Model-based systems engineering (MBSE) is well-known in gaining the control over the complexity of systems and the development processes, while agile is a project management methodology originally from software development that uses short development cycles to focus on continuous improvement in the development of a product or service. In this paper, we adopt the concept of agile into MBSE and then proposed the new approach - Munich Agile MBSE Concept (MAGIC). The highlights of the MAGIC approach can be concluded as 1) the requirements which have been defined in the first stage will be examined and traced at each following stages; 2) communication between every 2 stages always exists in order to have a close connection during each system development phase; 3) the idea of Industry 4.0 has been included and reflected to achieve automation and data exchange with manufacturing technologies; 4) the concept of IOT (Internet of Things) is also considered when it comes to the usage and service of the system to satisfy the customer's needs; 5) the whole spirit of agile is reflected as the iterative and incremental design and development

Artificial intelligence is transforming how we interact with vehicles. We examine the case of Maritime Autonomous Surface Ships (MASS), which are emerging as a safer and more effective solution for maritime transportation. Despite the focus on autonomy, humans are predicted to have a central role in MASS operations from a Shore Control Centre (SCC). Here, operators will provide back-up control in the event of system failure. There are signification design challenges with such a system. The most critical is human-system interaction in autonomy (H-SIA). We consider humans as the source of resilience in the system for adapting to unexpected events and managing safety. We ask, can Human-Centred Design (HCD) be used to create resilient interactions between MASS and SCC? Work has been done in resilience engineering for complex systems but has not been extended to H-SIA in transportation. “Resilient interaction design” is relevant as we progress from design to operational phase. We adopted the ISO 9421-210 guideline to structure our HCD approach. The result is an SCC designed for 1 Autonomy Operator (AO). The contribution is a demonstration of how resilient interaction design may lead to safer and more effective H-SIA in transportation.

Especially in the Laser Powder Bed Fusion (L-PBF) technology for metals, current manufacturing systems require the use of support structure to withstand recoater forces and lower thermal induced stresses. These support structures set limitations on the design freedom and affect the surface quality, part cost and lead-time in an undesirable manner. Complex parts, which were not possible with conventional manufacturing methods, can be produced without these limitations. While some companies claim to print parts with horizontal overhangs without the use of support structure, academic research seems to deal with these limitations by defining design guidelines rather than eliminating them. In order to highlight the discrepancies between academia and industry, a structured review is presented. As result, severe differences in knowledge were discovered, which might emerge from the use of unconstrained cutting-edge systems in industry. Eventually support-free L-PBF is not yet fully developed, but the use of support structure can be drastically reduced by optimizing the build process.

In today's engineering projects, interdisciplinary work leads to an increase in interfaces between different departments and domains. As each stakeholder pursues different goals and tasks, a heterogeneous model landscape is required. In each domain, a variety of different model and software implementations provide the essential basis for efficient work. On the interfaces, the risk of model inconsistencies increases. To handle occurring inconsistencies, various approaches have been presented. For model-based systems engineering projects, rule-based methods are considered as the most suitable technique. However, said approaches require a high manual effort in identifying model dependencies and establishing consistency rules. Unfortunately, in particular these steps are not well described and supported. Therefore, this paper presents an easily applicable approach for the identification of model dependencies in interdisciplinary projects. The method is supported by a software implementation and is directly integrated in engineering workflows. A first industrial case study has shown positive effects of the approach and revealed further research goals.

Early integration of sustainability considerations into decision making is seen as a key enabler for companies to understand the potential implications of their decisions on the triple bottom line aspects. Lack of the tools to support decisions when trade-off between sustainability aspects occur, however, may lead to uninformed decision-making and undesired outcomes. By consolidating the learnings from empirical work together with literature recommendations, we propose key criteria to be considered when developing decision support tools to manage sustainability-related trade-off situations.

Fidelity is one of the most important parameters to consider when dealing with prototypes, which affect the related costs and performances. Current literature contributions often rely on generic definitions of Fidelity based on the concept of closeness. However, the review performed in this paper revealed that Fidelity is a more complex concept, which considers (at least) eight main dimensions, mutually interrelated, and potentially characterized by many other potential sub-dimensions. The identified set has been applied to an industrial case study were a real engineering prototype has been assessed in terms of Fidelity. In particular, the case study application shows how the different dimensions can be interrelated each other. Furthermore, some important research hints have been highlighted in this paper, where the identified set of Fidelity dimensions paves the way for the related future activities.

In embodiment design, functions are implemented in a technical systems embodiment. For doing so, design engineers need to understand the relations of embodiment and function. Many systems change their states during function fulfilment which complicates their relations and leads to ambiguity in design decisions. The challenge for design engineers is that they often need to make important decisions about the design before they can use sophisticated analytical models to investigate them. This contribution presents a structure for the C&C²-Sequence Model as a non-analytical model to support design engineers in modelling embodiment function relations. This structure contains four dimensions that are derived from the state of the art and preliminary work. It enables the structuring of gained knowledge about embodiment function relations and supports their communication in design engineering teams. Two development projects in academic and corporate environment are conducted using the structure to investigate its applicability. In these projects, design engineers were able to document and use gained knowledge about the investigated complicated systems.

By applying data analytics to product usage information (PUI) from combinations of different channels, companies can get a more complete picture of their products’ and services’ Mid-Of-Life. All data, which is gathered within the usage phase of a product and which relates to a more comprehensive understanding of the usability of the product itself, can become valuable input. Nevertheless, an efficient use of such knowledge requires to setup related analysis capabilities enabling users not only to visualize relevant data, but providing development related knowledge e.g. to predict product behaviours not yet reflected by initial requirements.

The paper elaborates on explorations to support product development with analytics to improve anticipation of future usage of products and related services. The discussed descriptive, predictive and prescriptive analytics in given research context share the idea and overarching process of getting knowledge out of PUI data. By implementation of corresponding features into an open software platform, the application of advanced analytics for white goods product development has been explored as a reference scenario for PUI exploitation.

This paper presents an approach for evaluating exoskeleton support concepts through biomechanical analyses on a musculoskeletal human model. By simplifying the support forces of an exoskeleton as external forces, different support concepts can be biomechanically evaluated for the respective use case without concrete design specifications of the exoskeleton. This enables an estimation of the resulting relief and strain on the human body in the early stages of exoskeleton development. To present the approach, the use case of working at and above head height with a power tool is chosen.

The paper suggests an innovative design research and intervention approach using a poststructuralist organizational education perspective. The potential of a high impact trans-epistemic design process is shown for the field of industry 4.0 and the specific context of cognitive assistive systems (CASs). The multi-layered approach addresses the design of technical, social and educational complexity to implement CASs sustainably on the shopfloor and exploit their potential in industry 4.0. Finally, we will shed light on how the approach can enhance deep organizational transformation in industry.

In the event of damage to additively manufactured components whose shape cannot be produced by machining, an additive repair can potentially be not only ecologically but also ecologically more favorable than the production of a new component. In addition, a number of hurdles that otherwise often impede the use of additive repair, e.g. the availability of the material of the damaged component for the additive process, are eliminated. As far as the authors are aware, this publication is the first to present a process for the additive refurbishment of additively manufactured components using the example of a wheel carrier. In this context, the possibility of increasing the fatigue strength of a structural component in refurbishment is discussed for the first time. To increase the fatigue strength of the wheel carrier, the chosen approach is to integrate the effect of particle damping into the component. Particularly in the case of components subjected to bending stresses, the effect of particle damping can be integrated into the component's interior without having to accept a significant loss of strength.

Due to the varying environment conditions as well as the manufacturing induced deviations, the properties of products vary. In order to still meet the increasingly tightening of functional requirements, tolerancing as well as Robust Design practices became integral parts of the product development. However, despite the fact that the robustness of a product is mainly determined by its conceptual design in early design stages, these activities are usually carried out at the end of the design process. In order to overcome this shortcoming, this contribution shows a method that supports the selection of robust principal solutions and thus contributes to the design of product concepts, which are less sensitive to variations. The novelty lies in the adaption and combination of robust design criteria for the quantitative robustness evaluation in the conceptual design stage. First the product characteristics, which are relevant for the product robustness are determined on the basis of the function structure. By using an adopted VMEA and a newly developed evaluation matrix, this allows a thorough robustness evaluation of product concepts. The method is exemplary shown for a lifting table.

Collaborative robots (“cobots”) have attracted growing attention in academia and industry over the last years. Due to in-built safety features and easy programming, they allow for close human-cobot collaboration and support e.g. flexible manufacturing. However, the lack of a common understanding what a cobot is along with its traditional focus on arm-based cobots complicates further research and industry adoption. Thus, this paper analyses the variety of definitions in literature incl. standards and practice examples to derive a consistent and holistic definition and taxonomy of what a collaborative robot is. Aside from contributing a structured overview of various forms of human-robot collaboration, this builds an important foundation for future research as it systematically differentiates different cobot types. Companies and other organisations will benefit by a better understanding of what type of cobot they need and how to ensure safe collaboration.

Product-service systems (PSS) are solutions that integrate product and services in order to fulfill the customers’ needs by means of greater value in use. Multiple stakeholders should be involved in the design process for the development of a successful PSS value proposition. However, it is not clear who could be the potential stakeholders of a PSS. The aims of this study are to consolidate the stakeholders cited in PSS case studies and to reveal the terms used to refer to “stakeholder” in PSS literature. A systematic literature review was carried out, and an inductive content analysis procedure was applied. A total of 28 stakeholders were listed from the selected studies, whose PSS cases were classified as use- oriented or result-oriented services. Multiple terminologies are used to refer to stakeholders. This study contributes for showing the potential stakeholders that can be involved and engaged in the PSS design and operation. Also, it indicates the terms from which they can be addressed in the PSS literature.

Techniques and processes used for concept generation rely on composing new concepts and analysis given situational context. Composition and analysis require distinct neurocognitive function. For instance, jazz composition relies heavily on the right brain, while math relies on the left. Similar to music and math, is concept generation hemisphere dominant? What differences exist when using varying techniques? Twelve graduate engineering students were given three design tasks and instructed to use brainstorming, morphological analysis and TRIZ. A device called fNIRS measured cognitive activation. The results find left hemisphere dominance. More specifically, the left dorsolateral PFC (dlPFC), which is central to spatial working memory and filtering information. Temporal differences do exist. Morphological analysis and TRIZ reinforced the use of the left dlPFC, while brainstorming increased the use of the right dlPFC and medial PFC (mPFC) late during concept generation. The right dlPFC contributes to divergent thinking and mPFC facilitates memory retrieval. One explanation is designers relaxed rule constraints and more deeply searched for associations during brainstorming.

Underpinned by a contemporary view of automotive systems as cyber-physical systems, characterised by progressively open architectures increasingly defined by their interaction with the users and the smart environment, this paper provides a critical and up-to-date review of automotive Integrated Vehicle Health Management (IVHM) systems. The paper discusses the challenges with prognostics and intelligent health management of automotive systems, and proposes a high-level framework, referred to as the Automotive Healthcare Analytic Factory, to systematically collect and process heterogeneous data from across the product lifecycle, towards actionable insight for personalised healthcare of systems.

In this paper, we present results from an experiment using EEG to measure brain activity and explore EEG frequency power associated with gender differences of professional industrial designers while performing two prototypical stages of constrained and open design tasks, problem-solving and design sketching. Results indicate no main effect of gender. However, among other main effects, a consistent main effect of hemisphere for the six frequency bands under analysis was found. In the problem-solving stage, male designers show higher alpha and beta bands in channels of the prefrontal cortices and female designers in the right occipitotemporal cortex and secondary visual cortices. In the design sketching stage, male designers show higher alpha and beta bands in the right prefrontal cortex, and female designers in the right temporal cortex and left prefrontal cortex, where higher theta is also found. Prioritising different cognitive functions seem to play a role in each gender's approach to constrained and open design tasks. Results can be useful to design professionals, students and design educators, and for the development of methodological approaches in design research and education.

Considering a growing number of metrics and indicators to assess circular economy, it is of paramount importance to shed light on how they differ from traditional approaches, such as life cycle assessment (LCA) or sustainability performance indicators. This study provides new empirical insights on the correlation between LCA, circularity, and sustainability indicator-based approaches. Specifically, the importance lies in analyzing how the results generated by these different approaches can be used to support the design of products that are not only circular, but also sustainable. A practice-based project involving 87 engineering students (divided into 20 groups) is conducted with the aim to compare and improve the circularity and sustainability performance of three product alternatives of lawn mowers (gasoline, electric, autonomous). To do so, the following resources are deployed: 18 midpoints environmental indicators calculated by LCA, eight product circularity indicators, and numerous leading sustainability indicators. Critical analyses on the usability, time efficiency, scientific soundness, and robustness of each approach are drawn, combining quantitative results generated by each group with the feedback of future engineers.

To successfully facilitate user-centred design, a multitude of different aspects has to be considered, from purely physiological to psychological-emotional factors. The overall aim is to increase the customer satisfaction by enhancing the fit between products and their users in the respective context of use. Further virtualisation of user-centred design processes holds the potential to convey the concepts of frontloading and predictive engineering from classical product engineering. Our vision is to facilitate a comprehensive consideration of user-product interactions in virtual product engineering operationalised by the mission to develop methods and tools to assess and design user-product interactions according to physiological and psychological aspects. A variety of work has already been done to model musculoskeletal user groups, to configure, predict, simulate and optimise physical user-product interactions, to integrate such models into CAD or to map individual subjective values to product design. Nevertheless, there are still research areas to be addressed to enable a comprehensive implementation of the mentioned approach. These are discussed in the present contribution.

Nowadays, topology optimization and lattice structures are being re-discovered thanks to Additive Manufacturing technologies, that allow to easily produce parts with complex geometries.

The primary aim of this work is to provide an original contribution for geometric modeling of conformal lattice structures for both wireframe and mesh models, improving previously presented methods. The secondary aim is to compare the proposed approaches with commercial software solutions on a piston rod as a case study.

The central part of the rod undergoes size optimization of conformal lattice structure beams diameters using the proposed methods, and topology optimization using commercial software tool. The optimized lattice is modeled with a NURBS approach and with the novel mesh approach, while the topologically optimized part is manually remodeled to obtain a proper geometry. Results show that the lattice mesh modelling approach has the best performance, resulting in a lightweight structure with smooth surfaces and without sharp edges at nodes, enhancing mechanical properties and fatigue life.