Testing activities to gain specific design knowledge play an essential role in engineering design, when a structure needs to be developed, for which knowledge from analytical models or documentation is missing. As research into these testing activities is difficult, few insights into successful approaches exist.

In this contribution, we investigate testing activities to gain specific design knowledge through a laboratory task, where 10 engineering students optimize a system using a web-based process chain including rapid prototyping and testing. Design and testing data are acquired from 110 prototypes in 3 hours. A differentiation of performance is conducted and approaches of high- and low-performers are investigated to identify patterns.

Based on these patterns, hypotheses, and metrics indicating successful and non-successful approaches are derived as basis for development of metrics for testing to gain specific design knowledge. A successful approach was overstep the limit, where participants accept destruction of their system to identify boundaries. An unsuccessful approach was the change of many parameters in later tests. These hypotheses and their metrics can then be used in development and validation of support for testing.

Gaze sharing is an emerging technology which can enhance human communication and collaboration. As such, it is expected to play an important role in future educational practices. To date, its application was not explored in the context of design education. Additionally, it was mainly implemented in non-immersive environments, which are limited in their potential for engaging learners. Acknowledging the growing interest in immersive learning, as well as the promise made by gaze sharing technology, we strive to develop an immersive gaze sharing environment, to support design education. As a first step, we have implemented and tested an immersive gaze sharing system for supporting design learners. The system was then tested by focusing on a scenario of architectural design, with the aim of collecting valuable user feedback regarding its usability and potential. Our initial user study informs developers of such systems regarding potential issues that may be encountered during deployment in a real-world setting and proposes concrete ways to address these. These insights can help to pave the way for integrating gaze sharing system into design education practices in the near future.

The tolerancing of products for manufacturing is usually performed at the end of the design process and the responsibility of the designer. Although components are commonly tolerated to ensure functionality, time-based influences, like wear, that occur during operation, are often neglected. This could result in small amounts of scrap after production, but high quantities of failure during operation. To overcome this issue, this paper presents an approach to perform a multi-objective optimization considering tolerances based on a wear simulation. Thereby, mean shifts serve as optimization variables, while the aim of the optimization is to generate an optimal ratio of scrap to failure. In addition, the optimization results are interpreted and further options for the designer are presented. Moreover, the approach is exemplary applied to a use case.

Aluminum foam sandwich (AFS) is an innovative material for lightweight structures, consisting of an aluminum foam core surrounded by two face sheets of aluminum. The advantages of AFS are a low density combined with a high bending stiffness, good energy absorption properties, and high recyclability, meaning it can be used for many different applications. However, the number of realized series applications with AFS is low caused by a lack of design knowledge, as shown in various studies. In order to address this lack of design knowledge, a design guideline is to be developed. This paper focuses on the development of such a design guideline based on requirements and demands from the industry and presents a structure. In addition, the individual contents of the design guideline are explained in more detail in order to clarify how designers can be supported in the future when designing products with AFS, so that the full potential of this material can be realized. Finally, a survey in an industrial context evaluates the extent to which this design guideline is a useful form of support, in order to check whether its application can improve the design process with AFS.

In the EU, initiatives with concrete instruments for measuring and storing sustainability-related product data are now introduced in legislation. Based on literature review and semi-structured interviews, this study investigates two EU instruments, the Product Environmental Footprint method and Digital Product Passports, and their potential implications for company capabilities to design and select more sustainable solutions in a strategic way. The results show that these instruments can lead to increased transparency and traceability in the design and comparison of solutions, allowing for more effective collaboration across the value chain. By applying a strategic sustainability perspective, it was found that these EU instruments have major limitations as they lack a systems perspective, do not include a full socio-ecological sustainability perspective, and do not support strategic decision-making. This results in risks for suboptimization and the design of solutions that turn out to be costly dead-ends on the way towards a sustainable society. Research is therefore recommended to investigate how these instruments can facilitate a strategic development of sustainable solutions.

In the development and production of new products, interdepartmental knowledge transfer is essential. Successful knowledge transfer faces several challenges, such as a lack of willingness to transfer knowledge or an inappropriate selection of tools. These can lead to the reduction of efficiency and effectiveness of knowledge transfers. Therefore, the InKTI – Interdepartmental Knowledge Transfer Improvement Method is developed to support the improvement (in terms of speed and quality) of knowledge transfers, particularly in product and production engineering.

This paper presents the first validation of the InKTI Method through a field study at the company Protektorwerk Florenz Maisch GmbH & Co. KG, which is a leading European company in the construction industry, to support the successful knowledge transfer into practice. Therefore, the research need is pointed out, and a concept for validation is developed and implemented. Afterward, the InKTI Method is evaluated based on its success, support as well as applicability.

Prototyping is essential for knowledge acquisition and, thus, for informed decision-making in product development. The gold standard is still the use of physical prototypes. However, with the increase in computing capacity, it is becoming easier also to use virtual prototypes.

The selection of prototyping approaches often starts with the distinction between physical and virtual prototypes and therefore excluding a broad range of possibilities early on.

This paper explains why a selection of prototypes based on the distinction between physical and virtual is not necessarily the best solution and suggests a selection approach based on characteristics which offer the possibility to avoid this limitation. Therefore the characteristics of physical prototypes commonly used in literature are analysed and reduced to a generally valid selection. Examples of virtual prototypes are selected and analysed regarding their characteristics. All elaborated characteristics are then tested for their applicability to the examples of virtual prototypes.

With advancing digitalization, new technologies with more and more digital components make it necessary to integrate new components into current and future products. Sensors and actuators, such as motors, emit electromagnetic and thermal fields that can greatly affect product performance. Recent work has considered fields at the functional level using functional structures and at the system level using DSM. In this paper, the effects of fields on product architecture are investigated at the component level. Using an appropriate visualization, the impact of fields on the product structure is considered. Architectural guidelines are then used to develop suitable product structures. The methodological approach is then applied to a product family of vacuum cleaner robots. The overlaid field information helps to gain deeper insights into the product architecture. The approach is useful for representing alternative structures. The new mapping of functional and structural relationships by moving module boundaries against fields can help promote architectural innovation.

This study investigates the impact on student confidence of completing in-lecture engineering design activities focused on the application of specific engineering science topics within a materials engineering course. Many times, engineering science courses are taught with the expectation that the course content can be easily translated by students at a later time to apply in engineering design activities. By measuring student self-reported confidence across several related topics before and after completion of the in-lecture design exercises the impact of the exercises on student confidence has been quantified. On average, students have a lower than desired confidence in applying the specific materials engineering topics to a design problem after completing only the course content on the subject. Following completion of the related seventy-five minute design exercise, student confidence increased by a statistically significant degree. These results suggest that close integration of topical content learning with design application activity may be a useful method to improve engineering student confidence and, by extension, retention.

Well-educated engineers are key for successful engineering design in product development. Due to varying school education and technical backgrounds, the students have different prerequisites for the acquisition of competences. Subject of this paper is to show the methodical implementation of the prototype AdE-Le suited to the curriculum at Ruhr-University-Bochum and the open source learning platform Moodle. Aim is to evaluate the didactic potential to support engineering students with heterogeneous competence levels. The general needs and existing approaches for E-Learning environments as a means to individualize learning content in engineering design are discussed. Major aim is to reduce the linkage between the students' technical background and their exam success. AdE-Le as an exemplary application is developed based on the didactical concept of Constructive Alignment. Due to a harmonization of learning methods and contents in Engineering Design across the members of the Scientific Society for Product Development the results of this investigation can be transferred to other Universities.

This research aimed to gain insight into current practices and challenges with respect to the adoption of virtual testing and integration with physical testing in product development processes. A focused workshop investigated industrial perspectives on adopting virtual testing and current challenges. This paper reports the findings from the workshop in which representatives from a range of industries explored how virtual testing is used to support physical testing in their different contexts. This paper discusses the current challenges industries face in adopting virtual testing and changing role of physical testing, with reference to recent literature on physical and virtual testing and supported by an earlier empirical case study. This paper reports areas where more research is needed to support industries in overcoming these challenges.

Additive Manufacturing (AM) has traditionally been used for prototyping of products, however, in the last few decades, it has seen a rising growth in the manufacture of final products. The addition of AM as a manufacturing method in the portfolio of a company's production capabilities increases the complexity of decision-making. This is because the decisions are often not based on the same criteria and constraints, as related to conventional manufacturing processes. In this paper, we investigate this challenge by studying how AM affects the current workflow and the associated information flow for a design-make process in a Swedish manufacturer before and after the integration of AM. In this paper, it is argued that apart from an understanding of how to design for AM, it is equally important to consider how introducing AM alters the existing information flow and how to benefit from information available in various design-make process steps to facilitate decision making process. The result clarifies that the current process relies largely on tacit and experiences-based knowledge, whereas to take advantage of AM, more precision is required to capture and process the available information.

Product-Service Systems (PSS) are seen as key enablers of circularity. However, better sustainability performance of PSS when compared to transactional business models is not given and it must be carefully considered in the design process. The early-stage PSS design is considered crucial because it determines most of the future offerings' impact. Nevertheless, manufacturing companies struggle with PSS design and often rely on ad hoc intuitive approaches with low success rates. Current PSS design approaches have been dispersed in literature until a recent systematic literature review by the authors proposed a comprehensive generic process model to enable the inclusion of sustainability considerations in the early stages. This paper takes the generic process model as a starting point and instantiates it to the context of two manufacturing companies, seeking to (i) explore the instantiation process from a generic to company-specific process models to support manufacturing companies; and (ii) reflect upon and prepare an evaluation of the generic process model concerning eight predefined criteria. The study reveals a number of potential areas for improving both generic and instantiated process models.

Complex global problems, such as sustainable crop production, where conventional products do not fully solve the problem due to their low efficacy and negative environmental impact, require rationally designed products. Generally, these products are based on efficient technologies and stimuli-responsive and high-performance materials. Considering the product design approach with a science-based approach such as drug development through QbD. We propose to merge the most relevant elements of these approaches in an integrated design methodology. Regarding the conceptual analysis, we propose two phases: initially, an early phase with conceptual solutions, followed by an advanced phase based on QbD elements to define the research hypothesis. Hence, optimal product conditions defined in the design space must comply with the required performance of the stimuli-responsive product. So, with this proposed integration we pretend to potentialize and strengthen the established tools for product design, achieving an advanced and robust design methodology.

This paper present a pedagogical tool to address a lack of creative approach in traditional education on embedded sensors. The tool is built in a systematic way from the data sheet information of a large number of different sensors. The tool presents the main monitoring capabilities of embedded sensors on cards to assist students in the creative stages of product design. An experiment was conducted to test its educational potential with 30 Masters students in product design. The statistical analysis on the experiment data indicate that the tool enables the improvement of knowledge on embedded sensors, with a more significant gain in advanced thinking skills. Finally, the tool is easy to implement in product design education and accessible to a wide range of students.

While a significant amount of research has documented the importance of design artefacts in design communication, relatively little work has investigated the effect of design artefact quality on the development of a shared understanding between designers. In the current work we focus specifically on sketch quality and the effect of sketch quality on the shared understanding of design dyads. A controlled study with 22 design dyads (44 designers) was conducted to understand the relationship between sketch quality and shared understanding. Results suggest that design artefact quality, measured by sketch understandability, does not predict the shared understanding of a design concept. Our findings hold implications for the fundamental ways in which we evaluate sketch quality and the importance of artefact fidelity for communicative acts.

Design neurocognition is an emerging research area that can provide insights into the black box of designers’ cognitive processes. However, work to date has focused on neurocognition on its own, without integrating this with other design measures. This paper presents the results of a pilot study which brings together designer neurocognition with design output and assessment of the design process followed in a constrained prototyping activity comparing use of physical and digital Lego. This was achieved via EEG data capture, a TLX survey and measures of design output variance. Differences between physical and digital prototyping methods were found with respect to Task Related Powers of EEG signals and the design process followed with digital prototyping methods found to take longer, require more effort and cause more frustration. No differences were found with regard to design output. Whilst the sample size used (n=12) was small, future studies will use large sample sizes to increase their statistical power and will consider alternative EEG or fNIRS to capture brain activity due to challenges with the headset used in this study.

COVID-19 pandemic has continued to pose a challenge to the society for almost three years, adversely affecting all segments of population in a scale unseen in the recent decades. Over the course of COVID-19 pandemic, many people have lost their jobs and income. These social and economic impacts have disrupted the market, potentially altering people's attitudes towards different product features. Therefore, this paper investigates the changes in customer preferences on various features of different products, before and after COVID-19 pandemic, using online review analysis. The proposed framework consists of four stages. Firstly, product review data is collected and preprocessed. Secondly, customer interest in product features is explored using latent Dirichlet allocation. Thirdly, customer sentiment for these features is analyzed with Valence Aware Dictionary and sEntiment Reasoner. Finally, the importance of each feature is calculated based on interpretable machine learning. The proposed method is tested on two real-world datasets – smartphone and laptop reviews. The result reveals the changes in customer sentiments and preferences for product features, thus helping companies quickly establish strategies in rapidly changing market environments.

Transition activities, such as design reviews, are often utilised in product development to evaluate the conducted work and plan future actions. While key decisions are made during these activities, they are still underexplored. This paper studies the effect of transition goals and virtual reality (VR) on transition team performance. In an experimental study, four-member teams conducted two transition-related experimental tasks (validation and verification) working in one of the two conditions (VR or desktop interface). The results show that transition goals and VR affect performance. More specifically, the validation-oriented transition was more efficient but less effective than the verification one. Furthermore, the performance of the validation-oriented transition compared to the verification one was increased in VR and decreased in a desktop interface. Finally, the high-performing teams consistently discussed new issues, while low-performing teams had prolonged moments of not discussing anything new. These findings suggest that desktop interface and VR are not substitutable but rather complementary technologies.

The number of digital solutions based on machine learning has increased in recent years. In many industrial sectors, they try to enhance automation in manual or repetitive tasks or provide decision support for complex problems. Data plays an essential role in the selection and implementation of ML algorithms, as it determines the quality of the training and the results. As data drive ML models, selecting the correct data with the suitable ML algorithm for a given use case is crucial but challenging. This paper reviews the application of machine learning in the embodiment design phase addressing the challenge. The work focuses on ML applications in conventional product development and non-conventional additive manufacturing processes. Based on the literature review, the required knowledge to implement the ML algorithms has been derived and presented in a systematic approach. This work highlights the importance of an initial analysis of the existing knowledge in the engineering and additive manufacturing processes in order to implement the proper ML algorithms.