The maker movement has garnered interest from many disparate fields, from engineering to business management, to behavioural science, to city planning. The reason for this interest no doubt stems from the promised potential of the maker movement to revolutionize not only product creation and manufacturing, but in extension the economy around it. This paper examines existing literature across disciplines for evidence of what the maker movement has achieved so far, with a focus on implications for the field of Industrial Design.

Optimization-driven design offers advantages over traditional experience-based mechanical design. As an example, topology optimization can be a powerful tool to generate body shapes for Additive Manufacturing (AM). This is helpful, when (1) load paths are non-intuitive due to complex design domains or boundary conditions, or (2) the design process is to be automated to minimize effort associated with experience-based design. However, practically relevant boundary conditions are often difficult to put into a formal mathematical language to, for example, either feed it into a topology optimization algorithm, or provide precise quantitative criteria for CAE-supported manual design. This paper presents a survey of three industry use cases and identifies three types of requirements: the first can be directly cast into parts of an optimization problem statement (∼ 40%), the second is considered indirectly by adapting the optimization problem without explicit reference to the requirement (∼ 20%), and the third is only assessed after the design is finalized (∼ 40%). For categories 2 and 3 we propose directions of improvement to support formulating complex design tasks as unambiguous design problems.

Precise sustainability assessment becomes increasingly important in decision-making, marketing, and regulations. Therefore, reliable and comparable LCA becomes mandatory. Currently, primary data is rarely available due to vastly complex value chains. Secondary data from eco-databases provide a remedy to estimate the sustainability impacts of up- and downstream processes. While giving insights and estimations, this data is seldom fitting exactly to the own processes and lacks comparability. Therefore, this paper proposes a method to close the gap between unreliable secondary data and unavailable primary data. This gap is to be closed by the integration of simulated process data. CAM is a tool during the work preparation to assess the design's manufacturability, decrease set-up times and optimize the NC code. However, integrating DES into LCA is still subject to research and will be discussed in this paper. This paper answers the question of the necessary steps to integrate the simulated production process in an LCA to increase the quality and reliability of sustainability indicators. A method is presented, and the implementation of the steps with the help of a developed assistance system on an example is performed.

The research presented in this paper explores a novel method for assessing the effects of biophilic restorative experiences on designers’ cognition by combining the use of physiological, neurocognitive and semantic measures. A total of 12 engineering graduate students participated in a three-step pilot experiment that consisted of (1) a stressor (the Trier Social Stress Test), (2) a destressing intervention (biophilic sound experience), and (3) a design task. Heart rate variability (HRV) was used to track subjects’ autonomic nervous system (ANS) activity. Functional near-infrared spectroscopy (fNIRS) was used to track patterns of brain activation in subjects’ prefrontal cortex (PFC). Changes in design quality were assessed by the semantic space they explored, measured through a natural language processing (NLP) technique. Preliminary findings suggest that an auditory biophilic restorative experience can change designers’ bodies, brains, and minds. Results from this pilot study encourage further exploration of the use of exposure to nature-based stimuli as a method to help enhance engineering design cognition.

Chronobiology is the science that studies the role of time in biology. The study of time in human bodies revealed the presence of internal rhythms related to the time of day. Considering divergent thinking as one of the essential cognitive activities of conceptual design, this paper presents the results of investigating the effect of time of day on designers’ brain activity while performing divergent thinking tasks. An experiment was run with a revised Alternative Uses Task, measuring brain activity with an electroencephalogram (EEG) device. Students with different educational backgrounds were recruited for this experiment, including engineering and industrial design students, to determine if the time of day affected them differently. The brain waves and related power results show significant differences with respect to the time of day and educational background. The differences are particularly evident considering the interaction of these factors. Further studies are required to understand the relationship between the differences detected and the designers’ behavioural performance and to identify which time of day is most effective for idea-generation activities for designers.

As organisations grow, consequences of poor knowledge management are evident for new employees in product developing companies. The problem of leveraging existing knowledge between development projects and departments is still relevant. This paper presents an industrial case study of a traditional manufacturing company and extends prior research addressing the reuse of organisational knowledge in new product development. The paper outlines barriers that hinder effective reuse of codified engineering knowledge and suggest means to overcome those barriers by using A3-reports in the PLM-system.

The importance of forming concepts in one's mind has been argued from various perspectives in design studies. This experimental study examines how the co-creative process affects concept formation considering its depth.

The authors conducted a learning experiment applying three processes; non-interactive (NI), interactive but non-co-creative (NC), and interactive and co-creative processes (C). To evaluate whether and how deep the concept is formed in the examinee's mind, mimetic Japanese words, which contain several different explicit concepts underlying a certain integrated implicit concept, were chosen as learning materials. The examinees without any knowledge about mimetic Japanese words were gathered globally and the experiment was conducted fully online using English. Examinees were tested several times to measure how they had formed these concepts for comparing the processes.

The findings suggest that the co-creative process enhances the depth of concept formation: involvement load and willingness to participate in the co-creative process lead to deeper concept formation.

This paper seeks to address the gap between qualitative Robust Design principles and parameter optimization. The former often fails to consider the challenging amount of details in embodiment and configuration design, while the latter is the widely accepted main thrust in traditional Robust Design. The gap is addressed by exploring the value of five quantitative robustness indicators for Design Space Exploration based on variables, objectives and constraints: The set level indicators, Design Space Size and Pareto Set Dispersion, and the point level indicators, Neighbourhood Performance, Failure Rate and Distance to Failure. As a background for the discussion of the limitations of these indicators an industrial case is presented. The case is an incremental encoder and includes two configurations for comparison, five objectives, eight variables, and a range of constraints. The design spaces are sampled and they show conflicting objectives, dispersed spaces and variables dependencies. Based on this it is suggested that set level indicators are more suitable than point level indicators of early robustness evaluation, but the available indicators are limited in their considerations of design space discontinuity and conflicts.

Additively manufactured final products and components are not always tailored to the additive manufacturing (AM) process, but they need to be in order to exploit the many advantages and potentials that AM provides. Therefore, an appropriate AM design should be targeted, which reduces the necessary iterations in the developing process of AM products. Although there is a large number of existing literature on the Design for Additive Manufacturing (DfAM), designers usually lack criteria in order to assess AM-conformity in conceptual design. In this paper, we provide a basis for the assessment of solution principles regarding their conformity for additive manufacturing.

First, existing literature on DfAM and AM products is reviewed comprehensively to derive criteria for the AM-conformity of solution principles. Subsequently, the correlations between these criteria are identified including the interdependencies to be considered when assessing AM-conformity. A basis for assessment is created, which offers designers early support in the development of AM-conformal designs.

Sustainable production transition requires new paradigms and strategies, as well as alternative materials. Recently, an increasing number of innovative materials were developed. Such novelties greatly affected the design practice, widening the materic possibilities for designed products. However, traditional material classification does not apply well for these new materials trend. In this paper, the authors cooperated with design students to identify an iterative tracing activity of the new material trends for design, finalised to embed in the same work new tendencies that may rise in future.

Industry 4.0 is expected to change competitiveness of manufacturing firms. However, to completely achieve this goal, firms should manage barriers and complexity issues that my hinder its adoption or its effects. For this reason, the study explores, through a literature review, whether and how design theory may be a supporting theory to manage Industry 4.0 adoption and implementation to maximise the opportunities and minimise the risks. The results shows that these research questions require a design approach to innovate not only adopting technologies but reinventing the business practices.

It is of vital importance to explore and understand future users' needs and requirements in the early phases of the product development process. However, in times of social distancing meeting users might not be possible. The project reported on in this paper has investigated the possibilities of conducting advanced user studies online. In total 30 small experimental studies have been conducted. Common digital tools that were used were e.g. Zoom, Teams, Mural, Miro, Snapchat, and Instagram.

The data was analyzed in a thematic content analysis by the authors on Mural. Identified challenges were excluding not tech-savvy user groups, missing out on interpersonal interaction and observations, as well as difficulties creating participant commitment and trust. On the positive side were perceived efficiency, a more levelled power distribution between participants, and ease of engagement and data retrieval for tech-savvy users.

Identified best practices included lowering social barriers through warm up activities and techniques to support open discussion during workshops. Furthermore, engagement could be supported through private social media groups, regular reminders, as well as clear communication of purpose and goal of the activities.

In user-centred design, digital human models hold the potential for proactive evaluations of ergonomics or discomfort in terms of a computer aided ergonomics tool. Therefore, models predicting human interaction behaviour, are necessary. In this contribution we present such a model as well as its initial evaluation. The evaluation is performed by applying the interaction model to a specific use case, conducting a comparison with an empirical subject study. The evaluation shows that similar and realistic human behaviour was predicted, which was consistent in terms of whole-body strain.

We developed a wearable experimental sensor setup featuring multimodal EEG+fNIRS neuroimaging applicable for in situ experiments of human behavior in interaction with technology. A low-cost electroencephalography (EEG) was integrated with a wearable functional Near-Infrared Spectroscopy (fNIRS) system, which we present in two parts. Paper A provide an exhaustive description of setup infrastructure, data synchronization process, a procedure for usage, including sensor application, and ensuring high signal quality. This paper (Paper B) demonstrate the setup';s usability in three distinct use cases: a conventional human-computer interaction experiment, an in situ driving experiment where participants drive a car in the city and on the highway, and an ashtanga vinyasa yoga practice in situ. Data on cognitive load from highly ecologically valid experimental setups are presented, and we discuss lessons learned. These include acceptable and unacceptable artefacts, data quality, and constructs possible to investigate with the setup.

When designing assistive devices for children with disabilities, designers mostly consider technical and functional aspects and overlook factors that affect their usage from children’s perspective. Therefore, in most cases, assistive devices do not fully meet the needs of the children and may create a negative effect on children’s well-being. To explore the opinion’s of children using 3D printed hand prosthetics in Country-Xx, individual generative sessions were conducted with four children with limb deficiency. Generative tools are used to engage children and encourage them to express themselves in relation to prosthesis use. The main aim was to investigate how children provide design relevant information that may help designers to achieve improved assistive devices that support children’s physical, emotional and social wellbeing. Children’s feedback related to prosthetic usage categorized under two topics; expectations of children for prosthesis use and children’s priority expectation for the prosthesis. The findings are argued to be useful and usable by NGOs, product designers and design researchers who work with children with disabilities.

Finite element (FE) simulations can be used both in the early product development phase to evaluate the performance of developed components as well as in later stages to verify the reliability of functions and components that would otherwise require a large number of physical prototype tests. This requires calibrated material cards that are capable of realistically representing the specific material behavior. The necessary material parameter identification process is usually time-consuming and resource-intensive, which is why the direct inverse method based on machine learning has recently become increasingly popular. Within the neural network (NN) the generated domain knowledge can be stored and retrieved within milliseconds, which is why this method is time and resource-efficient. This research paper describes advantages and potentials of the direct inverse method in the context of the product development process (PDP). Additionally, arising transformation opportunities of the PDP are discussed and an application scenario of the method is presented followed by possible linkage potentials with existing development methods such as shape optimization.

The defense industry tends to anticipate environmental issues through eco-design integration in the overall design process. This leads to focus on the impact of technological and design choices of complex systems while maximizing operational performance. Such development involves long and complex processes and is constrained in a project owner and industrial project manager context. In this context poorly described in the literature, the objective of this paper is to identify barriers and drivers to achieve an efficient application of eco-design. A comprehensive analysis of the interactions and the current design processes is performed in the context of the French defense industry. Through internal documentation and semi-structured interviews with the key actors, the generic design process of a project owner is analysed (including relationships with industrial project manager). The failure modes that currently limit the integration of eco-design in projects are also identified.

Makers have proven to be skilled at prototyping and therefore present a unique opportunity for companies, who seek to improve their capabilities, to learn from them. In this study, a mixed methods approach was used to understand possible benefits to both companies and makers from collaborating in prototyping, and to identify a set of design considerations to guide the future development of a tool to facilitate such collaboration. Despite challenges to collaboration, a tool designed to help companies engage with makers in prototyping could be beneficial to both and should be developed.

More and more attention is paid nowadays to the human health concerns, associated with environmental problems arising from the fossil fuel use. The world scientific community offers new alternatives that, despite being more environmentally friendly, require an analysis of their potential environmental impacts. For example, biorefineries are becoming increasingly widespread nowadays offering a large gamma of bio-based products. However, it is necessary to take into account what potential effects such facility may have on the human health, depending on its geographical location since different territories may be more or less sensitive to its installation. Our study describes a new bioprocess implementation in terms of impact on human health through three countries: France, Belgium or China. In order to understand what territory can be more appropriate to the industrial process installation in terms of its effects on the human health, we propose to use the spatialized life-cycle analysis methodology.

This paper introduces a new method to help designers assess the impact of changes to a product platform when introducing a new variant. The method evaluates a platform design by investigating how changing some components will impact other platform design perspectives such as material, function, manufacturing processes and assembly time. To assess the usefulness of this method, it was applied to assess platform changes resulting from successive generations of scanner heads from two manufacturers. The method indicated that one manufacturer improved their scanner head design by improving the functionality of its components and assembly time. Whereas, the other manufacturer's new scanner head used more material and manufacturing processes without benefiting other design perspectives. Compared to existing product family evaluation methods which focus only on maximising commonality between product variants, the proposed method considers potential platform design improvements and assesses them from multiple design perspectives before deciding on reusing existing components or implementing the new design. The information from this method will also complement existing commonality indices.