Information usage is a key aspect of creative cognition and has been shown to influence design outcomes. The goal of this study was to investigate the information seeking behavior of student designers while validating a previously developed “Typology of Design Information” framework. Participants were asked to use and evaluate pieces of information during the idea generation process. Results show a discrepancy between the information that participants naturally sought out and their perceived utility (helpfulness) of the information. However, individually significant relationships between perceived utility and behavior were found with features generated by participants, suggesting that even though participants' perception of the utility of information pieces and their actual behavior are not related, both constructs have an identifiable influence on design outcomes. This study advances the Typology of Design Information framework by empirically exploring the link between the types of information used by novice designers and the ideas generated, and it illustrates that participants employ complex cognitive behavior when engaging with design information to generate novel ideas.

Automotive systems are changing rapidly from purely mechanical to smart, programmable assistants. These systems react and respond to the driving environment and communicate with other subsystems for better driver support and safety. However, instead of supporting, the complexity of such systems can result in a stressful experience for the driver, adding to the workload. Hence, a poorly designed system, from a usability and user experience perspective, can lead to reduced usage or even ignorance of the provided functionalities, especially concerning Adaptive Driver Assistance Systems.

In this paper, the authors propose a combined design approach for user behavior evaluation of such systems. At the core of the design is a mixed methods approach, where objective data, which is automatically collected in vehicles, is augmented with subjective data, which is gathered through in- depth interviews with end-users. The aim of the proposed methodology design is to improve current practices on user behavior evaluation, achieve a deeper understanding of driver's behavior, and improve the validity and rigor of the named results.

This paper aims to provide suggestions for the identification of potential new applications for the existing knowledge. A method is presented for extracting information about a product or technology, processing the international patent database (IPD) and extracting useful hints for potential new applications. The approach uses the Cooperative Patent Classification as stimulus for inspiring new potential fields towards which export existing product or technologies. Although some limits inevitably affect the approach, relevant directions for future developments have been inferred for a more comprehensive exploitation of both the firm internal knowledge and the suggestions provided by the international patent database. The achieved results can support firms in expanding market opportunities for their products or technologies.

To objectively and quantitatively study transcribed protocols of design problem solving conversations, we propose a semantic analysis approach based on dynamic semantic networks of nouns constructed with WordNet 3.1 lexical database. We examined the applicability of the semantic approach focused on a dynamic evaluation of the design problem solving process in educational settings. Using a case of real- world design problem-solving conversations, we show that the approach is able to determine the time dynamics of semantic factors such as level of abstraction, polysemy or information content, and quantify convergence/divergence of semantic similarity in design conversations between students, instructors and real clients. The approach can also be used to evaluate the aforementioned semantic factors for successful and unsuccessful ideas generated in the process of design problem solving, or to assess the effect of external feedback on the developed design solution. The proposed semantic analysis approach allows fast computation of the semantic factors in real time thereby demavonstrating a potential for both monitoring and support of the design problem solving process.

Techniques and processes used for concept generation rely on composing new concepts and analysis given situational context. Composition and analysis require distinct neurocognitive function. For instance, jazz composition relies heavily on the right brain, while math relies on the left. Similar to music and math, is concept generation hemisphere dominant? What differences exist when using varying techniques? Twelve graduate engineering students were given three design tasks and instructed to use brainstorming, morphological analysis and TRIZ. A device called fNIRS measured cognitive activation. The results find left hemisphere dominance. More specifically, the left dorsolateral PFC (dlPFC), which is central to spatial working memory and filtering information. Temporal differences do exist. Morphological analysis and TRIZ reinforced the use of the left dlPFC, while brainstorming increased the use of the right dlPFC and medial PFC (mPFC) late during concept generation. The right dlPFC contributes to divergent thinking and mPFC facilitates memory retrieval. One explanation is designers relaxed rule constraints and more deeply searched for associations during brainstorming.

In the uncertain process of product development, the developer is decisively responsible for product success. He operates in a complex environment that directly influences his synthesis and analysis activities. The context of the socio-technical system of product development has already been extensively researched and defined by a large number of factors. However, the developer is described as part of the context and not as the centre, which means that many of these factors have no interaction with the developer. For the design of methods and tools that support the developer in his activities in the development process, a summarizing understanding of the influences on and by the developer is necessary. In order to create a unified understanding of the developer at the centre of product development, a Systematic Literature Review was conducted. In this article, the procedure and findings are presented. The aim was to identify factors from the literature that significantly influence the interaction of the developer in his environment. As a result, these were documented in a model, which represents the basis for further, human-centred research in the context of product development.

New tools from neuroscience allow design researchers to explore design neurocognition. By taking the advantage of EEG's temporal resolution we give up spatial resolution to focus on the performance of time-related design tasks. This paper presents results from an experiment using EEG to measure brain activation to study mechanical engineers and architects to compare their design neurocognition. In this study, we adopted and extended the tasks described in a previous fMRI study of design neurocognition reported in the literature. The block experiment consists of a sequence of 3 tasks: problem solving, basic design and open design using a physical interface. The block is preceded by a familiarizing pre-task using the physical interface and then extended to a fourth task using free-hand sketching. Brainwaves were collected from both mechanical engineers and architects. Results comparing 36 mechanical engineers and architects while designing were produced. These results indicate design cognition differences between the two domains in task-related power between the problem-solving task and the design tasks, in temporal resolution and transformed power.

Behavioural design is a crucial research area due to its potential in leveraging the positive outcomes of traditional design. Current need for theory building requires discerning the unique characteristics and challenges of behavioural design. To contribute towards this goal, the paper structures the conceptual and operational uniqueness of the behavioural design using the process and cognitive perspective. Process model uses the basic design cycle to discern the tasks and stages of behavioural design. Cognitive perspective uses dual process theory and cognitive strategies used by designers. Integrated model of process and cognitive perspective is the crucial contribution of this paper. A case study involving interview of lead designers from five behavioural design consultancies has been used to present and elaborate the usefulness of the integrated model of behavioural design. Integrated perspective links the process characters like incomplete analysis, simulation and evaluation stages, over reliance on the prescriptive methods, and unequal emphasis to multiple disciplines, with incomplete analytical process, and solution and knowledge driven strategy along cognitive perspective

Recently, design researchers have begun to use neuroimaging methods (e.g., functional magnetic resonance imaging, fMRI) to understand a variety of cognitive processes relevant to design. However, common neuroimaging analysis techniques require significant assumptions relating temporal and spatial information during model formulation. In this work, we apply hidden Markov Models (HMM) in order to uncover patterns of brain activation in a design-relevant fMRI dataset. The underlying fMRI data comes from a prior research study in which participants generated solutions for twelve open-ended design problems from the literature. HMMs are generative models that are able to automatically infer the internal state characteristics of a process by observing state emissions. In this work, we demonstrate that distinct states can be extracted from the design ideation fMRI dataset, and that designers are likely to transition between a few key states. Additionally, the likelihood of occupancy within these states is different for high and low performing designers. This work opens up the door for future research to investigate the patterns of neural activation within the discovered states.

This paper presents a new method of human-response testing to enhance the success of designs. Rather than waiting until after a building is constructed to see how the design will affect human users, we developed a high-resolution virtual-reality platform to present design variations to the study participants. This technique allowed us to make very precise adjustments in design variables (e.g., the ceiling height, or the placement of windows) within the same overall structure, thereby obtaining more empirically rigorous comparisons than is possible in traditional post-occupancy studies of completed buildings. In addition, this approach allowed us to collect a variety of biometric data, such as EEG signals, heart rate, head motions, and other indicators of attention and stress, while the study participants interacted with the virtual environments. The overall outcome of this research method will be to improve the human quality of the built environment and to promote data-driven innovation in the design field.

The amount of new virtual reality input and output devices being developed is enormous. Those peripherals offer novel opportunities and possibilities in the industrial context, especially in the product development process. Nevertheless, virtual reality has to face several problems, counteracting reliable use of the technology, especially in ergonomic and aesthetic assessments. In particular, the discrepancies in perception between the real world and virtual reality are of great importance.

Therefore, we discuss these most important issues of current virtual reality technology and highlight approaches to solve them. First, we illustrate the use cases of VR in the product development process. In addition, we show which hardware is currently available for professional use and which issues exist with regard to visual perception and interaction. Derived from the depiction of a perfect virtual reality, we define the requirements to address visual perception and interaction. Subsequently we discuss approaches to solve the issues regarding visual perception and evaluate their suitability to enhance the use of virtual reality technology in engineering design.

In the first quarter of the new millennium, the immersive technologies such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) are only a few steps away from becoming the mainstream tools within the design industry. This study investigated the internal and external barriers of technology adoption within design-oriented businesses. A mixed method was used to collect and analyze the data from the employees of a large design firm. This research confirmed that external barriers such as funding, technical support, training, and business strategy that exist at the organizational level are interrelated with the internal barriers such as designers’ and managers’ perception and attitude toward the new technologies. The managerial applications were discussed later and the directions for future research were provided.

This paper discusses the issues involved with creating a Tangible Augmented Reality representation of a product so that it can be effectively and validly used to support the product design process. The development of a TAR representation entails building the physical model of the product, a digital model of the product, and developing interactions between the digital and physical representations. Different products have different user interactions, which makes developing TAR representation for products challenging since a new interaction needs to be mimicked. Challenges of developing TAR representations are discussed by investigating TAR representations of four consumer products: a space heater, a MP3 player, an electric can opener, and a seat assist cushion. The goal of TAR representations is to not only communicate the functionality of a product but also to improve the time efficiency of prototyping of physical products. Hence, having a good understanding of the user interactions that need to be developed and planning the representation for construction in the modeling software and AR software is crucial to making the process of developing a TAR representation efficient.

Use of virtual reality (VR) is considered beneficial for reviewing 3D models throughout product design. However, research on its usability in the design field is still explorative, and previous studies are often contradictory regarding the usability of VR for 3D model review. This paper argues that the usability of VR should be assessed by analysing human factors such as spatial perception and taking into consideration the complexity of the reviewed product. Hence, a comparative evaluation study has been conducted to assess spatial perception in desktop interface-based and VR-based review of 3D models of products with different levels of complexity. The results show that participants in VR more could perceive the fit of user interface elements, and estimation of the model dimensions had a lower relative error than in desktop interface. It has been found that various sensory cues are used to perceive the model size and that the employed sensory cues depend on the level of complexity. Finally, it is proposed that differences between a desktop interface and VR for reviewing models are more evident when reviewing models of higher complexity levels.

To design interactive behaviours for their products designers/makers have to use high fidelity tools like ‘electronic prototyping kits’, involving sensors and programming to incorporate interactions in their products and are dependent on availability of hardware. Not every designer is comfortable using such tools to ideate and test their concept ideas, eventually slowing them down in the process. Thus, there is a need for a design tool that reduces dependence on complex components of such tools while exploring new concepts for product design at an early stage. In this work, we propose a Mixed Reality system that we developed to simulate interactive behaviours of products using designed visual interaction blocks. The system is implemented in three stages: idea generation, creating interactions and revision of interactive behaviours. The implemented virtual scenario showed to elicit high motivation and appeal among users resulting in inventive and creative design experience at the same time. As a result, designers will be able to create and revise their interaction-behavioural design concepts virtually with relative ease, resulting in higher concept generation and their validation.

Assessing the impact of design automation on design practice prior to its implementation is difficult and subject to uncertainties. One reason for this is the designers' lack of knowledge about design automation. In this work, an industrial case study focusing on conceptual design of hydraulic circuits is conducted to assess the impact of the designers' knowledge on design automation potential estimation. In particular, the impact of demonstrating a prototypical implementation of a design automation application is investigated as a means to enhance the designers' knowledge about design automation. In this respect, a given set of metrics is rated twice to enable a comparative study: prior to and after introducing the design automation prototype. The yielded results show that the knowledge impacts the rating and supports reliability of potential estimation. Further, it is shown that designers acknowledge design automation potential for the early stages of design given sufficient knowledge about design automation. Yet, the results also indicate that careful attention needs to be put on the aspects covered by the prototype in order to avoid biasing participants.

The ability to effectively analyse design concepts is essential for making early stage design decisions. Human evaluations, the most common assessment method, describe individual design concepts on a variety of ideation metrics. However, this approach falls short in creating a holistic representation of the design space as a whole that informs the underlying relations between concepts. Motivated by this shortcoming, this work leverages network theory to visualize and characterize features of a conceptual design space. To illustrate the utility of network theory for these purposes, a network composed of a corpus of solutions to a design problem and their semantic similarity is derived, and its design properties (e.g., uniqueness and innovation potential) are studied. This network-based approach not only characterizes features of individual designs themselves, but also uncovers more nuanced properties of the design space through studying emerging clusters of concepts. Overall, this work expands on developing research in design, demonstrating the value in applying network analytics to a conceptual design space as an engineering support tool to aid design decision-making.

In this paper we use formal tools from category theory to develop a foundation for creating and managing models in systems where knowledge is distributed across multiple representations and formats. We define a class of models which incorporate three different representations---computations, logical semantics, and data--as well as model mappings (functors) to establish relationships between them. We prove that our models support model merge operations called colimits and use these to define a methodology for model integration.

SAR provides an unobtrusive implementation of AR and enables multiple stakeholders to observe and interact with an augmented physical model. This is synonymous with co-design activities and hence, there is a potential for SAR to have a significant impact in the way design teams may set-up and run their co-design activities in the future. Whilst there are a growing number of studies which apply SAR to design activities, few studies exist that examine a particular element of a design activity in a controlled manner. This paper will begin to fill this gap through the controlled study of SAR and its effects on the communication between participants of a co-design activity. To do so the paper compares a controlled design session, using more traditional methods of design representations (3D models on a screen), to sessions run using SAR. The sessions are then analysed to gather information on the gestures used by the participants as well as the overall efficiency of the participants at completing the set design task. The paper concludes that the data gathered tentatively supports a link between the use of SAR and improved communication between design session participants.

A Contradiction Matrix of TRIZ that classifies problems to solve as contradictions of features is an effective framework of knowledge management for problem solving. The features, however, may have a problem of completeness because they may not cover contradictions about all physical phenomena. In addition, rigidly structured Contradiction Matrix may have a problem of searchability because a relevant contradiction may not be properly searched if a recorder and a retriever describe it differently. To solve these problems, this paper proposes a semistructured contradiction matrix using not TRIZ features but physical quantities in SI unit. To enable not only exact match but also partial match in searching for relevant contradictions, dimensional similarity and qualitative value similarity of physical quantity and similarity between contradictions are defined. The proposed method is implemented as software in Python and contradictions are described in XML and stored in a semistructured matrix. From the result of similarity calculation between stored contradictions, possible effectiveness of the proposed method is confirmed.