In many engineering design contexts models are indispensable. They offer decision support and help tackle complex and interconnected design projects, capturing the underlying structure of development processes or resulting products. Because managers and engineers base many decisions on models, it is crucial to understand their properties and how these might influence their behaviour. The level of detail, or granularity, of a model is a key attribute that results from how reality is abstracted in the modelling process. Despite the direct impact granularity has on the use of a model, the general topic has so far only received limited attention and is therefore not well understood or documented. This article provides background on model theory, explores relevant terminology from a range of fields and discusses the implications for engineering design. Based on this, a classification framework is synthesised, which outlines the main manifestations of model granularity. This research contributes to theory by scrutinising the nature of model granularity. It also illustrates how this may manifest in engineering design models, using Design Structure Matrices as an example, and discusses associated challenges to provide a resource for modellers navigating decisions regarding granularity.

The design process often requires work by teams, rather than individuals. During team based design it is likely that situations will arise in which individual members of the team have different opinions, yet a group decision must still be made. Unfortunately, Arrow’s impossibility theorem indicates that there is no method for aggregating group preferences that will always satisfy a small number of ‘fair’ conditions. This work seeks to identify methods of combining individual preferences that can come close to satisfying Arrow’s conditions, enabling decisions that are fairer in practice. First, experiential conjoint analysis was used to obtain individual empirical utility functions for drinking mug designs. Each empirical utility function represented individual members who were part of a design team. Then, a number of functions for constructing group preference were analysed using both randomly generated preferences and empirical preferences derived from the experiential conjoint survey. The analysis involved checking each of Arrow’s conditions, as well as assessing the potential impact of strategic voting. Based on the results, methods that should be used to aggregate group preference within a design team in practice were identified and recommended.

Models of products and design processes are key to interacting with engineering designs and managing the processes by which they are developed. In practice, companies maintain networks of many interrelated models which need to be synthesised in the minds of their users when considering issues that cut across them. This article considers how information from product and design process models can be integrated with a view to help manage these complex interrelationships. A framework highlighting key issues surrounding model integration is introduced and terminology for describing these issues is developed. To illustrate the framework and terminology, selected modelling approaches that integrate product and process information are discussed and organised according to their levels and forms of integration. Opportunities for further work to advance integrated modelling in engineering design research and practice are discussed.

‘Practice what you preach’ is a phrase occasionally used to refer to those not acting as they want others to act. There are countless opportunities in professional work and daily life to bring such criticism upon ourselves. While the subject is broad, this study focuses on the application of this idea in research practice, and more specifically in design research. One point of departure is the question: ‘how should we practice research if its results are products just like other products?’ The Principle of Reflexive Practice (PRP) states that considering the outcome of design research or research itself as a product, many design principles, tools, methods or knowledge are applicable to design research.

A corollary of the principle is that in order to succeed in contemporary research environments, design researchers would gain significant benefit such as improving the success rate of their research projects, if they exercise design methods and tools in designing their research. By exercising these methods, researchers would gain quick and rich feedback about the methods they develop; they would become aware of issues that require users’ perspective that could not be possible without their own practical use.

The PRP makes participants in design research aware of the reflexive opportunity in studying design that could be mobilized to advancing their practice and making their research results more effective. Notwithstanding, adopting the PRP is not easy; therefore, it is presented as a challenge to design research. Four examples of using the PRP as a guiding principle in research are presented to demonstrate its importance and benefits.

Most products are developed in generations. This needs to be considered with regard to development methods and processes to make existing knowledge available to achieve increased efficiency. To realize this, the approach of PGE – product generation engineering – is formulated. Product generation engineering is understood as the development of products based on reference products (precursor or competitor products). The subsystems are either adapted to the new product generation by means of carryover or they are newly developed based on shape variation or principle variation. Validation is considered as the central activity in the product engineering process and is a major challenge, especially for complex mechatronic systems. Therefore, it is important to understand validation as an ongoing activity during product development. The pull principle of validation describes the definition and development of validation activities, including models and validation environments based on specific validation objectives. In order to have effectiveness within validation of subsystems, it is necessary to map the interactions with the overall system, namely the super-system. The relevant subsystems can be connected under consideration of functional and energetic aspects by means of virtual, physical or mixed virtual–physical modeling applied by the holistic IPEK-X-in-the-Loop approach within the integrated Product engineering Model (iPeM).

As a discipline, design science has traditionally focused on designing products and associated technical processes to improve usability and performance. Although significant progress has been made in these areas, little research has yet examined the role of human behaviour in the design of socio-technical systems (e.g., organizations). Here, we argue that applying organizational psychology as a design science can address this omission and enhance the capability of both disciplines. Specifically, we propose a method to predict malfunctions in socio-technical systems (PreMiSTS), thereby enabling them to be designed out or mitigated. We introduce this method, describe its nine stages, and illustrate its application with reference to two high-profile case studies of such malfunctions: (1) the severe breakdowns in patient care at the UK’s Mid-Staffordshire NHS Foundation Trust hospital in the period 2005–2009, and (2) the fatal Grayrigg rail accident in Cumbria, UK, in 2007. Having first identified the socio-technical and behavioural antecedents of these malfunctions, we then consider how the PreMiSTS method could be used to predict and prevent future malfunctions of this nature. Finally, we evaluate the method, consider its advantages and disadvantages, and suggest where it can be most usefully applied.

Towards addressing ontological issues in design cognition research, this paper presents the first generic classification of cognitive processes investigated in protocol studies on conceptual design cognition. The classification is based on a systematic review of 47 studies published over the past 30 years. Three viewpoints on the nature of design cognition are outlined (search, exploration and design activities), highlighting considerable differences in the concepts and terminology applied to describe cognition. To provide a more unified view of the cognitive processes fundamentally under study, we map specific descriptions of cognitive processes provided in protocol studies to more generic, established definitions in the cognitive psychology literature. This reveals a set of 6 categories of cognitive process that appear to be commonly studied and are therefore likely to be prevalent in conceptual design: (1) long-term memory; (2) semantic processing; (3) visual perception; (4) mental imagery processing; (5) creative output production and (6) executive functions. The categories and their constituent processes are formalised in the generic classification. The classification provides the basis for a generic, shared ontology of cognitive processes in design that is conceptually and terminologically consistent with the ontology of cognitive psychology and neuroscience. In addition, the work highlights 6 key avenues for future empirical research: (1) the role of episodic and semantic memory; (2) consistent definitions of semantic processes; (3) the role of sketching from alternative theoretical perspectives on perception and mental imagery; (4) the role of working memory; (5) the meaning and nature of synthesis and (6) unidentified cognitive processes implicated in conceptual design elsewhere in the literature.

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.

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 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.

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.

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 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.

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 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.

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.

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.

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.

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.