Recently, methods and approaches such as Participatory Data Analysis, Data-Enabled Design, and Contextual Inquiry have highlighted how design activities can benefit from behavioral data. This data offers new ways to learn from what people do and how they do it, across time and space. However, behavioral data introduces changes and frictions to design activities and poses several challenges for designers to overcome. In this paper, we conduct two workshops with 18 expert designers, from industry and academia, to understand the nature of these challenges, beyond the technical aspects. We contribute by underlining the challenges and opportunities of incorporating behavioral data into design activities; including a design perspective on data, interacting with participants, and interacting with regulatory bodies. We translate our findings into opportunities for a better alignment between regulatory bodies, designers, and participants. We propose to harness the iterative nature of design activities and embedded it into a process that allows for continuous reflection, reassessment, and review of highly dynamic datasets.

The perceived complexity of a product (product complexity) is doubtless an influential phenomenon in a design project. Insight into this factor and how it can be measured, is key to understanding its influence, supporting project planning and resource demand estimation. Opinions on product complexity vary greatly, with many definitions, scales and techniques to measure product complexity available; many of which draw their conclusions from engineering design research. Yet the field of product (or industrial) design companies, whose designers work across a vast range of product types, from domestic to industrial remains under researched. These designers have a tacit understanding of many influences over their projects, of which product complexity is one.

This paper presents an analysis of the dimensions (or measures) of product complexity found in literature and compares its findings to the measures defined by practicing product designers. This paper will demonstrate the process used to identify these dimensions and the scales developed to assess product complexity in a practical way and will make conclusions on the perspectives held on product complexity by product designers.

Engineered products have economic, environmental, and social impacts, which comprise the major dimensions of sustainability. This paper seeks to determine the interaction between design parameters when the social impacts are incorporated into the design process. Social impact evaluation is increasing in importance similar to what has happened with environmental impact consideration in recent years in the design of engineered products. Concurrently, research into new airship design has increased, however airships have yet to be reintroduced at a large scale and for a range of applications in society. Although airships have the potential for positive environmental and economic impacts, the social impacts are still rarely considered. This paper presents a case study of the hypothetical introduction of airships in the Amazon to help local farmers transport their produce to market. It explores the design space in terms of the airship's social impacts connected to the design parameters. The social impacts are found to be dependent not only on the social factors and airship design parameters, but also on the farmer-airship system, suggesting that socio-technical systems design will benefit from integrated social impact metric analysis.

This paper chronicles and reflects on the processes and the meanings of a project of speculative design that creates a narrative based on the scientific notion of phytomining, the activity of extracting metals from the soil using plants. The paper reflects on the ability of the project of bringing together people from different expertise, as a successful case study of Speculative Design and Research through Practice. Besides the scientific and technical challenges posed by GeoMerce, the authors of this paper reflect on the critical framework that set the basis for such a complex project.

The development of technical systems requires close cooperation of stakeholders from different disciplines. This collaboration takes place in workshops. Driven by digitalization and by the current pandemic such workshops take place primarily online. Suitable collaboration tools and methods are crucial to success. At the beginning of such workshops, use and damage scenarios are identified. In this paper, we presented a method and tool for identifying and modeling use and damage scenarios, which we evaluated in 14 online workshops with a total of 118 participants over a period of almost 3 years.

Many activities in the new product development requires the decision making to find the final solution from multiple alternatives and make an evaluation. Even methods to support decision maker are available, the decision can go to the wrong direction because of heuristics. “Decoy effect” is a heuristic that appears in a comparison when 2 of 3 alternatives are similar but different in quality. The alternative that is similar but better in quality is possibly selected. The paper aims to understand the decoy effect by investigating it in the pairwise comparison that is a powerful technique for comparing alternatives. In an experiment, 3 ideas for the next generation of apple peeler are compared in pairs with different sequences. An impact of the decoy alternative on the comparison between other two alternatives, is investigated. Results show low impact of the decoy effect in the pairwise comparison, but this effect induces a high chance of selecting the decoy alternative when comparing the results from this study and the previous study by proposing 3 alternatives in the same sequence. Applying pairwise comparison to avoid decoy effect is thus an idea that will be further investigated.

In this research some systemic forces to sustainable design are described and mapped out, along with key areas, dimensions and stakeholders. These results are visualized in a causal loop diagram (CLD), which was the outcome of a group model building approach supported by a literature review. Within the proposed system model, represented by the system-level variables and their relationships within the CLD, some potential leverage points that can help make product design better contribute to sustainability are identified and described. These can be found in the balancing and reinforcing feedback loops of the CLD as well as the mapping to societal dimensions of sustainability transitions and stakeholder groups. Among the stakeholder groups, business managers, scientific researchers and engineering designers can be tied to the design community. Future research is proposed to build on these initial results to deepen the knowledge about the systemic drivers and barriers and leverage the contribution of design practice to sustainable development.

Social robots are in direct communication and interaction with people, thus it is important to design these robots for different needs of individuals or small groups. This has revealed the need to develop design methods for personalized or mass-individualized social robots, which are expected to respond to many different needs of people today and in the future. In this paper, a previously developed 3D DSM model is implemented in the systematic conceptual design of social robot families. The model is independent of any physical elements and based on behavioural elements as perception, cognition and motoric action. The data regarding 45 different social robots from 80 articles in the literature is used to identify these three behaviours of the existing social robots and the mutual relationships among these different behaviours are defined in order to develop a 3D DSM structure to be used as a basis for designing social robot families. The resulting novel 3D DSM is a general-purpose, basic model that can be used to identify behavioural modules to design social robot families.

Finding redundant requirements or semantically similar ones in previous projects is a very time-consuming task in engineering design, especially with multilingual data. Due to modern NLP it is possible to automate such tasks. In this paper we compared different multilingual embeddings models to see which of them is the most suitable to find similar requirements in English and German. The comparison was done for both in-domain data (requirements pairs) and out-of-domain data (general sentence pairs). The most suitable model were sentence embeddings learnt with knowledge distillation.

Innovative products can be highly prospective and apt to disrupt usages profoundly. They can lead to multiple long-term social impacts influencing people's way of life and behaviour. So it is necessary to anticipate them without delay. Due to high uncertainty, designers may face the problem that conventional user-centred methods, which assess design performances from today's users, are not adapted. We think sociologists can help characterise the likely social impacts of future products. So we propose an original framework called the Representation-Usage-Impact (RUI) method to stimulate sociologists' projection and capture relevant knowledge about probable social impacts. The method includes a database structure encoding the knowledge of sociologists for further use in the design process. Its goal is to help designers avoid making choices today that may be regretted in decades. We illustrate the method and its process with the design of autonomous vehicle scenarios, as it will likely bring many new usages in the future. As the method is still under construction, we present an intermediate validation step involving sociologists. The first results suggest that the method might be a safeguard for the design of disruptive products.

This paper presents models that identify two “cultures” of computational design practice. By reviewing the established culture of computational optimization efforts and contrasting it with the emerging work integrating human-factors into these optimizations, this paper argues that there are sets of key assumptions, outputs and tools that can be synthesized for a generalizable understanding of computational design. Furthermore, this synthesis facilitates the identification of key tools suited to computational design efforts seeking to integrate the complex data associated with human-factors.

One of the greatest challenges of effectively managing knowledge in an organization is promoting seamless connections of operations between departments, the Product Lifecycle Management paradigm. It is also a paradigm that fosters organizational adaptability and quick change in production. Historically, information systems supporting operations have been developed with a specific department's culture in background. Due to this legacy, connecting data, information systems and people across the product lifecycle is an ongoing puzzle for organizations. Theorists and practicians agree on the need to include employees' expertise and vision in this process. However, this involves multiple perspectives and needs that are different but equally valid make. This study explores a tacit knowledge capture tool to be used as a means to voice the interaction and negotiation among employees. Through its influence on ontologies, concept maps collaborative creation can provide a usability tool focused on meaning throughout the product lifecycle. A literature review of the challenges involved and of the proposed tool is presented, followed by a use case and concluded with recommendations drawn from theory and practice.

This study aims at proposing an AI-agent model that helps designers to understand and interpret clients’ intent and create customized design outcomes. We recorded and analysed the purchasing process of collecting product information, selecting alternative products and making decision to understand the influence of artefacts on the client's intent during the purchasing process and collect the basic data for proposing an AI-agent model. We analysed the process by Linkography and found the relationship between the decision-making patterns and the artefacts that presented by the AI-agent.

The shift from linear to circular patterns is on the way and rise many questions. In the last ten years, reuse and upcycling are gaining more attention. Since reduce and reuse were describe as a priority by the European Union, some leading projects are unveiled in different countries. Scale and quality of those projects push the reuse issue out of the shadow, far from original prejudices who associate waste and reuse to « poverty » and « Do It Yourself ». Although Reuse emerge as a prominent question, the idea and boundaries of « what is reuse » appears to be blur and not clearly understood. This situation lead to general incomprehension, even for professionals. Reuse, repurpose, upcycling and recycling are usually considered to wear the same meaning despite a huge difference on what it implies.

In this paper we will examine these different notions through a pedagogical case study. We will draw the different ways to regenerate value at all steps of product life cycle in a precise manner. This allows to better insight the meaning of those issues in the case of student design education. In the same time, it aims to be a tool for teaching sustainable design and waste management.

Developing digital platform business models, especially in business-to-business (B2B) markets, has a high potential for companies who successfully develop their products in generations. The model of SGE - System Generation Engineering describes the development of mechatronic systems on subsystem level. The authors investigate to what extent a comprehensive and unified methodology can be identified, connecting the research areas of product development and digital B2B platform business models. Therefore, this study conducted a bibliometric analysis of scientific data to identify a research gap and a qualitative literature review to affirm the relevance of future research in this research area. The results show a gap between the research areas of digital B2B platform business models and product development. Essentially, several renowned platform researchers suggested performing future research with a methodology that fulfils the following purposes: (1) improve the general understanding of digital platforms, (2) understand their success factors and development, and (3) deal with challenges (e.g., monetization) and loss of valued personal relations in B2B markets through digitization.

Research in biologically-inspired design (BID) practice often focus on team composition or ideation based on an already discovered fascinating biological solution principle. However, how are the outcome of the early design phases affecting BID projects' quality?

In this study, historical data from 91 reports from student teams documenting their BID efforts from a 3-week course constitute the data source. Thus, the relationship between design problem types, function types, functions descriptions and BID projects' quality is addressed.

The study show that especially design problem types and function descriptions affect the BID projects' quality. For instance, BID projects dealing with open-ended problems yield better results than redesign problems with existing solutions operating in a very domain-limited solution space. Next, BID projects obtain the best results when using functions as drivers for analogy searching rather than properties. Finally, BID projects with certain function types seem to have more complicated conceptualization phases.

Product design is a key aspect of human intelligence and creativity, attracting not only experts but also workers and self-employed without any formal design training. Although numerous people in developing countries design and manufacture simple products in metalworking microenterprises, there is very little systematic knowledge about their design process. This paper aims to fill this gap in design knowledge. We aim at investigating some aspects of design process in the metalworking microenterprises in Tanzania. The findings reveal how they identify needs, and generate and evaluate concepts.

Water scarcity and resource depletion can be expected during the climate crisis. Therefore, thermally loaded processes in particular, must be made more efficient in the future. Heat exchangers will play a key role in this optimization process. More efficient designs allow a greater heat flow to be removed from processes while mass flows remain constant. In this context, the heat-transferring wall of heat exchangers is a focus of current research on the design of heat exchangers. The aim is to increase the heat-transferring surface of the wall as much as possible and to keep the design space as compact as possible. Therefore, this study investigates the suitability of the differential-growth method for generating complex heat-transferring walls for heat exchangers using CFD-analysis. Firstly, a framework for generating the wall structures and a computational model for predicting the design influence of such structures for the thermal and fluid-dynamic behavior of the heat exchanger are presented. Thereby, the potential of such wall structures is analyzed in this study. Furthermore, the study identified weaknesses of such walls designed with the differential-growth method, which should be the focus of future investigations.

The paper focuses on comparative experiment on manufacturing and inspection of two different prismatic one-off parts, which have different complexity. Our experiment shows that transforming product definition method from the Drawing Centric Definition (DCD) to the Model Centric Definition (MCD) enables 28%-29% time savings in manufacturing and inspection phases of machined one-off part's life cycle. Furthermore, transition from MCD to Model-Based Definition (MBD) enables 5%-9% time savings, respectively. Applying of MBD enables more time savings in complex part compared to a less complex part.

This article investigates human geometry in design, allowing exploration of unknown geometries in Paralympic sports equipment. By creating a configuration map exploring the solution-space, optimal sit-ski seating positions–in the sense of performance and ergonomics–can efficiently be found for individual athletes. A physical prototype was developed, and an experiment was designed to identify changes in performance due to different geometries. The design method and application make it possible to translate critical angles onto geometries, and test individuals for optimal work ergonomics.