The evolutionary development of advanced systems (AS) leads to a necessary rethinking of how they can be supported methodically and in terms of processes in product development. Advanced systems engineering (ASE) offers a novel and holistically adaptive approach to facing such challenges in a structured way. However, many of the ASE use cases relate to the development of systems as products, product networks or individual projects. The additional consideration of entire modular product families within AS offers a further decisive advantage for companies, organisations and the people in ASE. By considering modular product families along the entire life cycle in a product family engineering (PFE), the approaches of ASE can bring their impact and potential to additional system levels occurring when considering product families. The systems, which become complex through variety and collaboration, are broken down into their system elements in a structured way and prepared for a common interdisciplinary understanding, as conveyed by ASE. In this paper, the PFE is presented in excerpts using examples of various aspects and points in time of the product’s life as a complementary approach for ASE.

Over the last decades, modeling and simulation have become central methods in engineering design. Today’s technologies enable previously unachievable levels of sophistication and accuracy. However, if decision-makers are unaware of the confidence they can place in models and simulations (M&S), they either fail to leverage their potential by not involving them in processes or make judgments based on unreliable results. Assessments to evaluate M&S exist, but factors that enable decision-makers to have confidence and improve acceptance of using M&S need to be researched in more detail. Therefore, a literature review analyzing design requirements and an online survey to measure factors associated with confidence were conducted. As a result, the survey identified nine predictors of confidence: (1) capability, (2) history, (3) validity, (4) reliability and (5) accessibility of the model. Further, (6) integrity and (7) competence of the modeler, as well as (8) trusting nature and (9) risk awareness of the stakeholder were identified. Having confidence in M&S results significantly increases the reliance on them and leads to better-informed decision-making. Therefore, based on the findings, a framework and an initial application model were developed. The results were initially evaluated and are described.

The use of system models within model-based systems engineering (MBSE) is essential for improved communication or system documentation. Previous publications have investigated further reuse of these system models, for example, transforming them directly into discipline-specific models for reuse. The authors refer to this as the term “Utilization” of system models. It aims the compensation of modelling efforts and a further integration of linked models within MBSE. Motivated by a lack of common understanding of this term, a systematic literature review of the state of the art is presented. With this systematic overview, a definition and classification system for different use cases and system life cycle stages are created. These are key results to support engineers and researchers in adopting existing or discovering new utilization approaches. This supports the mission of advanced systems engineering and aims the identification of new research directions coming along with SysML v2 and the advanced systems engineering methods.

Objective of this contribution is to present the use of Model-based Systems Engineering within the engineering design community. Based on a differentiation between SE and MBSE, the definition of three core MBSE elements, namely modelling method, modelling language, and modelling tool as well as the three major aspects of a consistent system model (requirements, behaviour, and structure) a structured review is conducted, focussing on the understanding and motivation as well as the modelling of systems. The review includes 93 publications from Design Society library and proceedings of the CIRP Design conferences during the period from 2011 to 2022. The review points out, that there is an increasing application of MBSE within the engineering design community, mainly focussing on architecture definition or combined engineering activities. Only a small portion of works (16 publications) are providing a consistent approach as these publications link all aspects of the system model and consider all three MBSE elements. It can be concluded, that there is a diffuse understanding of MBSE and different motivations are given to apply more formal system models as well as modelling tools.

Model-based systems engineering (MBSE) aims at creating a model of a system under development, covering the complete system with a level of detail that allows to define and understand its behavior and enables to define any interface and work package based on the model. Once the model is established, further benefits can be reaped, such as the analysis of complex technical correlations within the system. Various insights can be gained by displaying the model as a formal graph and querying it. To enable such queries, a graph schema is necessary, which allows to transfer the model into a graph database. In the course of this paper, we discuss the design of a graph schema and MBSE modeling approach, enabling deep going system analysis and anomaly resolution in complex embedded systems with a focus on testing and anomaly resolution. The schema and modeling approach are designed to answer questions such as What happens if there is an electrical short in a component? Which other components are now offline and which data cannot be gathered anymore? If a component becomes unresponsive, which alternative routes can be established to obtain data processed by it. We build on the use case of qualification and operations of a small spacecraft. Structural elements of the MBSE model are transferred to a graph database where analyses are conducted on the system. The schema is implemented by means of an adapter for MagicDraw to Neo4J. A selection of complex analyses is shown in the example of the MOVE-II space mission.

This research work presents a methodological support for the specification of complex products. This is achieved by developing a specification structure in a MBSE environment. The new method draws on success factors of complex product specification, principles of MBSE and the explanatory model of PGE – Product Generation Engineering. For evaluation, the method is applied within a student development project. A high applicability and the realization of novel synergies for coping with continuously increasing product complexity is demonstrated.

Modular design allows to reduce costs based on scaling effects. However, due to strong alternating effects between the resulting modules and products, methods and tools are required that enable engineers to use specific views in which the respective information can be linked and retrieved according to the situation. Within the scope of this paper, the model-based systems engineering (MBSE) approach is used to model the complex real-world problem of vehicle modular kits. The aim is to investigate the potentials in this context, how modular kits and products can be efficiently modeled and finally how MBSE can support modular design. In order to investigate this in detail, two extensive studies are carried out in a company over a period of three years. The studies show that modular kits lead to an increased complexity of development. Across industries and companies, the demand for reference product models is shown, which facilitate the unification of inhomogeneous partial models and serve as a knowledge repository for the development of future product generations. On this basis, a framework is derived which enables the reuse of large proportions of the product models of previous product generations. This framework is evaluated on the basis of five case studies.

This paper demonstrates a concept for a cross-domain strategy for the sustainable processing and dissemination of product information. Important functional product features are explicitly mapped as working surface information in different domain tools with the help of the contact channel method and are integrated using a model-based systems development approach. The approach uses established state of the art design tools and can be integrated into existing product development processes, knowledge based engineering concepts and product (system) lifecycle management strategies.