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.

New design objectives as the digital twin encourage companies to replace the tradition document-based systems engineering approach by a model-centric one. All views of the system rely on different types of models that serve many objectives, especially to improve communication among stakeholders. However, the increasing number of heterogeneous models jeopardize communication at the end. Indeed, to get a holistic view of the virtual definition, engineers have no other alternative than to navigate through numerous models requiring domain-specific software and language. In this paper, we propose to use virtual reality to develop an immersive environment for a collaborative model-centric review of engineered systems. The virtual environment, which relies on a digital thread stored in a graph-oriented database, enables users to explore a model-centric design by navigating through the models in a unique virtual space. To illustrate our proposal, we use a model-centric design of a telescope and shows how our preliminary prototype supports the reviewing activity with data limited to the architecture and geometry. Future works will concentrate on the integration of data related to other perspectives on the system.

New technologies have always been disruptive for established systems and processes. Additive Manufacturing (AM) is proving to be one such process which has the potential to disrupt handicraft and its manufacturing processes. AM is customisable, adopt multiple materials and is not restricted by the manufacturing process. Our research discusses this global phenomenon with case studies to highlights the growth of a new kind of professionals known as ‘Digital Artisans’. These artisans will assimilate the latest technologies with the cultural practices of the societies to create a new genre of products. The evolution of such artisans will be majorly led by people who have an equal inclination towards art and science and can act as the bridge between the handicrafts and technology. The development of such artisans will be supported by academics that will serve as a cradle and expose them to AM, design and handicraft. Its will also help in paving the growth of contemporary artisans who will utilise the strength of algorithms, artificial intelligence, CAD software and traditional aesthetics to create handicrafts of the future.

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.

Predicting the impact of changes in a design can be challenging, especially for complex designs. Margins are often built into the designs which can absorb the knock-on effect of such changes, erroneously allocating which can however, lead to propagation. A method for localising and sizing margins in an incremental design context is the Margin Value Method. This paper adapts MVM in the context of uncertainty in input specifications. It discusses possible ways to allocate them in a design such that undesirable effects of margins are minimised while preventing change propagation.

Today high quality and low product development turnaround time are company-wide priorities. Quality supporting processes such as an effective risk management system shall support continuous business running and meeting the goals of an organization. In this paper, an approach is presented on how to integrate the product risk management in Product Lifecycle Management for configured products by definition of an additional software module and its implementation.

The dynamics of design teams play a critical role in product development, mainly in the early phases of the process. This paper presents a conceptual framework of a computational model about how cognitive and social features of a design team affect the quality of the produced design outcomes. The framework is based on various cognitive and social theories grounded in literature. Agent-Based Modelling (ABM) is used as a tool to evaluate the impact of design process organization and team dynamics on the design outcome. The model describes key research parameters, including dependent, independent, and intermediates. The independent parameters include: duration of a session, number of times a session is repeated, design task and team characteristics such as size, structure, old and new members. Intermediates include: features of team members (experience, learning abilities, and importance in the team) and social influence. The dependent parameter is the task outcome, represented by creativity and accuracy. The paper aims at laying the computational foundations for validating the proposed model in the future.

In design engineering, the early consideration of tolerance chains contributes to robust design. For this, a link of design and tolerancing domains is essential. This paper presents a combination of the graph-based tolerancing approach and the Contact and Channel approach to link these domains. The combined approach is applied at a coinage machine. Here it provides detailed insights into state-dependent relations of embodiment and functions, which can improve robustness evaluation of the concept. This approach shows a possibility to bridge the gap between design and tolerancing domains.

Additive Manufacturing (AM) processes had an extensively and substantially technological growth over the past years that directly influences the continuously increased and manifold possibilities for processing new and innovative products. However, additively manufactured products mostly are still fabricated with only small adaptions compared to conventional parts, and thus waste many design potentials although specific design guidelines have been widely developed to restrict geometrical deficiencies or suggest improvements in component design.

As a result, this contribution furtherly aims to systematically consider AM potentials already on the functional level of product development offering significant but until now still not or just insufficiently exploited potentials. Therefore, the presented approach uses the already proven Design Pattern Matrix (DPM) approach for conventional technologies extended by a concurrent selection of materials and processes specifically for AM. Here, the DPM derives information about the manufacturing process in form of design elements and links them to the function carriers of the product including a methodological determination of requirements.

Artificial intelligence (AI) is seen as a great opportunity to secure future competitiveness in many corporate sectors. Potential for its use also exists in product development (PD) activities due to the amount of data generated and processed. Nevertheless, there are problems in applying the technology. This paper addresses current challenges based on a literature review, considering three disciplines that are necessary for the scope of this paper as a minimum: AI itself, information technology infrastructures (ITI) in context of digital transformation (DT), and PD as an application area. Building on the basic considerations of the state of the art, a link between the domains is established by outlining a possible reference framework towards the utilization of AI applications in PD. This enables an expanded interdisciplinary understanding. Key obstacles appear specifically to be difficult collaboration conditions between the disciplines of PD and AI applications development due to communication problems. Reasons for this include:

• – Meta models of PD do not provide a sufficient information base

• – Lack of standardized process models for the deployment of AI

In this paper, we present the results of a survey of new product development practitioners regarding their design review experiences. We surveyed 128 product development professionals on their experience and preferences in design reviews. We found that the goals and type (location / synchronicity) of design reviews change over the course of a product development project. We found that the majority of design review meetings continue to be held as co-located, live, in-person meetings. For reviewing 3D models, we found that a native CAD package (rather than a viewer, or fixed views, or a physical prototype) is the most commonly used tool. We found a difference between Designers (more likely to be product engineers) and Non-Designers and their access to CAD software, as well as their preference for which tool to use at the design review for 3D model evaluation. We hope that our findings spark future work related to better understanding design reviews and design reviewers in context. Design reviews are an important part of industrial product development processes, so we believe future studies have a large potential to improve these design activities

Set-Based Concurrent Engineering is commonly adopted to drive the development of complex products and systems. However, its application requires design information about a future product that is often not mature enough in the early design stages, and that it is not encompassing a service and lifecycle- oriented perspective. There is a need for manufacturers to understand, since the early design stages, how customer value is created along the lifecycle of a product from a hardware and service perspective, and how to use such information to screen radically new technologies, trade-off promising design configurations and commit to a design concept. The paper presents an approach for the multidisciplinary value assessment of design concepts in sub-systems design, encompassing the high-level concept screening and the trade-off of different design concepts, and enabling the integration of value models results into a Set-based Concurrent Engineering process. The approach is described through its application in the case study of the development of a subsystem component for a commercial aircraft engine.

Current trends in product development are digital engineering, the increasing use of assistance tools based on artificial intelligence and in general shorter product lifecycles. These trends and new tools strongly rely on available data and will irreversibly change established product development processes. One example for such a new data driven tool is the plausibility check of linear finite element simulations with Convolutional Neural Networks (CNN). This tool is capable of determining whether new simulation results are plausible or non-plausible according to numeric input data. The digitalization and the increased use of data driven tools employing algorithms known from Artificial Intelligence also shifts the roles of many involved engineers. This paper describes and highlights this transition from current product development processes to a data driven / simulation driven product development process. Particularly, the shifts and changes of different roles and domains are illustrated and an example for changing roles in the design and simulation department is described. Furthermore, required adjustments in the design process are derived and compared to the current status.

Additive manufacturing offers great potential in geometric design through the layer-by-layer production of components. This is often used in the development of additively manufactured components to make components lighter. An even greater reduction in mass is possible if several components are combined into a more complex component. However, as complexity increases, so do the manufacturing costs, due to a higher demand for supporting structure, reworking and longer production time. Especially for complex components, which make poor use of the space available in the additive manufacturing system, component separation can be a useful way of reducing manufacturing costs. Therefore, a procedure for automated component separation is presented, which determines an optimal cutting plane with respect to the manufacturing costs. The presented procedure is evaluated using two exemplary components where a reduction of manufacturing costs up to 54 % could be achieved.

In the first quarter of the new millennium, the immersive technologies such as Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) are only a few steps away from becoming the mainstream tools within the design industry. This study investigated the internal and external barriers of technology adoption within design-oriented businesses. A mixed method was used to collect and analyze the data from the employees of a large design firm. This research confirmed that external barriers such as funding, technical support, training, and business strategy that exist at the organizational level are interrelated with the internal barriers such as designers’ and managers’ perception and attitude toward the new technologies. The managerial applications were discussed later and the directions for future research were provided.

Experiments that study engineering behavior in design often rely on participants responding to a given design prompt or a problem statement. Moreover, researchers often find themselves testing multiple variables with a relatively small participant pool. In such situations multiple design prompts may be used to boost replication by giving each participant an equivalent problem with a different experimental condition. This paper presents a systematic approach to compare given design prompts using a two-step process that allows an initial comparison of the prompts and a post-experiment verification of the similarity of the given prompts. Comparison metrics are provided which can be used to evaluate a level of similarity of existing prompts as well as develop similar problems. These metrics include complexity (size, coupling, and solvability), familiarity, and prompt structure. Statistical methods are discussed for post-experiment verification. Guidelines are provided for a post-experiment survey which may be used for an additional perspective of prompt similarity. The proposed approach is demonstrated using an experiment where two design prompts were used for within-subject replication.

This paper provides an overview of the state-of-the-art research about creative work and learning environments. We conducted a systematic literature search within the Scopus database and identified a total of 70 relevant sources discussing creative spaces within academic, practice, or other innovation environments. Among the included sources are 48 academic publications and 22 sources from company research and illustrative coffee-table books that are discussed separately. We analyse the academic sources regarding their theoretical contribution, as well as regarding their scope. Finally, the included sources are categorized according to three areas of interest: (1) the addressed space types for different creative activities, (2) abstracted requirements for creative spaces, and (3) concrete characteristics and configurations of a creative space. The results provide an in-depth insight into the current state of research on the topic of creative spaces. Practitioners, educators, and researchers can use the presented overview to investigate the possible impact of creative workspace design and to identify research gaps for conducting further research in the field.

Engineering changes are necessary to stay competitive, unavoidable and occur more frequently with increased product complexity. Currently, scheduling of engineering changes into production and supply chain is a manual process. With new possibilities in the field of artificial intelligence, this publication presents the vision of a flexible multi-agent system with four agents and a single shared database. By autonomously scheduling changes and predicting KPI impacts of implementation dates, the agent-system provides additional capacity and decision-making support to the organisation.

The modeling of battery electric vehicles (BEVs) still represents a challenge for vehicle manufacturers. The installation of the new types of components needed for BEVs gives rise to uncertainties in the quantification of parameters like the vehicle's weight. Indeed, vehicle weight plays a key role, since it has a drastic effect on the vehicle's range, which is an important selling point for BEVs. Uncertainties in weight estimation create weight fluctuations during the early development phase and the need to resize components like the electric machine or battery. This in turn affects the components' volume and weight. However, such resizing can also lead to component collision and unfeasibility of the vehicle architecture. To solve this problem and to support concept engineers during the early development phase, an iterative approach is required that is capable of estimating weight and volume fluctuations in the relevant components. The approach should also consider the geometrical interdependencies of the components, to ensure that no collisions occur between them. Taking the gearbox as an example application, this paper presents a novel approach that satisfies these requirements.