behavior observed in their written narrative equivalents. This result builds confidence for the use of game-based research approaches. However, the results in this paper suggest that response distributions collected from a game have more noise than those from an equivalent written narrative.

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.

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.

Prototyping is interwoven with nearly all product, service, and systems development efforts. A prototype is a pre-production representation of some aspect of a concept or final design. Prototyping often predetermines a large portion of resource deployment in development and influences design project success. This review surveys literature sources in engineering, management, design science, and architecture. The study is focused around design prototyping for early stage design. Insights are synthesized from critical review of the literature: key objectives of prototyping, critical review of major techniques, relationships between techniques, and a strategy matrix to connect objectives to techniques. The review is supported with exemplar prototypes provided from industrial design efforts. Techniques are roughly categorized into those that improve the outcomes of prototyping directly, and those that enable prototyping through lowering of cost and time. Compact descriptions of each technique provide a foundation to compare the potential benefits and drawbacks of each. The review concludes with a summary of key observations, highlighted opportunities in the research, and a vision of the future of prototyping. This review aims to provide a resource for designers as well as set a trajectory for continuing innovation in the scientific research of design prototyping.

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.

This paper reports findings from the first systematic review of protocol studies focusing specifically on conceptual design cognition, aiming to answer the following research question: What is our current understanding of the cognitive processes involved in conceptual design tasks carried out by individual designers? We reviewed 47 studies on architectural design, engineering design and product design engineering. This paper reports 24 cognitive processes investigated in a subset of 33 studies aligning with two viewpoints on the nature of designing: (V1) design as search (10 processes, 41.7%); and (V2) design as exploration (14 processes, 58.3%). Studies on search focused on solution search and problem structuring, involving: long-term memory retrieval; working memory; operators and reasoning processes. Studies on exploration investigated: co-evolutionary design; visual reasoning; cognitive actions; and unexpected discovery and situated requirements invention. Overall, considerable conceptual and terminological differences were observed among the studies. Nonetheless, a common focus on memory, semantic, associative, visual perceptual and mental imagery processes was observed to an extent. We suggest three challenges for future research to advance the field: (i) developing general models/theories; (ii) testing protocol study findings using objective methods conducive to larger samples and (iii) developing a shared ontology of cognitive processes in design.

Archetype in Greek means an original basis that prevails in all later forms. In the field of design, types and archetypes have been used as analytical tools; unfortunately, they have not been perceived as promising prospects in the search for creative ideas, and the dynamic transformative quality embedded in archetypes has not been fully utilized in the ideation process. This research is an exploration of re-establishing the value of implementing archetypes as generative abstractions in the initial phase of the ideation process. The fundamental structure of archetypes was redefined based on the dual structure of a core signal and a peripheral, and an interactive genetic algorithm (IGA) was implemented to visualize the transformative quality embedded in archetypes. In order to emphasize the experiential property of archetypes, the proposed system was designed to offer users the opportunity to view their exploration in a virtual environment (VE). Emphasis was placed on the artful use of technology in the pre-logical stage of the ideation process based on the theory of archetypes. This paper reports on the results from the experiment based on six museum archetypes focusing on (1) the system’s generative quality; (2) the synthesis $+$ evolution function; and (3) VE integration.

This position paper presents a new approach based on my experience in the evolution of human-centered design (HCD) during four decades, and how it has struggled to become a discipline in its own right in complex socio-technical systems’ creation, development and operations. The 20th century saw tremendous industrial developments based on tangible materials that were transformed and assembled to make washing machines, cars, aircraft and power plants; during its last three decades, electronics and software were incrementally added to hardware machines. Operationalization issues moved from hardware to software, making automation and user interfaces central issues. From the beginning of the 21st century, we began to do the exact opposite! Currently, we typically start a project by designing and developing technology on computers, using software only, which is later transformed into hardware (and software). I denote this shift, the ‘socio-technical inversion’. Operationalization issues are moving from software to hardware, making tangibility a central issue. Three useful conceptual models are presented: the SFAC (Structure/Function versus Abstract/Concrete) model; the NAIR (Natural/Artificial versus Cognitive/Physical) model; and the AUTOS (Artifact, User, Task, Organization and Situation) pyramid. Concepts developed in this article are based on the rationalization of a long experience in the aerospace domain.