Due to the high freedom of design, additive manufacturing (AM) is increasingly substituting conventional manufacturing technology in several sectors. However, the knowledge and the awareness for the suitable design of additively manufactured components or assemblies ensuring manufacturability and fully realizing its potential is still lacking. In recent years, approaches and tools have emerged that allow the incorporation of existing knowledge of Design for Additive Manufacturing (DfAM) into the design process. Nevertheless, these applications mostly do not consider the formalisation of both restrictive and opportunistic DfAM guidelines for their integration in design tools.

Therefore, the following article presents a framework for the knowledge-driven adaptation of existing designs in the context of DfAM within an expert system. The novelty of the presented approach lies in the interdisciplinarity between the formalization of design guidelines and their integration and consideration within computeraided design for the semi-automated adaptation of functional non-assembly mechanisms. The application of the presented framework to a case study manufactured via Fused Layer Modeling (FLM) illustrates the applicability and benefits.

Manufacturing companies are urged to take responsibility for their impacts on the environment and on society, to contribute to a more sustainable development. The concept of Corporate Social Responsibility (CSR) has therefore gained a lot of interest in the last decades. The Product Development Process (PDP) is a key activity in the operationalization of CSR in a company. However, little is known about the capabilities needed for companies to integrate and manage their CSR issues in their PDP. Therefore, this article aims at contributing to (1) identifying the capabilities to integrate and manage the CSR issues during the PDP, and (2) providing a maturity model to assess the level of capabilities for the integration of the CSR issues in the PDP. Insofar as CSR aims at contributing to sustainable development, the existing literature on capabilities for integrating sustainability in the PDP has been studied and taken as a basis to identify the capabilities for integrating and managing CSR in the PDP. A maturity model has then been built based on these capabilities. This contribution lays the foundation for a methodology to support companies in the improvement of their maturity level in terms of CSR-PDP interaction.

This research investigates changes in team behavior and communication through interruptions and gestures, due to design process strategies in pre-formed remote teams for conceptual design tasks. Understanding creative remote team behavior is important due to the increase of remote communication in knowledge work. Teams were given a creative or analytical condition intervention to facilitate their conceptual design team process. The research contributes to the human-computing interaction literature by characterizing changes in distributed team behavior due to process method interventions. The creative condition exhibited a decrease in interruptions. The analytical condition exhibited a decrease in gestures and an increase in problem characterization at the cost of ideation discussion. Remote team members can better gauge which meetings or work tasks are best to be done in person or remotely by gauging not just the task but also the team behavior.

Conflict can be both a productive and detrimental reality of design collaboration. While most studies on conflict characterize findings by type (conflict about the task, process, or interpersonal relationships), we extend this typology to understand the causes, topics, and outcomes of conflict. To do so, we analyze communications in a virtual chat platform, collected in a hybrid work environment. A thematic analysis on over 6000 messages between student design teams on the enterprise communication platform Slack revealed three emergent conflict themes: Engineering Design, Project Management, and Communication. A mapping of the themes to a widely-cited typology of conflict found an over- representation of task (productive) and process (detrimental) conflict in the Engineering Design and Project Management themes, respectively. The distribution of types of conflict in the Communication theme is representative of the entire dataset, suggesting that communication can be a cause and outcome in all types of conflict. Overall, our classification of conflict is the first step towards describing triads of the causes, topics, and outcomes of conflict, a contribution which will drive the development of interventions for design team conflict.

To help industries in their sustainable and circular transition from internal combustion engine production to electric motor production, the deployment of (i) a sound environmental impact assessment methodology, such as life cycle analysis, coupled with (ii) Design for Re-X tools, such as circularity indicators, is instrumental. To demonstrate the industrial relevance and complementary of both approaches, two consecutive workshops are conducted with a major original equipment manufacturer of recreational boats and their associated engines. On this basis, two circularity indicator-based tools were used to quantify and enhance (i) the circularity potential of the electric outboard as a whole, and (ii) the circularity performance of the two most impactful components, based on the LCA results: the electric motor unit and the lithium-ion battery pack. In all, the practice sessions supported the generation of strategic and operational ideas to improve the circularity of the electric outboard. As the industrial participants found both frameworks easy to use and efficient, all the details and resources used to conduct, replicate, or adapt such workshops in other industrial contexts are shared.

Due to an expanding number of mechatronic functionalities in modern technical products, the proportion of software and electronic components is also increasing. As a result, the products are developed by different engineering domains in complex development processes. To handle the growing complexity, Systems Engineering (SE) is increasingly important for development organizations of enterprises. System Engineering (SE) is understood as an approach to network the individual engineering domains and shall lead to a collaborative development of complex systems. Model-Based System Engineering (MBSE) expands SE by using common models and software tools to describe und visualize the systems. However, MBSE is not widely established in enterprises today. On the one hand, the introduction requires a distinct and consistent system understanding and collaborative way of working. On the other hand, the application of the existing tools requires extensive tool competencies due to many possible functions and features. Therefore, this paper presents a concept and a software based tool for a lean implementation of SE/MBSE to support the collaborative development of complex technical systems in small and medium-sized enterprieses.

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.

Designers are experiencing greater mental demands given the complexity of design tools, necessitating the study of cognitive load in design. Researchers have identified task- and designer-related factors that affect cognitive load; however, these studies primarily use self-reported measures that could be inaccurate and incomplete. Little research has tested the accuracy and completeness of self-reported measures and we aim to explore this gap. Towards this aim, we seek to answer the question: How does cognitive load vary based on the different design representations used, and do these differences depend on the measure of cognitive load? From our results, we see that the design representations vary in the range of cognitive load experienced by designers when using them. Moreover, this role of the range of cognitive load variance was observed given our use of pupil diameter. These findings call for the use of a multi-modal approach for measuring cognitive load with the combined use of subjective (e.g., self-report) and objective measures (e.g., physiological measures), as well as the use of both retrospective (e.g., self-report) and concurrent measures (e.g., physiological measures).

Machine learning (ML) is a well-established research topic in Industry 4.0 is boosting its adoption. ML is also used for manufacturing cost estimation during design. Such approaches are commonly used to estimate the cost of mass-produced parts. Many consolidated historical data are available for training the regression models. Unfortunately, very often, such a database of data is not available.

The paper defines an ML approach for parametric cost estimation of axisymmetric components. The data for training the ML model derives from automatic software for analytically estimating the manufacturing cost. With a proper set of simulations, the tool can generate a large amount of data for training. The paper presents the steps for developing a parametric cost model using ML. The approach is based on CRoss Industry Standard Process for Data Mining method. The proposed method was used to develop one cost model (to estimate the total cost that considered raw material and manufacturing cost). The obtained Relative Error is 23.52% ± 1.37%, coherent with E2516 − 11, Standard Classification for Cost Estimate Classification System.

The Agenda 2030 calls for collective awareness, starting with individuals. The interaction between users and household appliances produces a relevant amount of data that can be elaborated through Machine Learning algorithms to guide users towards sustainable behaviours. In particular, the data already available on household appliances can be conveniently used to create Virtual Sensors, increasing the overall information about the system. This paper focuses on the description of the pipeline for the creation of Virtual Sensors and applies it to a no-frost refrigerator. The Data Acquisition phase is described and feeds the Model Creation phase. For the case study, the data have been discretized and labelled to train a Random Forest algorithm. The validation of the model has been done on an independent dataset. An analysis of the minimum prediction accuracy required for the model is reported. Furthermore, experimental data shows the effect of hot load positioning on the compressor's working time rate.

Sustainable Product Development (SPD) has been gaining increased attention in academia, industry, and policy. Over the past three decades, significant progress has been observed in incorporation of environmental issues into the product development process, through the so-called ecodesign management practices. Nevertheless, systematisation of the SPD practices, which simultaneously consider the environmental, social and economic dimensions of sustainability, is still missing. To address this gap, this research aims to identify the existing SPD management practices in the academic literature, with special focus on how sustainability dimensions are currently being considered, their coverage in relation to key knowledge areas for product development and their applicability across the SPD phases. Through a systematic literature review, 362 practices were identified and further classified according to a classification criteria. While environmental considerations are still the most prominent ones, the research highlights the importance of the early stages of product development for SPD, as well as the key knowledge areas which are currently being covered by the practices, such as sustainability evaluation and sustainability improvement.

The agile methodology is gaining attention among practitioners and researchers in hardware development. As a new methodology, it is a source of misunderstandings and misinterpretations. This is problematic at the managers' levels as they may hinder its adoption or lead to its impractical implementation and use. This study, therefore, aims to explore the manager's level of understanding of the agile methodology. The study identifies the similarities and differences between the fundamental elements of the agile methodology and the elements mentioned by managers in hardware development. The fundamental elements of the agile methodology are identified based on the elements presented in the Scrum method; the elements mentioned by managers are identified based on ten semi-structured interviews with managers in hardware development. The study shows that the understanding of the agile methodology varies largely among managers. The obtained detailed insights in the managers' level of understanding of the agile methodology could be used to develop appropriate support to facilitate its adoption and implementation.

Data-driven design is expected to change design processes and organizations in significant ways. What actions should design managers take to ensure the best possible outcomes in this new data-driven design environment? This paper employs an interdisciplinary literature survey to distill key impacts that data-driven design may have on designers, design teams, organizations and product users. Findings reveal that designers may need a broader set of skills to be successful. For data-driven design to be most effective, design managers will be challenged with many integration tasks, including the integration of AI-based tools into design teams, the closer integration of interdisciplinary teams, the integration of qualitative design thinking methods with new data-driven design paradigms, and the integration of data and algorithms into traditional human-centred design practice, in an effort to overcome cognitive limitations and augment human skill. This paper identifies gaps in the literature at the intersection of data-driven design and design management, design thinking, and systems thinking.

With the continuously increasing integration of (mechanical) products, the identification and management of trade-offs becomes a major task in product synthesis, with substantial effect on optimality and robustness of the final solution. At the same time, a rigorous and comprehensive study of trade-offs through mathematical design optimisation is often impractical in design, as efforts spent on modeling and optimizing are likely wasted if a chosen design is changed. Extending research on configuration redesign based on a multiobjective monotonicty analysis (MOMA), this paper presents three levels of evaluation for early design or redesign: (I) informal evaluation, (II) opportunistic evaluation, and (III) exhaustive evaluation. The chosen level depends on what knowledge the designer wants to gain, and the higher the level, the larger the analysis effort, the lesser the re-use of the information gained from the initial MOMA analysis respectively. The approach is illustrated using a novel drug delivery device, the Self-Orienting Millimeter-Scale Applicator (SOMA), for the oral delivery of protein compounds such as insulin.

Using the case study of a smart green blue roof pilot project in Greater Manchester, the authors have coded and analysed a series of semi structured interviews. We present our findings which are specifically focused on how 'smart' was understood by the multiple stakeholders involved in the project and how product complexity is managed when digital technologies are integrated into nature based solutions that are becoming more popularised in the construction sector. This integration of digital twin and sensor technologies with physical drainage products to create the next generation of smart green blue infrastructure, presents numerous challenges for organisations in the construction sector. We conclude that the need for smart systems of systems in this sector necessitates organisational change and new methods of knowledge transfer across organisations who work together to deliver the holistic physical and digital services to the client.

participants have an average annual carbon footprint of 844 kg of carbon dioxide-equivalent emissions. Thus, it is crucial to find solutions that reduce the sports industry's environmental impact. In this context, the circular economy emerges as a possible alternative. This paper analyses a sports production and retail company transitioning to the circular economy. First, we identified 154 internal circular projects concerning 89 product categories and classified them into different circular strategies and approaches. Then, we conducted interviews with 33 project representatives. Our results show that repair & maintenance is the most employed loop, but sharing economy and recycling also have an essential role. Each circularity loop presents specific challenges, but personal conviction is the common motivator. However, there is a need for greater allocation of resources such as time and budget. Additionally, strong governance is essential to structure these initiatives.

Companies design, develop, and market new systems of products and services, through the process of translating beneficiaries’ needs into design specifications, where beneficiaries are those who generate value when using the new product or experiencing the new service enabled by the product. Successful new systems of products and services attract potential beneficiaries. This study explores how to identify the stakeholder engagement requirements of a new system at its early stage of development.

The study proposes a procedure and a tool - a new visual representation called the stakeholder-value map - to show the system development team how stakeholders are to interact with the system's key elements, and hence inform the timing of stakeholder involvement, for realising the value proposition of the new system. A working theoretical construct is also emerged from the study: for a new system to have a higher chance of market adoption, one can first visualise the ‘route’ of value-creation, from the lowest value-level product/service elements to the highest value-level service elements; then, identify the requirements for stakeholder engagement in the new system development.

Atrial Fibrillation (AF) is one of the most prevalent cardiac diseases in the world. How might we design patient journeys improving quality of life using wearable cardiac devices for continuous out of hospital monitoring and support? Most of the studies to date have emphasised the technical aspects of implementing such devices with less focus on human factors. As such, remote cardiac monitoring appears to be burdened by poor patient adherence. This research study proposed a journey map based on Roger's technology adoption model to understand the challenges faced by AF patients and non/asymptomatic patients in using wearable devices to monitor their health. Data from semi-structured interviews conducted in Denmark with 12 participants aged 24 to 65 years was used. Interview results show that citizens prefer tracking heart activity only in conjunction with other measures such as steps or sleep and do not feel motivated to track their heart activity on a daily basis. Patients view wearables as a valuable tool to check if their health is all right, although apprehension that devices can cause unnecessary worry can lead to their rejection. Finally, recommendations for the design of patient journeys when using wearables were made.

Complex systems typically consist of many components and are subject to many requirements. Approaches like the V-Model support complex systems design by providing guidelines on how to break down large systems into smaller pieces. Models built with SysML provide documentation on an abstract level. However, neither incoporates detailed information on components that may be relevant for design decisions. In robot-like systems, e.g., the choice of transmissions will depend on the system dynamics of the robot. This is modeled in the time domain, where detailed time-dependent component interaction is considered. The design perspective, however, is best represented in the property domain. Here, requirements on static component properties are formulated.

This paper presents a generic approach that connects the property and time domains to enable early-stage design decisions. The approach is applied to a 1-link robot system with a simple demonstrator transmission model, including properties that are typically not considered in the early design phase, like a nonlinear stiffness characteristic with backlash.

Objective of this contribution is to present the use of Model-based Systems Engineering within the engineering design community. Based on a differentiation between SE and MBSE, the definition of three core MBSE elements, namely modelling method, modelling language, and modelling tool as well as the three major aspects of a consistent system model (requirements, behaviour, and structure) a structured review is conducted, focussing on the understanding and motivation as well as the modelling of systems. The review includes 93 publications from Design Society library and proceedings of the CIRP Design conferences during the period from 2011 to 2022. The review points out, that there is an increasing application of MBSE within the engineering design community, mainly focussing on architecture definition or combined engineering activities. Only a small portion of works (16 publications) are providing a consistent approach as these publications link all aspects of the system model and consider all three MBSE elements. It can be concluded, that there is a diffuse understanding of MBSE and different motivations are given to apply more formal system models as well as modelling tools.