The development of a new motor can be a high effort. In this paper, Model-based Systems Engineering (MBSE) is applied to model the second generation of an electronic compact actuator (ECA). This paper focuses on the traceability between model elements from previous product generations. By integrating the approach of the PGE - Product Generation Engineering in MBSE, developers can store more relevant information in the model; they can accomplish automatic calculations of derived factors and build models more efficiently in further product developments.

The rapid pace of development in Digital Engineering has led to an explosion of ideas and new practice in how it can support Engineering Design and Manufacture. You may have heard of the terms Digital Transformation, Digital Twin, Digital Thread, Digital Tapestry and Digital Footprint amongst many other forms of “Digital X” but how have these come about and how do they come together to provide the landscape of what Digitalisation has to offer?

In this paper, we analyse the emergence, definition, use and co-occurrence of “Digital X” terminology from an academic dataset of 19,627 papers curated from Scopus. The results reveal that these terms are being used without being fully contextualised in terms of a hierarchy or equivalent to effectively articulate the Digital landscape.

Through this analysis, an emerging “Digital X” framework is proposed, with evidence given to support suggested links, and knowledge gaps highlighted for further investigation. Once this framework is complete, a rich lexicon describing the Digital Landscape will pave the way for the future in Digital Engineering.

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.

Engineering change management is a central part of the product development process. This paper investigates how variations from the PGE - Product Generation Engineering can improve the evaluation of engineering changes from the wiring harness. Engineering changes that occur in an automotive wiring harness development process are analysed in a case study, evaluated in expert interviews with regard to the risk and effort connected to the implementation and compared to the types of variations. Additional influencing factors are discussed. The variations provide an indication on risk and effort.

Future transport will change drastically with the introduction of automated vehicles. Here, Autonomous Mobility on Demand (AMoD) will play a major role, requiring a radical change of vehicle design, with many different conceivable concepts. This technology shift holds high potentials and high risks. Uncertainties about future usage profiles, operator and customer requirements have to be dealt with. An approach to elicit initial requirements for future vehicle concepts considering the entire ecosystem is introduced. The applicability is shown for a specific urban mobility scenario.

The information from Real Twins are increasingly used to construct Digital Twins. Acquisition of information from the Real Twin or in other words performing measurements on the Real Twin may lead to effects in the working of Real Twin. For instance, the introduction of sensors may impair certain functions of a Real Twin. Therefore, it is important to analyse the effect of any change that is performed on the Real Twin for achieving the Digital Twin. In this paper, a method for Digital Twin solution is presented that address these aspects as well as its use is demonstrated by a case example.

The ability to effectively analyse design concepts is essential for making early stage design decisions. Human evaluations, the most common assessment method, describe individual design concepts on a variety of ideation metrics. However, this approach falls short in creating a holistic representation of the design space as a whole that informs the underlying relations between concepts. Motivated by this shortcoming, this work leverages network theory to visualize and characterize features of a conceptual design space. To illustrate the utility of network theory for these purposes, a network composed of a corpus of solutions to a design problem and their semantic similarity is derived, and its design properties (e.g., uniqueness and innovation potential) are studied. This network-based approach not only characterizes features of individual designs themselves, but also uncovers more nuanced properties of the design space through studying emerging clusters of concepts. Overall, this work expands on developing research in design, demonstrating the value in applying network analytics to a conceptual design space as an engineering support tool to aid design decision-making.

Different variants of a-posteriori novelty metrics can be found in the literature. Indeed, such a kind of assessment procedures is often used to extract useful information about creativity and/or idea generation effectiveness. In particular, the metric proposed by Shah et al. in 2003, is one of the most used and discussed in the literature. However, scholars highlighted some flaws for this metric, and some variants have been proposed to overcome them. This paper argues about the variants proposed for the a-posteriori metric of Shah et al., and proposes a selection framework to support researchers in selecting the most suited for their experimental needs. The proposed selection framework also highlights important research hints, which could pave the way for future activities. More specifically, it is still necessary to support the identification of the best-suited abstraction framework to assign weights to attributes, and the assignment of weights should be better supported as well. Moreover, this paper highlights the presence of “uncommonness of key attributes”, which needs to be investigated for experimental cases where ideas missing some key attributes are present.

This paper presents a new design methodology for improving the installation of large size and long life cycle goods that need to be assembled in the field. The approach integrates a modified design for assembly (DfA) methodology. A new approach is proposed for integrating different DfA methodologies and tested in a real case study of a machine room-less (MRL) elevator. A tool for analyzing and quantifying the proposed solutions is developed. Improvements of approximately 20 pp are achieved during the elevator installation and on-site assembly process, which could mean a potential reduction in assembly time of 11 h or 6%. Additional extensions and guidelines are recommended to improve the methodology and the tool.

Lightweight Design as an engineering domain is becoming more and more important in terms of sustainable mobility. Therefore, a large number of researchers is developing methods for utilisation of modern, but as well more complex materials with high lightweight potential. One subgroup of these materials are fibre-reinforced plastics (FRP). A lot of work is done supporting the design engineer in exploiting the structural and mechanical behaviour as good as possible. Whereas variations of laminate parameters, resulting from production, are poorly studied. Their impact especially on defined measures under load is of high importance, e.g. having a look on clearances in automotive industry. Because of the high complexity of FRP-parts, resulting from many laminate parameters, tolerancing is not an intuitive process. This is reflected in the fact that there is no defined procedure for tolerancing of FRP- parts. To support the design engineer the authors perform sensitivity analysis for simple loadcases to identify layers with a high importance on a defined measure. The results then are generalised to provide general guidelines to the design engineer.

Data-driven technologies have found their way into all areas of engineering. In product development they can accelerate the customization to individualized requirements. Therefore, they need a database that exceeds common product data management systems. The creation of this database proves to be challenging because in addition to explicit standards and regulations the product design contains implicit knowledge of product developers. Hence, this paper presents an approach for the semantic integration of the engineering design (SeED). The goal is an automated design of an ontology, which represents the product design in detail.

SeED fulfils two tasks. First, the ontology provides a machine-processable representation of the products design, which enables all kind of data-driven technologies. Among other representations, the ontology contains formal logics and semantics. Accordingly, it is a more comprehensible solution for product developers and knowledge engineers. Second, the detailed representation enables discovering of intrinsic knowledge, e.g. design patterns in product generations. Consequently, SeED is a novel approach for efficient semantic integration of the product design.

Scientific discoveries and inventions have long been established as two distinct and sequential activities. It has nonetheless been showed that projects aiming at producing both scientific discoveries and inventions could record impressive results. Our investigations are focusing on the creativity of collaborations outputs: a first agent is entailed to design a scientific discovery and another one invention. We use fixation effects as a performance measurement indicator for creativity based on Design Theory. We propose a first set of elements that can be suffering from fixation effects in both invention and scientific models designers reasoning. We propose a series of defixed inputs that could be shared between both designers to overcome their fixation effects. We highlight that if partners are engaged in one-way knowledge transfer it can conduct to “fixation traps”. We define a set of restrictive conditions that could conduct to a “cross-defixation process”: both actors would be able to create conjoint new inventions and scientific models in the non-fixed design path. In particular this process does not required designers to be defixed before starting the collaboration.

The recent interest in human-robot interaction requires the development of new gripping solutions, compared to those already available and widely used. One of the most advanced solutions in nature is that of the human hand, and several research contributions try to replicate its functionality. Technological advances in manufacturing technologies and design tools are opening possibilities in the design of new solutions. The paper reports the results of the design of an underactuated artificial robotic hand, designed by exploiting the benefits offered by additive manufacturing technologies.

Revolutionary changes of a VUCA-world are effecting more and more industries. Focusing the automotive industry, this is caused by several new trends in technology or market. This situation is requiring high flexibility and is questioning for sustainability as well as resilience in system development projects. This publication represents results out of a survey, part of a wider research. The objective is the development of a process orientated method for risk and technical change management. The survey is conducted by participants of transdisciplinary system development in automotive industry. Topics questioned are VUCA, complexity, (re-)action, quality and module interfaces of Generic Systems Engineering. The results demonstrate the participants’ experience and demands for sustainable and resilient system development projects. In conclusion, this report provides information on the considering elements to develop a process orientated method for risk and technical change management in automotive industry.

The importance of prototyping is unanimous with numerous studies into the media, types, roles and properties of prototypes. However, no recent papers have sought to examine and characterise industry practice and if and how this has changed since the early 2000s.

To address this, a snapshot of industrial prototyping practice with particular attention to the what, when, why, how, and by whom is reported. The study involved five small-medium sized design companies based in the South-West of the UK and validation of the findings by two independent practitioners.

The snapshot revealed that 3D printing and virtual prototyping tools have reached widespread adoption in SMEs,that their design processes are highly agile and iterative and are difficult to fit to any extant design process model.

Rather, the approaches appear to implicitly comprise of three levels of design convergence: macro, meso, and micro, which correspond to finer/more detailed changes.

The results also reveal the frequent transitions between digital and physical media and the need to manage these transitions to ensure the product representations in different media are appropriately up-to-date.

Although Life Cycle Sustainability Assessments (LCSA) are important in evaluating the sustainability of complex products and services, there is no sufficient support for engineers performing LCSA. The concept of an Engineering Graph focuses on the relations of data within engineering. It provides a model that leverages existing data in engineering and extendibility to include specialized databases and open and public data from the semantic web. This paper proposes a concept of how Engineering Graphs can be used to address the issues of LCSA and support engineers.

This paper investigates the use of Large Language Models (LLMs) in engineering complex systems, demonstrating how they can support designers on detail design phases. Two aerospace cases, a system architecture definition and a CAD model generation activities are studied. The research reveals LLMs' challenges and opportunities to support designers, and future research areas to further improve their application in engineering tasks. It emphasizes the new paradigm of LLMs support compared to traditional Machine Learning techniques, as they can successfully perform tasks with just a few examples.

The consideration of manufacturing in design is still a challenge for design engineers. This paper presents the results of an interview study, conducted with 15 participants. 4 challenges are identified in this study: Manufacturing-specific knowledge is mostly not sufficient. The design of manufacturing-oriented concepts in terms of costs is difficult. The feasibility of manufacturing is not assessed. The dimension of cost drivers is unknown, hindering optimisation in early stages of design. Based on these results the need for further research emerges regarding the impact of these challenges.

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.

In automotive industry, the design process is costly and time-consuming. Car safety is a crucial factor in the development of a vehicle, which is why crash simulation is an essential step in the design process. To improve car crash simulation analysis, it is necessary to reduce the time required and support the resolution of encountered design issues. We propose a knowledge management approach to support car crash simulation analysis and ensure the collaboration of different stakeholders. In a knowledge-intensive context, we used an ontology-based approach to formalise and capture knowledge.