Design is increasingly influenced by digitalisation yet differs largely across domains. We present synergies between the works of UX designers and data scientists. We can utilise personas to represent users and their behaviours, or synthetic populations to represent agent groups. Despite sharing characteristics, their synergies have not been explored so far. We propose a workflow and test it in the urban mobility context to link a synthetic population of Paris with a set of contextual personas. This builds the basis for an integrated approach for designing urban mobility across fields.

This paper investigates which activities and success factors can be identified for the data-driven validation of functional requirements. For this purpose, a case study is conducted at a machine tool manufacturer. To validate functional requirements by analyzing data of reference products, these activities must be performed iteratively: basic work, interdisciplinary work, programming and check results. For the successful execution of data-driven validation, the success factors: data origin, acceptance, data quality, knowledge about data and combination of domain knowledge must be considered.

The implementation of Digital Twins has become a common task for many industrial companies to ensure a sufficient digitization of their products and maintain competitiveness. This results in the question of how to compensate additional effort caused by designing Digital Twins. With this paper, an approach for this compensation is presented by creating Digital Twin behaviour through utilizing SysML diagrams and directly derivate usable code from them for a further implementation. This offers a part solution of lowering the threshold for using MBSE and increasing its benefits.

Novel concepts are essential for design innovation and can be generated with the aid of data stimuli and computers. However, current generative design algorithms focus on diagrammatic or spatial concepts that are either too abstract to understand or too detailed for early phase design exploration. This paper explores the uses of generative pre-trained transformers (GPT) for natural language design concept generation. Our experiments involve the use of GPT-2 and GPT-3 for different creative reasonings in design tasks. Both show reasonably good performance for verbal design concept generation.

In an increasingly interconnected world, changes of uncertain nature and impact affect the functioning of human societies that depend on health, ecological, and economic systems. The proposed framework for systems-of-systems resilience explains ways of accommodating and responding to these challenges while encompassing the interfaces of the health, environment, and economy domains and their effect on communities. Resilience is defined as a continuous process and we distinguish between four system properties, five resilience capacities, and a variety of system activities.

Aircraft vehicle systems enable an aircraft to fly safely throughout a mission. Generating feasible vehicle system architectures at the aircraft concept design phase is complex. Aspects from various complex systems theories are used to provide different insights into this complexity. To address this complexity, a framework based on industrial reality that can used recursively is presented. The framework employs various design theories to harness the complexity of vehicle system design at the concept design phase of an aircraft.

Through-Lifecycle Whole Design Design Optimisation is widely considered one of the future approaches to solving design problems featuring prominently in Model-Based Systems Engineering, Set-Based Design and Digital Twins. Yet, design optimisation remains siloed optimising for design subsets. In this paper, we review academic literature and a series of case studies to uncover the challenges in achieving Through-Lifecycle Whole Design Design Optimisation. This is followed by action research that has investigated the application of software deployment toolchains to overcome the challenges.

Requirements changes are a leading cause for project failures. Due to propagation effects, change management requires dependency analysis. Existing approaches have shortcomings regarding ability to process large requirement sets, availability of required data, differentiation of propagation behavior and consideration of higher order dependencies. This paper introduces a new method for advanced requirement dependency analysis based on machine learning. Evaluation proves applicability and high performance by means of a case example, 4 development projects and 3 workshops with industry experts.

Increasing system complexity can be controlled by using systems engineering processes. INCOSE defines processes with inputs and outputs (artifacts) for this purpose. Specific SE roles are used to organize the tasks of the processes within the company. In this work, the responsibilities for artifacts are evaluated by means of the RACI scheme and examined by a cluster analysis and discussed for a SE transformation project with a German automotive OEM. As a result of the study, the optimal composition for systems engineering teams is identified and the systems engineering roles are prioritized.

Effect chain modeling approaches are applied to model cause-effect relations and analyze affected elements and dependencies. In this paper a systematic literature research is conducted to derive main characteristics and limitations of existing approaches. Then, the Model-based Effect Chain Analysis (MECA) method is introduced. Evaluation proves applicability of the method by means of a case example. This is done in the context of a project with a German automotive company. In the project 66 workshops were conducted to model certification-compliant effect chains in accordance to the UN ECE 156.

In addition to the known approaches for product development new or supplementary approaches have emerged. An important approach in this field is Systems Engineering (SE) and Model-Based Systems Engineering. Through these approaches, new procedures, level-focused description concepts and terms come into product development. However there are still some uncertainties as to how the known approaches of product development can be combined with the SE approaches. This paper aims to show how the known development approaches can be extended by and integrated with SE approaches.

The process of generating FMEA following document-centric approach is tedious and susceptible to human error. This paper presents preliminary methodology for robotic manufacturing process modelling in MBSE environment with a scope of automating multiple steps of the modelling process using ontology. This is followed by the reasoning towards automatic generation of process FMEA from the MBSE model. The proposed methodology allows to establish robust and self-synchronising links between process-relevant information, reduce the likelihood of human error, and scale down time expenses.

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.

MBSE and SysML are increasingly finding their applications in industry as well as in academia. The reuse of the information described in SysML models depends, among others, on the modelling methods, management of dependencies between elements and on the needed remodelling effort. In this paper, a modelling method is presented that address the reuse of SysML models and descriptions as well as reuse of model variants in SysML. A case example is presented to explain the modelling methods and the gained experience is summarised in the form of general recommendations for further use.

In a smart product-service system (smart PSS), non-tangible services are bundled with tangible products as well as options for information and communication technologies. Enterprises offer smart PSS in order to provide added value for customers and deal with increasing competitive pressure. However, the development of these complex systems also presents enterprises, especially SMEs, with challenges. In order to identify the challenges in the development of smart PSS and requests for corresponding support, a multi-method study was conducted with eighteen participants from German SMEs.

The design of large-scale engineered systems relies on the extensive use of models. Although there are few papers that study design review practices, we did not find any on model-based design reviews. Thus, we undertook a survey to collect current practices and challenges. We found that reviews are mainly synchronous co-located or remote meetings that involve various profiles who need to access and share models, but that they pragmatically give them up and prefer to comment on PowerPoint-like slides containing screenshots of models except when the meeting gathers only experts in model-based design.

This article aims to contribute to the knowledge on product/service system (PSS) design practice as follows. First, a new rationale for why PSS design in practice often does not exploit its full potential is given based on a theory on inseparability of services. Second, a representation of the dependencies between product design parameters (DPs) and service DPs in a form of potential-dependency knowledge base is proposed as a remedy. Third, reusability of the knowledge captured from product-service integration across sectorial borders is shown with PSS design at a complex product manufacturer.

The modular lightweight design attempts to reconcile the partially conflicting goals between modularization and lightweight design in order to establish a harmonized modular hybrid design. This requires a close exchange of the resulting development data between the two areas. In this contribution a concept for an interface for the data exchange between system models and FEM models is presented and successfully implemented in the Cameo Systems Modeler and applied to examples from the aircraft cabin. With the interface the homogenization step of modular lightweight design can be performed.

The main focus of this paper is the exploration of fault accommodation possibilities in the context of function development. Faults occur in complex technical systems and may lead, if no accommodation entities or processes are present, to catastrophic failure. Several entities and processes exist and are applied, but mainly on the concrete levels. Faults very often concern more than one physical domain and accommodation possibilities are present in many physical or even non-physical domains. This paper explores this specific challenge and proposes an initial collection of countermeasures.

One of the main current threats for producing companies is the possibility of cyber-space attacks. Due to several reasons, industrial companies need to connect their plants over some kind of networks. Obviously, today many approaches from information technology (IT) exist which will greatly reduce the danger of attacks. Still, no producing company can completely rely on these IT solutions. This paper proposes a systemic approach to design processes and products for increased cyber security. This approach is based on an attack model and is explained based on an automated storage system.