FuSE Agility as a Foundation for Sound MBSE Lifecycle Management

The objective of this paper is to show how a system composed of many individually designed and manufactured components each with independent descriptive and analytical models of varying definition can be developed and managed by an integrated systems model. Typical engineering design methods require the engineering team to manually coordinate and integrate the engineering domains: electrical, hydraulic, mechanical, software, etc. This effort can take an inordinate amount of time and resources and is rife with errors, which inevitably lead to specification issues. Model-based system engineering (MBSE) is a method used extensively in the military and aerospace industries to reduce component integration and system development time for complex systems. This paper examines methods used to integrate the component models during development of a design for a subsea system. The authors describe the application of a commercially available MBSE toolset extended to integrate with analytical physics based design software. The challenges, advantages, disadvantages, and suggested improvements for integrating the models are explored. The authors discuss how their process supports the domains of system engineering including: requirements, behavior, physical architectures and verification strategies, and how this intimately aligns with the typical engineering domains. Finally, the authors discuss the development of an application programming interface (API) to integrate the models and manage the transfer of data between disparate software tool sets and provide suggestions for future projects of similar complexity. The paper discusses how the methods applied reduce duplicate work and specification errors, achieving a reduction in rework, and ultimately, development time and cost. The MBSE methodology has not typically been applied broadly in energy. This paper highlights a successful deployment of MBSE covering early stages of conceptual design to manufacturing. The API developed to permit seamless integration of multiple systems engineering development tools is unique for this type of application. The interoperability between development tools is highly sought after in the engineering community and enables many advanced capabilities for development teams. Some of these capabilities include: end-to-end traceability, automated model development, automated design verification, and automated document generation and design specification.

The engineering of space systems is a collaborative, iterative process that integrates various domain-specific viewpoints to represent the final system. To ensure consistency across these viewpoints, the European Space Agency (ESA) employs Model-Based System Engineering (MBSE) and Semantic-Based System Engineering (SBSE) methodologies together to improve digital continuity and interoperability across collaborative space system developments. One significant application of semantic engineering in SE is the ESA MBSE Methodology. The ESA MBSE Methodology provides a standardized approach aligned with the European Cooperation for Space Standardization (ECSS), promotes interoperability across MBSE methodologies and tools, and overcomes integration challenges. ESA MBSE Methodology is the input for the Overall Semantic Modeling for Space System Engineering (OSMoSE) which leverages interoperability in the space community. Case studies, such as the EagleEye Earth Observation mission, demonstrate practical applications, highlighting how semantic models enhance efficiency in complex space systems. This paper discusses the importance of semantics and data management in SE and presents a practical solution derived from the ESA MBSE Methodology.

Moving systems engineering's center of gravity from text documents to digital models, model‐based system engineering (MBSE) facilitates collaboration, reduces errors, and improves system understanding, but systems engineers often face challenges when they start working with MBSE, as they need to consider and model textual requirements as a basis for the system architecture. Synchronizing requirements with the system model can address critical questions, such as which requirements are assigned and covered in the system model, what effort is required to meet these requirements, how to manage changes to requirements, and how to effectively trace them in the system. Object Process Methodology (OPM, ISO 19450) is an MBSE language and methodology for modeling systems, which encapsulates function, structure, and behavior within a single model. The research goal is to expand the MBSE methodology by modeling requirements that are linked to system model artifacts. The objective is minimizing misunderstandings between stakeholders’ text‐based requirements and the engineered model while improving the ability to track changes in requirements and artifacts. An OPM‐based model, OPM‐R, which unifies system requirements and architecture, was developed and evaluated through (1) interviews with seven experts who compared the current text‐based approach and the proposed one based on the requirements of three test system models and (2) a researcher diary. Findings indicate that OPM‐R is preferred over the text‐based approach, as it reduces misunderstandings and gaps in requirements, enhancing the ability to trace coverage of system artifacts and track changes in requirements.

One approach to tackle the complexity in the development of cyber-physical systems is system decomposition and modelling in a central system model with model-based system engineering (MBSE). However, MBSE also requires increased development effort due to the high degree of formalisation of the development results using the Systems Modelling Language (SysML). One solution is reusing system elements from model libraries, which requires formalization that allows them to be networked into consistent models. Due to the abstract nature of SysML, the options for formalizing system elements are extremely diverse, meaning that even identical technical system elements are modelled with a different structure by engineers. As a consequence, no standardized structure is maintained and the reuse of system elements from model libraries is very unlikely. This leads to high, redundant modelling efforts as well as a considerable error potential and significantly hinders the economic application of MBSE in mechanical engineering. A standardized structure of the system elements can be ensured through MBSE methodology specific modelling guidelines. Current modelling guidelines for MBSE are based on the SysMLv1 language standard and cannot be used unchanged in SysML v2. Nevertheless, SysML v2 offers great potential for modelling reusable system elements, especially with its synonymous textual and graphical modelling capabilities, enabling the easy linkage of knowledge from various domain-specific tools. Consequently, modelling guidelines based on SysML v2, which guarantee a standardized structure, are required to fully exploit the potential of model libraries in MBSE. To solve this deficit, this paper presents modelling guidelines based on SysML v2 and their application for building reusable system elements.

Systems engineering is a transdisciplinary scientific and applied direction that combines the principles of a systems approach, methods, tools and standards that provide an integrated methodology and relevant technologies for the design and development of complex systems, their comprehensive analysis and verification, efficient and safe use. The modern approach to systems engineering is characterized by an accentuated modeling of systems throughout their life cycle with the ultimate goal of creating their digital twins. It is called model-based systems engineering (MBSE). Consistent integration of MBSE with software engineering leads to the formation of the MBSSE (Model-Based Systems and Software Engineering) direction. This textbook is devoted to this area, the main objective of which is to study the conceptual and scientific-methodological foundations of MBSE and MBSSE, models and methods of life cycle management of systems and software, basic standards of systems engineering, study and mastery of the UML and SysML systems modeling languages and the corresponding modeling tools, study of requirements engineering methods and development of a description of the system architecture, familiarization with the concept of digital twins and their role in MBSE, study of the MBSSE reference model and its relationship with the process standards of systems engineering, study of the methodological aspects of the system and software integration process. The final chapter of the textbook is devoted to the study of the mathematical foundations of systems engineering. The main aspects of the mathematical theory of systems by A. Wayne Wymore, which became an important stimulus for the development of the model-oriented approach in systems engineering, and modern research, including the apparatus of finite automata by David Harel, the formalism of modeling of discrete systems DEVS, research into category theory as a formal mathematical basis for model-based system design are considered. The authors recommend this course as a basic course for training IT professionals.

The complex system engineering in the aerospace domain is undergoing a digital transformation, with Model-Based Systems Engineering (MBSE) serving as the core driving force. By establishing a unified model framework, MBSE has revolutionized traditional development paradigms and significantly enhanced multidisciplinary collaboration and full lifecycle management capabilities. However, MBSE still faces bottlenecks in model standardization, cross-domain integration, and dynamic decision-making. This paper examines MBSE model mappings across key aerospace mission phases: planning, requirement analysis, design, and on-orbit operations. It identifies core AI-empowered scenarios such as intelligent requirement capture, multidisciplinary collaborative optimization, and virtual-physical fusion verification. The study explores the synergistic application of AI and MBSE in aerospace complex system engineering, providing methodological support for the digital transformation and intelligent upgrading of China’s aerospace equipment. The complex system engineering in the aerospace domain is undergoing a digital transformation, with Model-Based Systems Engineering (MBSE) serving as the core driving force. By establishing a unified model framework, MBSE has revolutionized traditional development paradigms and significantly enhanced multidisciplinary collaboration and full lifecycle management capabilities. However, MBSE still faces bottlenecks in model standardization, cross-domain integration, and dynamic decision-making. This paper examines MBSE model mappings across key aerospace mission phases: planning, requirement analysis, design, and on-orbit operations. It identifies core AI-empowered scenarios such as intelligent requirement capture, multidisciplinary collaborative optimization, and virtual-physical fusion verification. The study explores the synergistic application of AI and MBSE in aerospace complex system engineering, providing methodological support for the digital transformation and intelligent upgrading of China’s aerospace equipment.

Nowadays, in software, electronics and automotive industries, it takes 1.5–2 years for a new product to appear, although it takes 3 or even more years to develop new space instruments. The update of higher education system standards is even more conservative. It takes 10 or more years. Because of this, graduates come into the industry with outdated knowledge. Thus, the problem is to synchronize the processes of updating technologies that ensure the creation of innovative products with educational programs. It can be solved by changing the paradigm of products creation based on the synthesis of deep and interdisciplinary educational, scientific, innovative and production activities with the model-based systems engineering software and methodological tools.The existing model-based systems engineering (MBSE) Software (SW) tools based on the Systems Modelling Language (SysML) are complex and expensive. This chapter raises the question, “Is it possible to make use of MBSE SW and methodological tools available to a wide audience of users?” To answer this question, the following MBSE approaches and tools were researched: Quality Function Deployment (QFD), House of Quality (HoQ), and SysML. Consequently, five methodological tools were developed for application during space instruments design and development life cycle stages. Tools are based on SysML, QFD, HoQ improvements and synthesis, and expressed in theoretical and practical algorithms.The theoretical algorithm determines “What” (input and output data) and “How” (by using which systems engineering (including MBSE) tools are methodically analysed at the certain space instruments life cycle stage. The practical algorithm automates the development of SysML diagrams by using data structured in HoQ models and widely available SW. It reduces the time to develop and update SysML requirements diagrams from several days to some minutes and enables implementation of SysML SW by many users. Altogether, the obtained results constitute the software and methodological toolkit (SMT) called “improved Quality Function Deployment for improved House of Quality”.To disseminate the obtained results, educational materials were created and validated during lectures on systems engineering. Lectures were supplemented with seminars and practicum. Practicum was focused on the design and development (D&D) of nanosatellites in the MBSE paradigm as the single project. The results showed that the developed SMT makes it possible to implement the life cycle of the cyber-physical system in the MBSE paradigm in a cost-effective way and a short time—in 6 months, students developed, conducted synthesis and flight tests of CubeSat-format satellite prototype and prepared the project documentation. In addition, students were motivated to study science, technology, engineering and math disciplines, MBSE tools, and become transdisciplinary specialists.In addition, developed SysML requirements models were applied to examine the “Preliminary Design” product life cycle (PLC) stage of different space projects. Such application allowed quick assessment of project results, identifying non-compliance with requirements, conducting beforehand all necessary corrections and generating correct new product documentation. Taking into account the mentioned advantages of the obtained MBSE SMT, it can be concluded that its usage improves the quality and accuracy of current projects and speeds up the planning process of future analogue projects by up to 60%. Consequently, projects (their life cycle stages) can be realized faster by 5–10%.These results allow to recommend for all interested in the innovative D&D of systems to initiate: formation of educational programs based on the project approach and MBSE paradigm; preparation of MBSE materials for online and offline teaching of students and teachers; development of domestic widely available software for the development of integrated SysML models with HoQ models that assures synchronization with CAE/CAD/CAM systems; support these recommendations for the implementation of the above-mentioned research results at educational organizations of different levels. The future research is focused on the application of the developed MBSE methodological toolkit during design and development with numerical modelling and operation of several CubeSat satellites.KeywordsSystems engineeringMBSEParadigmMethodological toolkitSysMLQFDHoQ

Systems Engineering (SE) and in particular Model-Based Systems Engineering (MBSE) are disciplines that are particularly suitable for the development of complex systems. MBSE is therefore often used for developments in the fields of vehicle technology and mobility systems, as these systems are highly complex. In these areas, there is a clear trend in research and development towards innovative and sustainable public mobility systems. For this purpose, vehicles are being developed that are specially adapted for use in the respective mobility systems and are designed to meet the needs of customers. An important feature of vehicles used in such a mobility system, which is intended for the general public, is that the vehicles should be as accessible and barrier-free as possible.The integration of systems that can be used for the barrier-free design of vehicles is also characterised by a high degree of complexity. This is due to the very different requirements that different types of mobility restrictions entail, the technical design of the systems themselves, the interaction of the individual systems and the limitations imposed by the vehicles in terms of payload and installation space. By adding the high degree of complexity of the vehicles themselves, an accessible or barrier-free vehicle therefore represents a system with a high degree of complexity. However, the integration of accessibility elements into an existing vehicle is also associated with a high degree of complexity for the reasons mentioned above.Due to the complexity associated with the barrier-free vehicle system, the use of MBSE to develop vehicles that are as barrier-free as possible seems very sensible. Due to the relatively large proportion of people with mobility impairments, ethical aspects and the legal framework in various countries that prioritise inclusion, the topic of barrier-free mobility is also highly relevant. For these reasons, a closer look at the use of MBSE for the development of accessible vehicles is justified. For the reasons explained above, this article will first analyse the extent to which MBSE is already being used for the development of accessible vehicles. In particular, the methods and tools of MBSE that have been designed specifically for the development of accessible vehicles or that support them are analysed. For this purpose, a systematic literature review is carried out, which shows that there are large research gaps with regard to the use of MBSE for the development of barrier-free vehicles. The next step of the article examines and justifies why there is a need to close the identified research gaps, so that a need for research is identified. Furthermore, the article looks at which approaches exist in the literature that could be used to design MBSE methods and tools that address the development of accessible vehicles. This step also includes an analysis that identifies the gaps and needs in the area of tools for the development of accessible vehicles beyond the MBSE.

This study compares the types and quantities of knowledge that are captured by a model‐based systems engineering (MBSE) approach and a traditional architecting approach to measure the benefits of the MBSE approach in managing the complexity of a robotic space system. The MBSE approach was implemented with Cameo Systems Modeler using Systems Modeling Language (SysML) and applied to architecting an orbiting sample Capture and Orient Module (COM) system concept for a Capture, Containment, and Return System payload concept for potential Mars Sample Return. An architecture framework was established, covering system, subsystem, and assembly levels, along with structure, behavior, data, and requirements perspectives. The COM system architecture was captured in parallel using both the MBSE and non‐MBSE approaches in order to provide a side‐by‐side comparison of the approaches. The approaches were evaluated based on how well each represented the information content of the COM system architecture. A total of 4389 knowledge elements were classified using the Revised Bloom's Taxonomy knowledge dimension and used to quantitatively compare the two approaches. The MBSE approach more completely captured architectural knowledge than the non‐MBSE approach. Limitations to the SysML‐based MBSE approach were also identified, including its ability to fully represent certain high‐level conceptual, procedural, and metacognitive knowledge such as design principles, design approaches and rationales, risks, development strategies and rationales, organizational core competencies, and requirement verification methods. The overall results demonstrate the benefits of MBSE in managing the complexity of robotic space systems and strengthen the case for adopting MBSE within the systems engineering community.

Combine the key concepts of MBSE with the essentials of their practical application. This tutorial is designed help you leverage model‐based techniques to better meet the engineering challenges of analyzing stakeholder needs and defining system solutions. The tutorial uses a practical top‐down system analysis and design example and exercise to explore the application of layered model‐based systems engineering (MBSE) to system definition challenges. It examines the range of views available to the systems engineer for understanding and communicating design choices and provides a practical introduction to constructing the model and generating each representation. As the analysis and design advances, the engineer will use a wide variety of views drawn from traditional and SysML representations to portray aspects of the model and gain understanding of stakeholder concerns and the design choices to be made. This tutorial works for both new and experienced systems engineers, capability analysts and others working on an integrated project team, and program/project/capability managers. While a basic understanding of the systems engineering process is assumed, the MBSE framework and approach provide the foundation for those not experienced in systems engineering. The detailed discussion of MBSE methodology and model representations including SysML and traditional SE products delivers value for all but the most experienced model‐based systems analysts and engineers. This is an MBSE methods, models, and representations tutorial, not a tool tutorial. The focus is on the practical application of essential MBSE for project success. The concepts taught and methods shared are applicable regardless of the systems engineering tools the attendee may choose.

As Model-Based Systems Engineering (MBSE) was applied to the Electric Multiple Unit (EMU) braking system control logic, a preliminary exploration was conducted for bullet train braking system control logic research using an MBSE practice framework. The framework mainly includes the requirement analysis phase, functional analysis phase, and design phase. Systems Modeling Language (SysML) was used as the modeling language, and Cameo Systems Modeler (CSM) was employed as the modeling tool. By integrating the EMU braking system control logic and utilizing a top-down design approach, the implementation of MBSE in the bullet train braking system was analyzed and studied. The results show that, according to the MBSE practice framework, a unified description of the requirement analysis, functional analysis, and design synthesis of the EMU braking system control logic can be achieved. Additionally, the correlation and traceability between models can be established.

The model based systems engineering (MBSE) approach describes a system using consistent views to provide a holistic model as complete as possible. MBSE methodologies end with the physical architecture of the system, but a physical model is clearly incomplete without the study of its associated physical laws and phenomena related to the whole system or its parts. However, the computational demands could be excessive even for modest projects. Dimensional analysis (DA) is common in fluid dynamics and chemical engineering, but its application to systems engineering is still limited. We describe an engineering methodological process, which incorporates DA as a powerful tool to understand the physical constraints of the system without the burden of complex analytical or numerical calculations. A detailed example describing a microantenna is presented showing the benefits of this approach. The selected example describes a problem rarely covered in modern expositions of DA in order to show the wide benefit of these techniques. The information provided by this analysis is very useful to select the best physically realizable architectures, testing design, and conduct trade‐off studies. The complexity of modern systems and systems of systems demands new testing procedures in order to comply with increasingly demanding requirements and regulations. This can be accomplished through research in new DA methods. Finally, this article serves as a fairly comprehensive guide to the use of DA in the context of MBSE, detailing its strengths, limitations, and controversial issues.

Circularity measures like repair, remanufacture and refurbish provide options to enhance the life cycle and thus the sustainability of a product besides measures, which primarily concentrate on the end-of-life of a product. To integrate the concept of circular value creation engendered by such measures in the development process of a product, we extended the idea of modelling standard life cycles as introduced by Block et al. [3]. This extension introduces the novel notion of undesired states within a product’s life cycle. Undesired states can be dissolved with the help of circularity measures. A Model Based Systems Engineering (MBSE) approach was developed to implement this strategy. The resultant modelling approach is implemented in form of a software tool. The system is evaluated within an automotive development project revealing a significant advantage in contrast to previous methods.

This article proposes a novel methodology aimed at streamlining the system’s development process. By examining existing state-of-the-art approaches and the capabilities inherent in Model-Based Systems Engineering (MBSE) tools, the article introduces a methodology centered around transforming a descriptive Systems Modeling Language (SysML) model into a digital twin. This virtual representation of the physical asset leverages real-time data and simulations to mirror its behavior and characteristics. When integrated with MBSE, this synergy allows for a comprehensive and dynamic approach, enhancing innovation by providing a holistic and adaptable framework for designing, analyzing, and optimizing complex systems throughout their lifecycle. The practical application of this Real-Time Communication and Data Acquisition (RT-CDA) methodology is implemented in a context and operational scenario of an electric unmanned autonomous vehicle employing both Software-in-the-Loop (SITL) and Hardware-in-the-Loop (HITL) approaches. The methodology empowers systems engineers to iteratively update and refine their system model’s fidelity based on real-world testing insights. The article specifically demonstrates the real-time communication capabilities achieved between an electric unmanned autonomous vehicle (a physical asset) and a descriptive (SysML) model, illustrating the real-time data aspect integral to the concept of a digital twin. This study serves as a foundation for future endeavors, envisioning real-time communication among virtual and physical models to construct comprehensive digital twins of complex systems to predict behavior and performance.

Model-based systems engineering (MBSE) is a discipline of systems engineering in which the model forms the heart of all the systems engineering activities and is the basis of many of the project artefacts. Systems modeling is no longer viewed as simply a “good idea” but is becoming an increasingly important part of any systems engineering project. The application of MBSE is becoming well understood at the systems level; however, there is a lack of research and subsequent industrial application at the system of systems (SoS) level. This paper presents a model-based approach to requirements engineering for SoSs. The approach is derived from an MBSE approach to requirements engineering and therefore represents current best practice in SoSs in terms of established standards and research. This paper builds upon and is an evolution of the initial foundations for model-based requirements engineering for systems of systems that were published in an earlier paper.