Breast cancer is one of the most common cancer types among women, accountable for approximately 2.2 million new cases and 684,996 deaths globally in 2020. There are various screening methods to detect cancer early, and experts suggest that women should perform breast self-examination (BSE) once a month. Unfortunately, most women fail to do so even if they are aware of the risks and the importance of screening methods. The aim of this paper is to understand women's current behavior and experience with BSE and mobile BSE apps and to suggest several design dimensions for positive mobile BSE app experience by benefiting from positive technology. With this aim, three selected mobile BSE apps were used by a total of 24 participants for four weeks. A three-phase study was carried out to uncover women’s pre- during-, and post-usage experiences of BSE apps. The analysis revealed six headings under two themes: strategies, limitations, and emotions under BSE theme; and the needs, limitations, and benefits under Mobile Apps theme. Consequently, based on the findings, suggestions for design dimensions for BSE apps to better meet women’s needs by benefiting from levels of positive technology are made.

Artificial intelligence is transforming how we interact with vehicles. We examine the case of Maritime Autonomous Surface Ships (MASS), which are emerging as a safer and more effective solution for maritime transportation. Despite the focus on autonomy, humans are predicted to have a central role in MASS operations from a Shore Control Centre (SCC). Here, operators will provide back-up control in the event of system failure. There are signification design challenges with such a system. The most critical is human-system interaction in autonomy (H-SIA). We consider humans as the source of resilience in the system for adapting to unexpected events and managing safety. We ask, can Human-Centred Design (HCD) be used to create resilient interactions between MASS and SCC? Work has been done in resilience engineering for complex systems but has not been extended to H-SIA in transportation. “Resilient interaction design” is relevant as we progress from design to operational phase. We adopted the ISO 9421-210 guideline to structure our HCD approach. The result is an SCC designed for 1 Autonomy Operator (AO). The contribution is a demonstration of how resilient interaction design may lead to safer and more effective H-SIA in transportation.

Product-service/systems (PSS) have been projected to be a potential solution to address overconsumption and to enable an enhanced sustainability performance. However, PSS do not always live up to their potential benefits, due to unintended changes in consumer behaviour. This study aims at investigating existing methods and tools to develop sustainable behaviour within PSS, alongside potential barriers and success factors. Based on a systematic literature review, a total of 46 methods to achieve sustainable behaviour were collected and analysed, and further discussed on the basis of the identified success factors and barriers.

Engineers often need to discover and learn designs from unfamiliar domains for inspiration or other particular uses. However, the complexity of the technical design descriptions and the unfamiliarity to the domain make it hard for engineers to comprehend the function, behavior, and structure of a design. To help engineers quickly understand a complex technical design description new to them, one approach is to represent it as a network graph of the design-related entities and their relations as an abstract summary of the design. While graph or network visualizations are widely adopted in the engineering design literature, the challenge remains in retrieving the design entities and deriving their relations. In this paper, we propose a network mapping method that is powered by Technology Semantic Network (TechNet). Through a case study, we showcase how TechNet’s unique characteristic of being trained on a large technology-related data source advantages itself over common-sense knowledge bases, such as WordNet and ConceptNet, for design knowledge representation.

Progressive stamping tools are widely used in mass-production of sheet metal components and their performance is critical as the design of the tool impact the cost of the manufactured component significantly.

Knowledge reuse is an important part of successful design in general, and in progressive stamping tool design in particular. In the study described in this paper, 8 tool designers from 5 different Swedish companies were interviewed about (1) at what points in the tool design process they search for previously designed tools for information and knowledge reuse, (2) under what conditions and for what reasons does this reuse take place, and (3) what types of information and knowledge are sought for at each point. The results show that reuse of information and knowledge from previously designed tools happens in many parts of the tool design process. The reasons and conditions for reuse vary depending on where in the process the designer is. High component complexity is one example of a common factor triggering reuse. Also, information about the performance of the tool is important to tool designers, as they only want to reuse information and knowledge from tools with good performance and low maintenance.

In this paper the development process of a sensing rolling bearing is presented, from which finally design rules for sensing machine elements are derived. In the first step, the requirements of the users are determined. It turns out user of sensing machine elements want to continue to use the advantage of the standardized machine elements and costs should not be incurred by redesign or complex assembly. With these requirements the development of the sensing rolling bearing is started, in which the different presented technologies are reviewed for their suitability regarding the requirements. With the selected technology measuring the electric rolling bearing impedance to estimate rolling bearing loads, a first prototype is developed by creating a functional structure of the product and focusing on the partial solution of the most relevant partial functions. This prototype is then tested with regard to its functionality. Finally, generalizable design rules for sensing machine elements are derived from the development.

This article presents a design of an experiment for investigating the effect of changing the geometry of Paralympic alpine sit-ski poles/outriggers in the LW 10-12 class. An experiment design for mapping an individual athlete’s performance parameters has been developed, with a resolution for finding the optimal outrigger geometry. By prototyping an adjustable experiment setup with implemented sensor systems, the performance increase can be analysed and implemented in new equipment. Results show that changing double poling geometry provides a substantial performance increase, regarding time and propulsive force.

Using three projects as a showcase, the aim of this article is to report on design students’ take on co-design in health, in terms of both outcomes and processes. It builds on project work conducted in a master’s course called ‘Design for Society’, reserved for 4th-year industrial design students in the Department of Design at the Norwegian University of Science and Technology. The students were encouraged to explore how healthcare services could facilitate active, informed and involved patients. The overall theme was provided by a cluster funded by the Norwegian Research Council addressing co-creative service design and innovation in health. Based on initial research, the students, organised in groups, identified a chronic illness that has a lifelong impact on everyday life, such as cystic fibrosis, fibromyalgia, and Alzheimer’s disease. We give an account of three selected projects by showcasing developed concepts, central methods and tools, and we share key reflections from the students and the course educators on their experiences of working with co-design in health in an academic environment.

Massive data are surrounding us in our daily lives. Urban mobility generates a very high number of complex data reflecting the mobility of people, vehicles and objects. Transport operators are primary users who strive to discover the meaning of phenomena behind traffic data, aiming at regulation and transport planning. This paper tackles the question "How to design a supportive tool for visual exploration of digital mobility data to help a transport analyst in decision making?” The objective is to support an analyst to conduct an ex post analysis of train circulation and passenger flows, notably in disrupted situations. We propose a problem-solution process combined with data visualisation. It relies on the observation of operational agents, creativity sessions and the development of user scenarios. The process is illustrated for a case study on one of the commuter line of the Paris metropolitan area. Results encompass three different layers and multiple interlinked views to explore spatial patterns, spatio-temporal clusters and passenger flows. We join several transport network indicators whether are measured, forecasted, or estimated. A user scenario is developed to investigate disrupted situations in public transport.

The development of engineered systems is a complex process, involving many activities and development artifacts. The challenges introduced by this complexity calls for a model-based design environment. The PROVE methodology is an artifact-centric, model-based development process design methodology. In this paper, we present the first, fully model-based design environment of the PROVE. Furthermore, our environment incorporates additional process design perspectives that are applied in real-time and in a completely consistent manner, based on a formally defined information model. We discuss the details of our environment's design as well as highlight its potential benefits.

Remaining seated for extended periods increases the risk health issues and discomfort perception. Consequently, the seat-pan design is crucial and could be mainly influenced by two factors: pressure distribution and seat contour. For seat pan discomfort, the lower average pressure is accompanied by less discomfort. Moreover, a seat contour with a large contact area is correlated with more comfort. Thus, a shaped cushion had been accurately designed (Virtual Prototype) and realized (Physical Prototype) aiming to translate the pressure distribution due to interaction between seat and buttock in a geometric shape, suitable for the international population (including P5 females and P95 males). With this shape, the pressure should be more uniform and lower, the contact area at interface bigger, and the perceived comfort higher. Both Virtual and Physical Prototype design had been described in this paper through a repeatable and straightforward approach. Also, experiments had been performed to validate the hypothesis through a comparison with a standard flat cushion. Results showed the goal of the design had been reached: the shaped cushion scored less pressure distribution and higher contact area than the flat cushion.

During the cold season, the cold protective products are often short during evacuation life after a natural disaster. If evacuees can make and wear simple cold protective gears by using materials obtainable on site, it will reduce the burden on the evacuees in emergent situation. Therefore, we investigated the structure constructed by folding newsprint paper, which can improve the heat retention effect and be applied to various body shapes. Focusing on the glide reflection structure repeating a smaller chamber, the basic size was determined by experiments with reference to the accordion shape, and the experimental results indicated that the heat retention effect was significantly greater than that of a mere air layer and those of ordinary fabrics. Next, it was found that the apex angle of structure had no significant difference in the heat retention effect. Then, the dimensions of the structure were determined to maintain the air layer under the pressure of the clothes by simulation of structural analyses. Finally, we made a temporary cold protective gear that can practically cover the trunk of the body and found that the heat retention effect was significantly higher than that of unprocessed newsprint and that of accordion shape.

Developing appropriate assistive technology to be manufactured and maintained within the local context of a low-resource setting requires alternative design principles and designerly ways to those used when designing in, or for, more resourced regions of the world. This case study offers an empirical account of the design of SafariSeat, an all-terrain wheelchair which has been designed, tested, manufactured and turned into a sustainable enterprise in East Africa. The wheelchair was developed with intentions to reduce inequality and help alleviate poverty in low-resource communities by improving users' health, wellbeing and participation in society, whilst creating and facilitating local jobs to support communities. Having developed SafariSeat with a human-centred design approach, a local mindset, and prioritisation of usability and affordability, this case study is used to reflect on the applied design principles, practices and processes whilst providing contextual insights for other designers seeking to work in a similar way. The study discusses challenges encountered whilst designing in a low-resource setting, and highlights how local collaboration and partnerships can help lead to the creation of a more sustainable solution.

Trust is an important factor in building acceptance of autonomous vehicles within our society, but the complex nature of trust makes it challenging to design for an appropriate level of trust. This can lead to instances of mistrust and/or distrust between users and AV’s. Designing for calibrated trust is a possible option to address this challenge. Existing research on designing for calibrated trust focuses on the human machine interaction (HMI), while from literature we infer that trust creation beings much before the first interaction between a user and an AV. The goal of our research is to broaden the scope of calibrated trust, by exploring the pre-use phase and understand the challenges faced in calibration of trust. Within our study 16 mobility experts were interviewed and a thematic analysis of the interviews was conducted. The analysis revealed the lack of clear communication between stakeholders, a solutionism approach towards designing and lack of transparency in design as the prominent challenges. Building on the research insights, we briefly introduce the Calibrated Trust Toolkit as our design solution, and conclude by proposing a sweet spot for achieving calibration of trust between users and autonomous vehicles.

Engineering designers seek to explore ‘real’ problems that must be solved across design processes. This exploration might be challenging in complex problem situations. An effective way of encouraging design exploration is conjecture-based problem exploration—informing problem re-interpretation by potential solutions. However, little evidence indicated how this process unfolds, especially in complex problem situations. This study addresses this question by articulating the underlying cognitive mechanism of conjecture-based problem exploration. Situated in a creative design practice that tackles real-world, complex problem situations, we employ grounded theory to conduct qualitative coding of interview transcripts and documents elicited from ten multidisciplinary graduate students. We developed a three-phase process model to explain conjecture-based problem exploration: (1) triggering through analogizing, inspiring, evaluating, and questioning; (2) transitioning to problem space expansion; and (3) resulting in problem focus adjustment incrementally or radically. Our explanation contributes to design theory building and encourages engineering designers to embrace a dynamic view of design problems when addressing complexity.

The earliest stage in the innovation lifecycle, problem formulation, is crucial for setting direction in an innovation effort. When faced with an interesting problem, engineers commonly assume the approximate solution area and focus on ideating innovative solutions. However, in this project, NASA and their contracted partner, Accenture, collaboratively conducted problem discovery to ensure that solutioning efforts were focused on the right problems, for the right users, and addressing the most critical needs—in this case, exploring weather tolerant operations (WTO) to further urban air mobility (UAM) – known as UAM WTO. The project team leveraged generative, qualitative methods to understand the ecosystem, players, and where challenges in the industry are inhibiting development. The complexity of the problem area required that the team constantly observe and iterate on problem discovery, effectively “designing the design process.” This paper discusses the approach, methodologies, and selected results, including significant insights on the application of early-stage design methodologies to a complex, system-level problem.

The representation of the product use context is a well established design practice in Engineering Design. Recently, design theory is studying the product interaction involving several cognitive aspects such as the possible conditions in which a wrong interaction occurs. The aim of this paper is to find a quantitative evidence of the causes of these misuses. In particular, this study focuses on the detection of bad design and biases.

In this paper, we propose a method that helps to the automatic detection of bad design and biases from patents. The method is based on an approach that defines syntactic rules to detect sentences containing these artifacts. These rules are defined based on an exploratory analysis of the explicit mention of “bad design” and “bias” and then, tested with multiple experiments on a sample of patents. The results give a first quantitative evidence of the presence of bad design and biases in patents and consequently of their importance in the design theory. In particular, it is provided a fine grain analysis of the linguistic structure of sentences containing these artifacts helping designers in detecting automatically them from patents.

Data-driven methods from the field of Artificial Intelligence or Machine Learning are increasingly applied in mechanical engineering. This refers to the development of digital engineering in recent years, which aims to bring these methods into practice in order to realize cost and time savings. However, a necessary step towards the implementation of such methods is the utilization of existing data. This problem is essential because the mere availability of data does not automatically imply data usability. Therefore, this paper presents a method to automatically recognize symbols from principle sketches, which allows the generation of training data for machine learning algorithms. In this approach, the symbols are created randomly and their illustration varies with each generation. . A deep learning network from the field of computer vision is used to test the generated data set and thus to recognize symbols on principle sketches. This type of drawing is especially interesting because the cost-saving potential is very high due to the application in the early phases of the product development process.

Engineering Digitalization enables development of new high intelligent products containing mechanical, electrical, software and communication components. As these complex products are result of multidisciplinary engineering processes, digitalization also enforces companies to raise, adapt and revise their engineering competencies and process capabilities to increase agility and maintain competitiveness. Also, the growing amount of data related to product and processes requires a well-structured management concept. In order to encounter all these changes and new requirements companies should identify their specific strengths and weaknesses and derive needs for action. This paper presents a novel maturity model for evaluation of capabilities of Engineering Digitalization in areas of processes, products, services, data, human and organization. The maturity model enables the detection of enhancement potentials and conception of individual digitalization plans for production companies. It has been composed based on a proven multidisciplinary engineering methodology along the product lifecycle process, which includes Model Based Systems Engineering Methods, and a multilevel IT architecture integration concept.

Digital inclusion is becoming more important as many consumer products and engineered systems adopt increasingly digital interfaces. The designers of such services often assume that users have a certain level of digital interface competence, but this is not the case for many users. In this paper, we present a set of personas that could help designers to better understand and consider the range of digital expertise across the population. The personas are based on survey data from 338 people across England and Wales in 2019. The survey examined various factors that affect ability to use digital interfaces, including technology experience, attitudes towards technology and competence with basic interface operations. Twelve clusters were identified using K-means cluster analysis, and twelve personas were developed based on these. The personas help to bring to life the range of digital expertise and highlight people at risk of digital exclusion. In addition, the cluster sizes indicate the proportion of the population represented by each persona and thus the scale of potential digital exclusion.