In order to operate in line with the circular economy (CE) concept, companies and other stakeholders need to work together to enable the circulation and cascading of resources. Although the need for proactive stakeholder management is a common theme in recent work on CE, little work has been dedicated to creating prescriptive methods for the co-design of CE value chains (CEVCs) focusing on selecting strategic partners, when to engage them and in what capacity. Following calls to connect the emerging CE literature with literature from existing bodies of knowledge, this paper explores the theoretical foundations of a CEVCs co-design method. Specifically, this paper explores resource-base view (RBV); resource dependency theory (RDT); and actor-network theory (ANT), and synthesises an outline for the co-design process of CEVCs. Reflections on the process link it to the extant co-design literature and explain how the process can be used for method and tool development.

One of the arguments against an increased use of repair is that, due to the constantly growing progress, an often already outdated component would be restored. However, refurbishment also allows a component to be modified in order to upgrade it to the state of the art or to adapt it to changed requirements. Many existing approaches regarding Design for Upgradeability are based on a modular product architecture. In these approaches, however, only the upgradeability of a product is considered through the exchange of components. Nevertheless, the exchange and improvement of individual component regions within a refurbishment has already been successfully carried out using additive processes. In this paper, a general method is presented to support the reengineering process, which is necessary to refurbish and upgrade a damaged component. In order to identify which areas can be replaced in the closed system of a component, the systematics of the modular product architecture are used. This allows dependencies between functions and component regions to be identified. Thus, it possible to determine which functions can be integrated into the intended component.

Extending the lifespan of products and parts is seen as a solution in the transition towards a circular economy. There are many proposed design approaches argued to facilitate this. However, extending the lifespan of products and parts is not always desirable, and product developers should instead strive to design for a specific longevity; the product's optimal lifetime. The latter in turn depends on many various contextual factors, and this paper has identified the three main contextual factors as; the user, the business, and the resource efficiency. Considering these three appropriately can help product developers to define their product's optimal lifetime. Altogether, these components promote the mindset of Design for Longevity. Specifically, as extracted from this paper: “Design for Longevity aims at designing products with an optimal lifetime, where optimal means taking the user, the business and the resource efficiency perspectives into account when designing the life of a product”. A Design for Longevity framework is proposed and evaluated in this paper, and it is concluded that the proposed Design for Longevity framework can support product developers to implement the Design for Longevity mindset.

The act of prototyping is a key element of the design process. However, capturing information on how prototypes evolve and influence one another is a complex problem. This paper presents an iterative evolution to a prototyping capture platform, termed Pro2Booth, designed to address the shortcomings encountered in previous systems. The Pro2Booth hardware and online software described in this paper provide a new baseline for future innovation and exploration of the prototype capture process.

Customer centricity is described as placing value creation for customers at the core of business decisions and organizational practices and is progressively regarded as a foundation of sustainable competitive advantage by companies. Hence in recent years, there is a shift from companies being product-centric to them adapting customer-centric practices as a practice to create balanced and sustainable businesses. Although there are several methods and processes that can help companies become customer-centric; Design Thinking (DT) is championed by many practitioners and academics alike as being effective in introducing customer-centricity in organizations. Despite being a highly researched topic in the last decade, the bulk of the research is focused on success stories or one-off cases of using design thinking in Business to Customer (B2C) environments. This paper is based on a qualitative study performed at a high-tech Swedish electronics company and focuses on highlighting the barriers and opportunities of adapting DT in Business to Business (B2B) companies with established product development processes. The barriers we identified can help companies to address the impediments and will make the DT implementation easier for companies

Integrated Natural Resource and Conservation Development (INRCD) Projects is an umbrella term for a variety of Integrated Conservation and Development Projects (ICDPs), a concept first introduced by the World Wide Fund for Nature in the mid 1980s to target practice-oriented efforts in developing countries; and Integrated Natural Resource Management (INRM) research and development projects introduced as adaptive management for fisheries, wildlife, forest, and rangeland to target analysis-oriented efforts in developing and developed countries. Both efforts seek to balance economic development and natural resource conservation. This paper reviews the literature over the past four decades in an attempt to determine which planning and execution methods lead to greater success. A thematic analysis revealed three broad areas of importance: community inclusion and income diversification, inadequate training and management, and inability to properly quantify data. A systems design optimization approach for such projects is advocated to support project decision making in these areas of importance.

Systems engineering and design thinking have been widely seen as distinctly different processes, systems engineering being more data-driven and analytical, and design thinking being more human- centred and creative. We use the term ‘design thinking’ to encompass the plurality of human-centered design processes that seek to unpack the core values behind design decisions. With the increased awareness that both systems engineering and design thinking need each other, the effects of a possibly persisting distinction on engineers’ attitudes toward these two processes are not well understood. In this paper, we describe the development and validation of a scale for measuring individual attitudes about systems engineering and design thinking. Thematic analysis of engineering and design literature is used to derive a Likert scale reflecting these attitudes. We use exploratory and confirmatory factor analysis to test and confirm this two-factor thematic representation, resulting in a 9-item Systems Engineering and Design Thinking Scale measure of attitudes.

Developments in artificial intelligence (AI) are opening the possibilities for the development of more advanced design tools. An example of these innovations are generative design tools, in which the generation of complex and high performing products is possible. This study investigates the use of generative design tools and how they may influence the design process and designer behaviour. Six interviews of interdisciplinary designers were conducted to understand the implications of using generative design tools. It was observed that generative design tools primarily allow for quantitative inputs to the tool while qualitative metrics, such as aesthetics, are considered indirectly by designers. The subjectivity of the designer and how they incorporate the quantitative and qualitative metrics in the generative design tool can lead to differing outcomes between designers. Notable differences in tool usage are also observed between expert and novice computational designers. Additional studies should be conducted to further understand the extent generative design tools impact the design process, designer behaviour, and design outcomes.

Engineering changes (ECs) and engineering change management (ECM) are crucial for successful product design processes (PDP). Due to the increasing complexity of today's products (like vehicles) and the interaction of different engineering domains (mechanics, electric/electronics, software) involved in the PDP, cross-domain EC impact assessments as well as processes are required. To better support engineers in assessing change propagation across domains and products, existing approaches for ECM product models are analyzed in this paper and an enhanced product model is derived using MBSE.

The aim of our research is to stimulate cross disciplinary design collaboration to improve innovation processes in product and service design domain. We focus on the intersection of biotechnology and design as this field poses great challenges and opportunities for innovation, and it has received little attention in light of technological advancements of digital goods over the past decades. Experimental studies in the area expose challenging interactions, rising from lack of common vocabulary and preconceptions. Organisational management studies suggest that creativity is a prerequisite for innovation in group processes. As such, we are interested in enhancing collective creativity. Numerous studies investigate external creativity triggers, however only on individual level. Our review suggests that external triggers can be effective when the task is problem solving or styling, but ambiguous goals like innovation require stimulation of intrinsic triggers, such as group incidental learning and tacit knowledge. To explain this, we propose a hypothetical innovation approach, that draws attention to cognitive stimulation methods leading to creativity in multidisciplinary teams.

The topic of support structure design in the Design for Additive Manufacturing (DfAM) field is not addressed with the same relevance as the topic of part design. Therefore, this contribution investigates parameters for both the manufacturing and support structure design for the Laser Powder Bed Fusion (L-PBF) process. Matrices for cause-effect-relations of manufacturing and design parameters on build properties as well as correlations of them are presented. Based on these, recommendations for actions for experimental procedures are derived following the Design of Experiments method.

Augmented Reality (AR) is to be used extensively in today's digitized teaching in order to enable students to a more efficient learning. However, teaching content must not be only digitised, but must be communicated in a meaningful way. For this purpose, a generally valid flowchart has been developed, that allows lectures to choose the right content for AR experiences. In order to create this flowchart, empirical values from test runs were combined with pedagogically proven empirical values for good teaching.

Many companies face a challenge while defining their individualized digitalization strategy. Therefore, the interrelation of corporate and digitalization strategy is addressed and a novel procedure model to assist companies in defining their strategy is introduced. Based on their corporate strategy, the introduced model allows companies to simply identify suitable business model patterns, digitization use cases and offers a possibility to asses the maturity level of their internal processes and evaluate the added value from an economic point of view.

Model-Based Systems Engineering (MBSE) is an efficient approach to support product development in order to meet today's challenges. The MBSE approach includes methods and, above all, modelling approaches of the technical system with the aim of continuous use in development. The objective of this paper is to use the potential of the MBSE models and to show the added value of such models on the system level when used as a single source. With this objective, this paper presents a three-step approach to systematically identify and apply meaningful modelling approaches within MBSE, based on the needs during the development process. Furthermore, an FMEA example is included in this paper to elaborate the use of MBSE in the system failure analysis.

We present results from an EEG experiment EEG to measure neurophysiological activation to study novice and experienced designers when designing and problem-solving. We adopted and extended the tasks described in a previous fMRI study. The block experiment consists of 3 tasks: problem-solving, basic design, and open layout design. The block is preceded by a familiarizing pre-task and extended to an open design sketching task. Results from 36 sessions of mechanical engineers and industrial designers indicate significant differences in activations between the problem-solving and the design tasks.

Designing accessible and inclusive buildings is essential if they are to provide enjoyable and inspiring experiences for all their occupants. Research revealed that many architectural design professionals perceive a lack of awareness of the aspects to consider when designing to be a limiting factor in the uptake of Inclusive Design. By involving expert stakeholders this study provides evidence for the demand to create an Inclusive Design Canvas, a strategic design template offering an educational springboard for building industry professionals to embed Inclusive Design in the design process.

This paper presents experience-oriented aspects of the development of wearable assistive devices (exoskeletons) for industrial purposes, an area which has only begun to be explored. Our research aims to examine user acceptance criteria for assistive devices and understand the meaning of interaction with wearable assistive devices for the users. The resulting models deliver new insights about the importance of user experience for technology acceptance and should be generally considered in development processes of wearable assistive devices.

Complex new functionalities and dissimilar stakeholder groups pose challenges to the requirement analysis for driverless vehicles. To overcome these challenges, we propose a value-oriented reference process for innovative functionalities of an autonomous family vehicle. The value-oriented measures are taken from the approach of Value Sensitive Design. In our application, we have found that the consideration of the human values involved is of great importance for the identification of stakeholders and the management of their potentially conflicting interests throughout the development process.

This work aims to test Prosperity Thinking methodology in Action and assess whether this method would respond to the needs of designers, innovators, and change-makers that are willing to change the food system. Starting from the evolution of marketing design to human-centered design, we illustrate the importance of taking into account the planet's means in the design for Sustainability at the system level. We approached the problem starting from practice, with an Action Research Innovation Management Framework (Guertler, Kriz, and Sick, 2020). Results show that designers, innovators, and changemakers have an interest in a methodology that helps them to analyze and solve systemic challenges linking the micro (human) and macro (planet) through a participatory approach to achieve long-term impact of the designed solutions.

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.