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.

Grammars, with their generic approach and broad application potential in many planning fields, are accepted as adaptable and efficient tools for design and planning applications, bridging design rules and technical planning requirements. This paper provides a formal introduction of grammars for effective consolidation and application, including a rule-based notation and required specification information. Two proposed grammar evaluation methods – based on technical planning knowledge and using recent computational development – foster understanding of a grammar’s effects, often missing in other definitions. Knowledge gained enables efficient grammar rule application, e.g. in burgeoning planning software. This research focuses particularly on urban network design and road intersection grammars to validate proposed grammar evaluation methods. Results are specified in the proposed grammar notation with corresponding application specifications. Results generally show that network topology and intersection type choice both depend on transport mode characteristics and flow. Specifically, medium-dense gridiron networks are car-efficient in terms of travel costs and reliability at urban densities, when combined with high road and intersection capacities. Pedestrian networks ideally have higher intersection and road densities with lower capacities than car networks. Highly meshed networks improve overall travel cost efficiencies for all transport modes at various flow levels.

The ‘open approach’ is rooted in the open-source and free-software movements. Its application has spread to more fields than computer engineering. Product design is impacted as well: we observe new stakeholders and practices challenging current structured design processes and leading to industrial successes. Open-design appears to be promising yet disruptive. Moreover, its distinctive features remain unclear.

This paper aims to popularize this new concept, as well as to give both researchers and practitioners an overview of current research on open-design, and its consequences on design. For this, we conducted a systematic quantitative bibliometric analysis of 624 entries corresponding to the keyword ‘open-design’ in the Scopus database. This supports a qualitative synthesis of scientific literature, enabling us to summarize practices falling under the umbrella term ‘open-design’. As such, this paper traces the evolution of product design and the open approach. It also analyzes the impact of open-design on the design process as presented in the scientific literature. Finally, this paper develops a typology of open-design of tangible artifacts that distinguishes among three currently reported varieties of practice: do-it-yourself, meta-design, and industrial ecosystems. As the major contribution of this paper, this typology is developed as a final discussion.

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.

Designers can involve users in the design process. The challenge lies in reaching multiple users and finding the best way to use their input in the design process. Affordance based design (ABD) is a design method that focuses in part on the perceived or existing interactions between the user and the artifact. The shape and physical characteristics of the product enable the user to perceive some of its affordances. The goal of this research is to use ABD, along with an optimization tool, to evolve the shape of products toward better perceived solutions using the input from users. A web application has been developed that evolves design concepts using an interactive multi-objective genetic algorithm (IGA) relying on the user assessment of product affordances. As a proof of concept, a steering wheel is designed using the application by having users rate specific affordances of solutions presented to them. The results show that the design concepts evolve toward better perceived solutions, allowing designers to explore more solutions that reflect the preferences of end users. Relationships between affordances and product design variables are also explored, revealing that specific affordances can be targeted with changes in design parameter values and highlighting the tie between physical characteristics and affordances.

In this paper, a concept for a community innovation platform is introduced focusing on human behavior of motivation and barriers in the context of product generation development. Building on the state of the art, a three year case study in cooperation with Dr. Ing. h.c. F. Porsche AG is at the core. In the first step of the study, a questionnaire and interviews are used to point out that a new attractive channel for ideas is needed. The three perspectives of users, experts and stakeholders are investigated in order to discover needs and preferences. Based on these findings, in a second step, a software prototype was designed and introduced in a pilot project with more than 200 users. Using a questionnaire and expert workshops, in the final step, this project is evaluated as appealing to the community, and the generated content is demonstrated to be valuable to specific activities of product generation development.

Over the last decade, product/service systems (PSSs) have become a research issue in several disciplines, such as engineering design and marketing. The inherent interdisciplinary nature of this research issue has however remained unexploited. In order to bridge these silos and foster more interaction across relevant disciplines, this research examines PSSs from an interdisciplinary angle by analyzing how engineering design and marketing inform one another, as well as presents insights for PSS design. The research is carried out using a three-stage process for analyzing and evaluating interdisciplinary research: first, through a systematic literature review to identify relevant papers and their level of utilization across disciplines; second, by using a qualitative thematic analysis looking for different perspectives in order to find themes to bridge the gap between the disciplines; and third, by providing a research agenda to advance research by moving from silos to synergy. The results show a limited use of theories, frameworks, methods and tools across disciplines thus far, while the major contribution of this article lies in the implications derived for PSS design for academics and practitioners alike, which are categorized into seven specific themes: business orientation, collaboration, cost aspects, flexibility, performance indicators, requirements and services.

Recent advances in early stage failure analysis approaches have introduced behavioral network analysis (BNA), which applies a network-based model of a complex engineered system to detect the system-level effect of ‘local’ failures of design variables and parameters. Previous work has shown that changes in microscale network metrics can signify system-level performance degradation. This article introduces a new insight into the influence of the community structure of the behavioral network on the failure tolerance of the system through the role of bridging nodes. Bridging nodes connect a community of nodes in a system to one or more nodes or communities outside of the community. In a study of forty systems, it is found that bridging nodes, under attack, are associated with significantly larger system-level behavioral degradation than non-bridging nodes. This finding indicates that the modularity of the behavioral network could be key to understanding the failure tolerance of the system and that parameters associated with bridging nodes between modules could play a vital role in system degradation.

We propose a data-driven network-based approach to understand the interactions among technologies, products, and customers. Specifically, the approach enables both a qualitative understanding and a quantitative assessment of the impact of technological changes on customers’ co-consideration behaviors (decision of cross-shopping) and as a consequence the product competitions. The uniqueness of the proposed approach is its capability of predicting complex co-consideration relations of products as a network where both descriptive analyses (e.g., network statistics and joint correspondence analysis) and predictive models (e.g., multiple regressions quadratic assignment procedure) are employed. The integrated network analysis approach features three advantages: (1) It provides an effective visual representation of the underlying market structures; (2) It facilitates the evaluation of the correlation between customers’ consideration preferences and product attributes as well as customer demographics; (3) It enables the prediction of market competitions in response to potential technological changes. This paper demonstrates the proposed network-based approach in a vehicle design context. We investigate the impacts of the fuel economy-boosting technologies and the turbocharged engine technology on individual automakers as well as the entire auto industry. The case study provides vehicle engineers with insights into the change of market competitions brought by technological developments and thereby supports attribute decision-making in vehicle design.

Human-centered design (HCD) offers a systematic approach to innovation practice, driven by customer research and feedback throughout the design process. Within the community of engineers and researchers who engage in design for global development, interest in HCD has grown in the past decade. In this paper, we examine the human-centered design for development (HCD+D) academic community to better understand the interactions between researchers. By building and evaluating a co-authorship network from a dataset of HCD+D papers, in which the nodes are researchers and the connecting links are co-authorship relationships, we provide a decade-long benchmark to answer a variety of questions about collaboration patterns within this emerging field. Our analysis shows that most HCD+D authors publish few papers and are part of small, well-connected sub-communities. Influential authors that bridge separate communities are few. HCD+D is emerging from disparate disciplines and widely shared scholarship across disciplines continues to be developed. Influential authors in HCD+D play a large role in shaping HCD+D, yet there are few authors that are in a position to connect and influence collaborative research. Our analysis gives rise to several implications including an increased need for cross-disciplinary collaboration and the need for a stronger core of HCD+D practitioners.

Idea generation is significant in design, but coming up with creative ideas is often challenging. This paper presents a computer-based tool, called the Combinator, for assisting designers to produce creative ideas. The tool is developed based on an approach simulating aspects of human cognition in achieving combinational creativity. It can generate combinational prompts in text and image forms through combining unrelated ideas. A case study has been conducted to evaluate the Combinator. The study results indicate that the Combinator, in its current formulation, has assisted the tool users involved in the case study in improving the fluency of idea generation, as well as increasing the originality, usefulness, and flexibility of the ideas generated. The results also indicate that the tool could benefit its users in generating high-novelty and high-quality ideas effectively. The Combinator is considered to be beneficial in expanding the design space, increasing better idea occurrence, improving design space exploration, and enhancing the design success rate.

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.

The introduction of autonomous vehicles (autonomous vehicles) will reshape the many social interactions that are part of traffic today. In order for autonomous vehicles to become successfully integrated, the social interactions surrounding them need to be purposefully designed. To ensure success and save development efforts, design methods that explore social aspects in early design phases are needed to provide conceptual directions before committing to concrete solutions. This paper contributes an exploration of methods for addressing the social aspects of autonomous vehicles in three key areas: the vehicle as a social entity in traffic, co-experience within the vehicle and the user–vehicle relationship. The methods explored include Wizard of Oz, small-scale scenarios, design metaphors, enactment and peer-to-peer interviews. These were applied in a workshop setting with 18 participants from academia and industry. The methods provided interesting design seeds, however with differing effectiveness. The most promising methods enabled flexible idea exploration, but in a contextualized and concrete manner through tangible objects and enactment to stage future use situations. Further, combinations of methods that enable a shift between social perspectives were preferred. Wizard of Oz and small-scale scenarios were found fruitful as collaboration basis for multidisciplinary teams, by establishing a united understanding of the problem at hand.

A critical task in product design is mapping information from the consumer space to the design space. This process is largely dependent on the designer to identify and relate psychological and consumer level factors to engineered product attributes. In this way, current methodologies lack provision to test a designer’s cognitive reasoning and may introduce bias through the mapping process. Prior work on Cyber-Empathic Design (CED) supports this mapping by relating user–product interaction data from embedded sensors to psychological constructs. To understand consumer perceptions, a network of psychological constructs is developed using Structural Equation Modeling for parameter estimation and hypothesis testing, making the framework falsifiable in nature. The focus of this technical brief is toward automating CED through unsupervised deep learning to extract features from raw data. Additionally, Partial Least Square Structural Equation Modeling is used with extracted sensor features as inputs. To demonstrate the effectiveness of the approach a case study involving sensor-integrated shoes compares three models – a survey-only model (no sensor data), the existing CED approach with manually extracted sensor features, and the proposed deep learning based CED approach. The deep learning based approach results in improved model fit.

Many public transport authorities have a great interest in introducing zero-emission electric buses. However, the transformation process from diesel to electric bus systems opens up a vast design space which seems prohibitive for a systematic decision making process. We present a holistic design methodology to identify the ‘most suitable system solution’ under given strategic and operational requirements. The relevant vehicle technologies and charging systems are analysed and structured using a morphological matrix. A modular simulation model is introduced which takes technical and operational aspects into account. The model can be used to determine a feasible electric bus system. The technology selection is based on a detailed economic analysis which is conducted by means of a total cost of ownership (TCO) model. To cope with uncertainties in forecasting, a stochastic modelling of critical input parameters is applied and three different future scenarios are evaluated. The applicability of the model was verified in a pilot project in Berlin and the methodology was applied to a realistic operational scenario. Our results indicate that electric bus systems are technically feasible and can become economically competitive from the year 2025 under the conditions examined.

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.

This paper provides an empirical review of the reward-based crowdfunding platform Kickstarter.com, with the aim to explore and identify challenges in crowdfunded product development, which consequently can lead to failure of the crowdfunding campaign. The review was based on the analysis of a total of 144 successfully funded ‘technology’ campaigns, which all concerned the creation of physical consumer hardware preordered by campaign backers. The analysis was built around a failure mode model, which was established through a pre-study. The study reveals that (i) no more than 32% of the campaigns managed to deliver the crowdfunded products on time, and, if campaigns are delayed, (ii) there is a significantly higher probability that the delivered products might lack expected attributes. The causes for delay have many reasons, but (iii) a set of particular product development issues were identified as the main challenges. A better understanding of crowdfunded product development can help researchers and practitioners to better understand and utilize the opportunities of this new product development paradigm.

Open Source Hardware (OSH) is an increasingly viable approach to intellectual property management extending the principles of Open Source Software (OSS) to the domain of physical products. These principles support the development of products in transparent processes allowing the participation of any interested person. While increasing numbers of products have been released as OSH, little is known on the prevalence of participative development practices in this emerging field. It remains unclear to which extent the transparent and participatory processes known from software reached hardware product development. To fill this gap, this paper applies repository mining techniques to investigate the transparency and workload distribution of 105 OSH product development projects. The results highlight a certain heterogeneity of practices filling a continuum between public and private development settings. They reveal different organizational patterns with different levels of centralization and distribution. Nonetheless, they clearly indicate the expansion of the open source development model from software into the realms of physical products and provide the first large-scale empirical evidence of this recent evolution. Therewith, this article gives body to an emerging phenomenon and contributes to give it a place in the scientific debate. It delivers categories to delineate practices, techniques to investigate them in further detail as well as a large dataset of exemplary OSH projects. The discussion of first results signposts avenues for a stream of research aiming at understanding stakeholder interactions at work in new product innovation practices in order to enable institutions and industry in providing appropriate responses.