Future scenarios are intermediary artefacts for mid- and long-term design of complex solutions, e.g., to improve urban mobility systems. They allow designers to explore possible alternatives and incorporate uncertainty in the process. While their making is widely studied and implemented in scenario planning, their assessment got little attention. To find out which characteristics of scenarios we can assess, we conducted interviews and an expert workshop. This results in a scenario assessment framework of 3 levels: Assessment of system impact, evaluation of impact on practitioners and quality assurance. We focus on the latter as it represents the key gap and established a checklist for it. We distinguish between the level of engagement, i.e., scenario makers and users who adapt existing sets (or archetypes). Finally, we provide a checklist to aid ensuring that when choosing existing scenario sets, key criteria are fulfilled. This shall enable designers to better integrate scenarios in their workflows. We provide examples of designing mobility solutions. Yet, the findings can be applied to all disciplines where scenarios can aid design processes but are so far limited due to the resources needed for creating meaningful scenarios.

The well-thought implementation of technology within the product-service system (PSS) will undoubtedly contribute to the increase of healthy life expectancy and to the improvement of the wellbeing of society. The ‘Exercise-Well’ project, explored the problem and solution areas related to home-based exercise through digital interventions. Students worked in pairs and expected to propose a PSS solution providing a type of sports/physical activities for individuals to support their wellbeing. The proposed solutions were encouraged to create positive change especially through the integration of self-determination theory (SDT), but also be functionality suited to the persona. The project had the goals of directing students: i) to learn how digital technologies can be best tailored to assist people to exercise; ii) to consider engineering and healthcare domain constraints for utilizing convenient technological methods and integrating relevant hardware and software components; and iii) to motivate people by integrating autonomy, competence, relatedness into their design proposals. The paper demonstrated how SDT can be integrated into the design process, and how home-based digital exercise interventions can lead to creative solutions.

While the causes of failures in complex engineered systems are often clear in hindsight, it can be challenging to predict failures proactively during the design of novel engineered products or systems. Identifying patterns can be useful for capturing common characteristics that may lead to failure. In this paper, we present a methodology for identifying patterns of failure from NASA's publicly available Lessons Learned Information System (LLIS). We apply an ontology development and clustering approach to identify representative patterns leading to failures in historical lessons learned. A joint inductive-deductive approach reveals the key themes in lessons that lead to failure, which are formalized and recorded as an ontology of complex systems failure causes. Documents from the LLIS are manually tagged with relevant characteristics from the ontology. From the tagged set, clustering is used to capture co-occurring sets of characteristics that lead to failure. The primary contribution of this work is a method for extracting a set of generic failure patterns in complex engineered systems and characteristics for these patterns that can be identified at design time, knowledge of which can be used to plan mitigation strategies.

People living with tetraplegia experience a significant loss of sensory and motor function; with the severity depending on their injury level and completeness. To complete tasks independently, people with tetraplegia often rely on assistive devices. To avoid upper extremity pain, designs should not require applications of force near the limits of the user's physical strength. This paper establishes a 2D biomechanical model using static equilibrium and joint torque limits to predict multidirectional strength patterns in the sagittal plane for people with C5 to C7 tetraplegia in a seated position. The results from the biomechanical model highlight the areas and directions of high strength. The strength patterns observed in this paper provide an opportunity for designers to evaluate strength requirements and take advantage of areas and directions of high strength and ensure that users are not required to apply force near their physical limit. In doing this, designs such as assistive devices can be developed that enable users with a reduction in strength to operate them independently.

Approximately 10% of hospitalized patients develops decubitus ulcers that quickly degenerates into chronic illness that reduces the quality of life and requires expensive clinical management. The use of an anti-decubitus active mattress, that automatically redistributes the pressure loads, reduces the occurrence of new lesions and promotes the healing of the pre-existing ones.

The aim of this work is to design and develop two tools to support the design of an anti-decubitus active mattress. Almost all the systems found in literature are based on the classification of pressure maps through machine learning and are difficultly usable in the design context.

This work proposes a pressure map Classifier and an Interactive Simulator of the mattress, based on a simpler logic, by integrating image processing techniques and functioning simulations. The Classifier can recognize the patient's pressure maps and classify them according to six reference sleep postures. The Interactive Simulator allows to understand the operating mechanisms of the mattress and to test the controller and the various control logics in the absence of a physical prototype.

Conceptual design synthesis, which focuses on generating solution alternatives, has a significant impact on the cost and quality of the final product. The development of radically new and significantly better solutions requires the generation and exploration of a large solution space. This work deals with the conceptual design synthesis of multi-state mechanical devices (MSMD). A scheme for representing a MSMD design task is described. Empirical studies have been carried out to develop a common understanding of the MSMD design synthesis process and use this knowledge for developing a prescriptive model. In order to support the effective and efficient use of the proposed prescriptive model, a web-based computational tool is developed.

Interest in applying a “lean” philosophy to design has been slowly growing in recent years, but there are still few broadly applicable methodologies and illustrative cases published in the literature to guide lean design processes. Lean approaches promise cost reduction and increased product value, which could be particularly beneficial in product development for low- and middle-income country markets, where value demands are high. We use the clinical need of efficient diabetic foot risk assessment in lowresource healthcare settings to present an example of lean early-stage design of a medical device. The background of existing medical literature and commercial products is intentionally leveraged throughout the design process to streamline development and minimize the need for independent validation of product strategies and design features. Our approach resulted in an efficient design process that generated a novel, purely mechanical plantar pressure evaluation device that can indicate high risk of diabetic foot ulcer in resource-constrained settings. This case provides a practical example of how design processes can be adapted to be leaner where there are large gains from minimizing design cycle time and cost.

The increasing importance of software as an essential functional provider in products and processes requires that companies master the development capabilities to continiously and quickly deliver high-quality software features. DevOps (acronym for Development and Operations) is an essential approach to these capabilities, which has so far been used predominantly in software-driven companies. This paper investigates the conditions under which DevOps can also be used in the industrial context of series manufacturing in order to be able to steadily develop and provide software features used in these environments (e.g. for monitoring and maintenance of manufacturing machines). A concept for DevOps for manufacturing systems was developed based on current best practices and the specific situation in the industrial company. The concept was then implemented and validated with experts on the basis of initial development cycles, demonstrating the usefulness of DevOps for manufacturing systems.

The selection of an analogical source is a critical step in the design-by-analogy process. Previous researchers have explored the reasons and preferences of individual designers or design teams in selecting analogical sources. Non-designers, who instead have more knowledge of other fields, may offer new possibilities for retrieving novel analogical sources. This study focuses on differences in the selection of analogical sources between collaborative design teams composed of designers and nondesigners. There are indeed significant differences in the selection of the source type, the reasons for selecting the source, the level of abstraction in inspiration stimuli, and the novelty of design ideas between designers and non-designers. This work may provide theoretical guidance for the development of collaborative design tools and methods for teams composed of designers and non-designers with different knowledge bases.

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.

In order to better understand the stakeholder choices of knowledge-based organisational actors, this study focuses on a novel application of Huber's (2012) dimensions of proximity salience, namely spatial proximity, social proximity and cognitive proximity. The population of the study is made up of knowledge-based organisational actors involved in developing an innovation ecosystem, in terms of stakeholder network creation. The extent to which the three proximity dimensions of stakeholder salience is evident in the stakeholder choices of these innovation-focused actors seeking knowledge-based collaborators is explored. Our findings show how various forms of proximity prompt the decision of who to work with among a diverse population of experts involved in building a cross-national innovation ecosystem. The various explanations that motivate stakeholder choice matched Huber's proximity dimensions. The findings provide new insight into stakeholder choice among knowledge-based organisations, and highlight a new proximity dimension indirectly linked to cognition proximity. Termed the “potential proximity” dimension, it involves attraction to stakeholders that represent strategic value.

The extension of the product lifecycle is crucial in the application of Circular Economy principles. However, when Energy Related Products are concerned, managing a durable product does not necessarily mean dealing with sustainable products. This happens because components and/or materials are affected by aging and lead to increased requirement of resources to run (i.e. electricity); there are certain trends that, although distinct from the previous facts, balance the effects of aging, i.e. energy grid mix decarbonization. In the present work an approach that considers both the economic and environmental consequences of durable products is proposed. The Durabot tool has been developed to accomplish the environmental analysis. The work overcomes the main literature criticalities: enables the assessment of environmental consequences of durability ; the evolution of energy grid mix is introduced; the environmental consequences of durable products in different lifecycle scenarios can be assessed during the design phase; therefore, the components to substitute and to make accessible are identified. The tool is intended to be used aiming at design for product lifecycle extension, maintaining both economic and environmental convenience

Research and Technology Organisations (RTOs) develop and transfer new technologies to industry. Considering environnemental and social challenges in their activities is becoming more and more important. Integrating these challenges within an organization requires a global and coherent method, but also flexibility to adapt to the various activities of the organisationz. Eco-innovation is an approach that can meet these goals. However, literature has already shown that the main obstacles for the integration of eco-innovation come from the lack of global approaches adapted to companies' practices. In this paper, we characterise the specific activities of RTOs. Then, we specified the need for an eco innovation approach for RTOs. We carried out a functional analysis to formalise the need and identify the main functions that the eco-innovation approach must fulfil. We conducted exploratory interviews with various stakholders from an RTO in order to validate the identified needs and functions.

This paper presents an EEG (Electroencephalography) study that explores the correlation between the EEG variation across design stages and the quality of the design outcomes. The brain activations of 33 volunteers with engineering backgrounds were recorded while performing a design task using a morphological table to develop an amphibious bike. The EEG variations from the analysing/selecting stage to the illustrating stage were analysed based on the EEG frequency band and channel sets. A significant correlation between the detail level of the design outcome and the power variation mode was observed in theta, alpha and gamma bands, each involving different channel sets. Compared to the assessment results from two evaluators, using EEG variations as a proxy of the detail level of the design outcome could reach a maximum accuracy of 0.727, precision of 0.765, and recall of 0.889. These results also provide suggestions on the selection of the frequency bands and channel sets to achieve better prediction performance according to each metric.

As an initial step towards a better understanding of cognitive load in computer-aided design (CAD), the herein presented study investigated cognitive load imposed on 24 mechanical engineers during two CAD modelling tasks of intentionally different complexity levels. The cognitive load has been rarely studied in the CAD context, which resulted in the lack of understanding if and how the EEG-based indicators available from the literature reflect the changes in cognitive load imposed on engineering designers in CAD activities. Therefore, cognitive load was measured and analysed using three EEG-based indicators to explore insights that might be obtained from them. The initial analysis revealed different cognitive load results from the employed indicators for the same EEG data. In addition, the study implies that the cognitive load results obtained through the used indicators are only partially coherent with the CAD modelling task complexity. Hence, the results imply that the chosen EEG-based indicator matters when measuring and analysing cognitive load in CAD modelling tasks and that its adjustment for CAD context might be needed.

Industry 4.0 introduces innovative ways of professional training thanks to new technologies such as Virtual Reality and Augmented Reality. Despite improvements, there's still a lack of a good user experience and connection between user needs and these applications. To tackle this problem, designers of such applications must work in a collaborative way integrating final users. It's specifically true during design phases such as scenario creation. But the co-creation of scenario is a difficult task for designers and final users who don't have enough expertise with IT. A solution seems to stand in intermediary objects (IOs) which are well known for their characteristics of mediation, transformation, and representation. We have studied the use of different IOs during a project consisting in designing an immersive professional training application for risk hunting for Stäubli company. We used an IO1 made of an excel sheet and an IO2 made of 360 views of the workshop. Two ideation sessions with two groups of designers were conducted to propose a scenario consisting of several risks to spot in the future application. Results show that the scenario was improved using the IO2, and final users and designers were more collaborative.

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.

The study presented in this paper investigated the impact of embodied and self-reflected virtual reality (VR) experiences on engineering design students' cognition and perception of nature-relatedness during the early conceptual design phase. Results showed that students who explored the design environment as a bird (embodied) or human (self) avatar were significantly more likely to explore a larger design space indicated by more semantically unique design concepts compared to students without the VR experience. Network graphs of the syntactic connection of design concepts revealed notable differences among the three groups. The bird avatar group showed more connections to nature-related and social concepts, while more technical concepts were central for the human avatar group, and concepts about money were more central to the control group. Finally, students who embodied the bird avatar had a significantly stronger perception of connection to nature compared to the human avatar and control group, with a small to medium effect size. The results suggest that embodied (as a bird) and self-reflected (as a human) VR experiences can enhance engineering students' design thinking and perception of connection to nature.

In recent years, the use of virtual reality (VR) has been a promising opportunity to improve the immersive experience in virtual environments. In this study, we explore the effectiveness of immersive VR experiences on an individual's creativity. To do this, we first identified the characteristics of VR that are closely related to creative performance. Considering these factors, we designed and implemented the interaction method and the three outdoor and indoor virtual environments (Wilderness, City Park, and Office). We evaluated the effectiveness of the virtual environments with 12 participants. The user study results show that outdoor and indoor immersive virtual experiences improved their creativity skills. We concluded by analysing how factors such as simulator sickness and perceived workload influence creativity levels. Moreover, our study showed the potentiality of using immersive virtual environments to enhance individuals’ creative performance.

Currently, engineers need to manually analyse requirement specifications for determining parameters to create geometries in generative engineering. This analysis is time-consuming, error-prone and causes high costs. Generative engineering tools (e.g. Synera) cannot interpret natural language requirements directly. The requirements need to be formalised in a machine-readable format. AI algorithms have the potential to automatically transform natural language requirements into such a formal, machine-readable representation. In this work, a method for formalising requirements for generative engineering is developed and implemented as a prototype in Python. The method is validated in a case example using three products of an automotive engineering service provider. Requirements to be formalised are identified in the specifications of these three products, which are used as a test set to evaluate the performance of the method. The results show that requirements for generative engineering are formalised with high performance (F1 of 86.55 %). By applying the method, efforts and therefore costs for manually analysing requirements regarding parameters for generative engineering are reduced.