Systems thinking is vital for engineering of nowadays systems characterized by system spanning interactions and an incresing amount of functions. Systems Engineering (SE) represents an interdisciplinary approach, gaining extensive attention to cope with increasing system complexity. Implementation of SE in existing organizations and processes, however, is facing challenges. As a matter of course there is not out of the box concept to be used, in fact definitions and understandings seem to be based on the background and experience of the individual or organization und differ widely. Thus, motivations and expectations of practitioner are manifold and support to adapte and implement SE-methodolgies is needed. Research presented in this contribution picks up the need to provide orientation for individuals, engineering teams and project managers when implementing SE and to address the specific context in that engineering is carried out. Objective is to describe the core idea of SE by a consistent set of principles. This set is used to build up a context specific understanding of SE as a foundation to introduce new methods and procedures in existing method ecosystems.

Aviation strives today to include environmental and social considerations as drivers for decision making in design. This paper proposes a serious game to raise awareness of the value and cost implications of being ‘sustainability compliant’ when developing aerospace sub-systems and components. After describing the development of the game, from needfinding to prototyping and testing, the paper discusses the results from verification activities with practitioners, revealing the ability of the game to raise sustainability awareness and support negotiation across disciplinary boundaries in design.

The control shifting between a human driver and a semi-autonomous vehicle is one of the most critical scenarios in the road-map of autonomous vehicle development. This paper proposes a methodology to study driver's behaviour in semi-autonomous driving with physiological-sensors-integrated driving simulators. A virtual scenario simulating take-over tasks has been implemented. The behavioural profile of the driver has been defined analysing key metrics collected by the simulator namely lateral position, steering wheel angle, throttle time, brake time, speed, and the take-over time. In addition, heart rate and skin conductance changes have been considered as physiological indicators to assess cognitive workload and reactivity. The methodology has been applied in an experimental study which results are crucial for taking insights on users’ behaviour. Results show that individual different driving styles and performance are able to be distinguished by calculating and elaborating the data collected by the system. This research provides potential directions for establishing a method to characterize a driver's behaviour in a semi-autonomous vehicle.

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.

The aim of this paper is to show to how far VR technology can help in the implementation of methods in product development. First, an overview of the product development approach and VR technology is given. Then, an evaluation scheme is developed to examine product development methods for their VR suitability. Finally, the results are evaluated and recommendations for future research are given.

Requirements represent a central element in product development. The large number of requirements inevitably results in an increased susceptibility to errors, an expenditure of time and development costs. The associated problems motivate the application of Artificial Intelligence in the form of Natural Language Processing (NLP). In Requirements Engineering one main task is the classification of requirements which serves as the input in architectural models e.g. in SysML. In mechanical engineering there is still little overview regarding the interface between requirements classification and modelling. This paper provides an overview of the requirement classes and entities used in the literature and analyses their utilisation in modelling. Existing requirements classes usually do not offer the flexibility to be transferred to other domains. However, basic structures can be adopted from those classifications. This enables a clear assignment of existing classes to object classes in modelling. Resulting from the conducted literature study the observed predominant focus of research on the software industry requires an extension of the existing requirement classes and entities to enable further use and transfer to mechanical engineering.

The work introduced two novel multiscale multifunctional tire designs developed using the Domain Integrated Design (DID) method and modelled with the LatticeQuery geometric modelling software. Furthermore, this research validates the meta-level parameter “interaction area” proposed for selecting biological analogy in the DID method. These two use cases were simulated with Abaqus. The concepts covered in this work are an example of multi-functional design. The obtained results validate the meta-level parameter derived from the DID methodology.

To respond to today's needs, engineers must be able to develop sustainable and environmentally compatible products and systems. To do so, they have to carry out new or changed activities and tasks within the product development process and therefore have to obtain new or changed competences. This publication examines which specific competences from the competence groups system thinking and communication are especially important for the development of Ecodesign products apart from technical know-how and should thus be included in a future higher education engineering course.

The use of Additive Manufacturing (AM) can bring opportunities for industry, but several challenges need to be addressed, specifically the digital infrastructure comprising the AM value chain. A combination of a systematic literature review and an industrial use case study concludes that there is low consideration of the digital infrastructure in Design for Additive Manufacturing (DfAM) methods and tools which has a negative impact on the industrialisation of AM. It is therefore recommended that further studies are to be made on how to manage the digital infrastructure in DfAM processes.

Aspect-based sentiment analysis (ABSA) provides an opportunity to systematically generate user's opinions of specific aspects to enrich the idea creation process in the early stage of product/service design process. Yet, the current ABSA task has two major limitations. First, existing research mostly focusing on the subsets of ABSA task, e.g. aspect-sentiment extraction, extract aspect, opinion, and sentiment in a unified model is still an open problem. Second, the implicit opinion and sentiment are ignored in the current ABSA task. This article tackles these gaps by (1) creating a new annotated dataset comprised of five types of labels, including aspect, category, opinion, sentiment, and implicit indicator (ACOSI) and (2) developing a unified model which could extract all five types of labels simultaneously in a generative manner. Numerical experiments conducted on the manually labeled dataset originally scraped from three major e-Commerce retail stores for apparel and footwear products indicate the performance, scalability, and potentials of the framework developed. Several directions are provided for future exploration in the area of automated aspect-based sentiment analysis for user-centered design.

The climate change and the new regulations imposed to slow down this process have pushed major actors around the world to apply sustainable measures in order to meet governmental obligations. The packaging industry has a major role in fighting climate change and the environmental social and financial disasters. In fact, packaging requires substantial number of natural resources and is often disposed of in ways that harm the environment. Supply chain managers realized that packaging design is the root to solve all the problems packages create throughout their entire life cycle. Therefore, a thorough study about influencing the design process should be prioritized. This paper provides a systematic review of industrial packaging eco-design applied to the supply chain. It aims to conceptualize the definition of industrial packaging eco-design and supply chain sustainability to categorize main parameters to its implementation and to identify the limitations of current research and its prospects.

The biggest advantage of Additive Manufacturing is the individualization of products. Mass Customization is well known as a promising future application. The use of Additive Manufacturing for assembly groups is mostly not reasonable, however combining it with conventional manufacturing processes can lead to new opportunities.

This paper works out concepts to join, by using similar material combinations, an injection molded part with an additive deposited geometry by the Fused-Deposition-Modeling (FDM) process. Therefore, two of the main industrially used polymers, acrylonitrile butadiene styrene (ABS) and polypropylene (PP), are selected for further study. In particular, this investigation focuses on the procedural potentials and surface preparation of the injection molded part. By the variation of adhesive bonding, the fusion of similar materials can be identified and tested in several series of testing.

First in general a direct joining function by the FLM process will be tested. After proving this hypothesis, the results will be summarised in a recommendation of joining similar materials, which are manufactured in different ways.

Prototyping is a well-established and valued design process activity. However, capturing prototypes and the tacit knowledge that led to and was gained from their creation is a challenge. Beyond that, questions remain on how best to utilise that captured data. This paper looks at how one can exploit and generate insights from data that has been captured, specifically looking at graph databases, the network analysis techniques they permit and the differing fidelities of visualisation and interactivity that they enable.

In the realm of process engineering, the pursuit of sustainability is paramount. Traditional approaches can be time-consuming and often struggle to address modern environmental challenges effectively. This article explores the integration of generative AI, as a powerful tool to generate solution ideas and solve problems in process engineering using a Solution-Driven Approach (SDA). SDA applies nature-inspired principles to tackle intricate engineering challenges. In this study, generative AI is trained to understand and use the SDA patterns to suggest solutions to complex engineering challenges.

Current development of renewable energy systems (RES) is characterised by an increasing participation of citizens in the upstream decision-making process. These citizens can be future users of the RES but also members of a Renewable Energy Community that develop RES. They can be at the same time Renewable Energy producer, investor and consumer. Moreover, several type of businesses and terms are used to cope with social innovations within the energy sector: local renewable projects, sustainable energy communities or community of renewable energy production. So, actors' engagement opens new solutions for designers who are induced to share alternatives before making decisions. They usually impose constraints since the early phases of the design process. This approach implies for designers to consider new criteria related to citizens motivations and barriers. This paper presents a study to define the main factors that drive people to contribute in social innovation schemes for clean-energy transition. After a state of the art, a survey about 6 main factors and 18 criteria is presented. The analysis based on the responses from 34 participants (i.e. experts) reveals 2 most important factors of motivation and 2 principal barrier sources.

The amount of information in our society and its opportunities have given rise to Big Data research. The systems supplier industry needs suitable tools and methods to ensure the harvest and utilization of Big Data in their product development. This paper used Systems Thinking to analyze the current state in the industry and suggested leverage points for further research direction. The findings suggest that the research project should emphasize the industry cases, the collaboration between the companies and academia, develop a Big Data systems architecture, and maintain a socio-technical view.

Scenario planning is often used in design practice to foster futures thinking, reduce uncertainties and improve decision-making. Scenarios are especially relevant for innovation activities in manufacturing companies, such as technology development, a particularly uncertain process where many trade-offs occur. This study is, to the authors knowledge, the first to empirically measure the effect of scenarios in decision-making quality, in the context of technology development. In a quasi-experiment, engineers from a manufacturing company and university students were independently asked to analyse a trade-off situation between environmental and financial aspects of a technology concept, with and without scenarios. The quality of decision-making quality for control and experiment groups was measured through a standardized questionnaire. The results show that scenarios had a positive impact in 6 of the 7 quality decision-making practices (QMDP), although the effect size is small. The results suggest that both expert and novice designers may benefit from using scenario planning when performing early-stage design activities by having awareness of the decision context, a more structured decision process, and clearer decision criteria.

During engineering design, designers employ three types of model: physical, virtual and cognitive. The role and contribution of each is documented in literature albeit fragmented in nature. Consequentially, a gap in understanding exists in terms of how these models and the transitions between them impact the designer and design process. This paper begins to address this through a characterisation of each model class and an appraisal of the transitional pathways including their alignment to seminal design frameworks.

Virtual reality (VR) has been widely used in engineering design in different ways. It has the potential to enhance some design aspects, such as visualization and interaction, but might be incapable of solving the others. There are no consensus or general guidelines on how VR can facilitate design processes. This paper aims to understand how VR is currently used in engineering design at an early stage, so that researchers and practitioners can better know when and how to use VR for efficient design activities. Specifically, this paper reviews the research questions and applications addressed by using VR technology. The study helps identify the design questions currently studied, and gaps to be filled in order to use VR effectively for optimal design outcomes. This review also provides guidelines about when and how to use VR in design research and practices.

Laser Powder Bed Fusion is the most widespread additive manufacturing process for metals. In literature, there are several analytical models for estimating the manufacturing cost. However, few papers present sensitivity analyses for evaluating the most relevant product and process parameters on the production cost. This paper presents a cost model elaborated from previous studies used in a sensitivity analysis. The most relevant process parameters observed in the sensitivity analysis are the 3D printer load factor, layer thickness, raw material price and laser speed.