Model-Based Systems Engineering Methodology Research Articles

A novel system architecture of intelligent adaptive cruise control for safety aspects

Following industrial and safety standards for autonomous vehicles, Adaptive Cruise Control (ACC) is a widely employed Advanced Driving Assistance System (ADAS) feature in modern vehicles. ACC currently facilitates speed control based on the driver's desired speed value. This study introduces a significant advancement: the Intelligent Adaptive Cruise Control (IACC) feature, accompanied by the development of a control system architecture poised to make noteworthy contributions in scientific, economic, and social dimensions through its integration into autonomous vehicles. The design incorporates crucial elements such as Traffic Sign and Limit Recognition (TSLR), ADAS features, and Global Positioning System (GPS) data, primarily enhancing driver safety through these supportive features. The main focus revolves around designing a system architecture that accommodates these new features to ensure safe driving. The creation of the IACC system architecture is approached using Model-Based System Engineering (MBSE). Through this MBSE methodology, system-level diagrams were crafted, and security considerations were systematically addressed. Several scenarios were devised to evaluate the contributions and were subsequently tested and analyzed. The architecture places particular emphasis on the security aspects of IACC. Leveraging the TSLR feature, the system interprets traffic signs and acquires speed limit data from external sources, preventing the vehicle's speed from exceeding the specified limit. The comparison between the set speed value and the speed limit ensures adherence to safety parameters. In such scenarios, the system enhances driver support on winding roads by utilizing GPS data to recognize the vehicle in front. This approach significantly elevates the reliability of the IACC feature, particularly in terms of safety sensitivity, when compared to other adaptive cruise control concepts.

Semantic-based systems engineering for digitalization of space mission design

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.

Development of a Body Weight Support System Employing Model-Based System Engineering Methodology

Partial body weight support systems have proven to be a vital tool in performing physical therapy for patients with lower limb disabilities to improve gait. Developing this type of equipment requires rigorous design process that obtains a robust system, allowing physiotherapy exercises to be performed safely and efficiently. With this in mind, a “Model-Based Systems Engineering” design process using SysML improves communication between different areas, thereby increasing the synergy of interdisciplinary workgroups and positively impacting the development process of cyber-physical systems. The proposed development process presents a work sequence that defines a clear path in the design process, allowing traceability in the development phase. This also ensures the observability of elements related to a part that has suffered a failure. This methodology reduces the integration complexity between subsystems that compose the partial body weight support system because is possible to have a hierarchical and functional system vision at each design stage. The standard allowed requirements to be established graphically, making it possible to observe their system dependencies and who satisfied them. Consequently, the Partial Weight Support System was implemented through with a clear design route obtained by the MBSE methodology.

Model‐Based Systems Engineering (MBSE) Application in Nuclear Power Plants (NPP)

AbstractCompanies in the nuclear power sector are constantly being challenged to improve their safety and reliability due to increasing complexity arise from evolving safety regulations, long production life, interdisciplinary collaboration, and the need for analyzing the impact of the changes in an operational life cycle. Recognizing these challenges, the paper proposes a transition to Model‐Based Systems Engineering (MBSE) as a transformative solution to improve the management of such complex systems. With this objective, this paper presents a workflow implementation that demonstrates the MBSE methodologies to define a concept model, system architecture, impact analysis, safety and reliability analysis, and operational decision‐making of Nuclear Power Plants (NPP). The paper concludes that MBSE provides a potent approach to managing NPP by employing graphical models to develop interrelated systems that has strong adaptability to heterogeneous environments and regulatory changes. The simulation results demonstrated an NPP life cycle, impact analysis, and a test case for model‐based safety and reliability analysis for regulatory compliance, operational efficiency, balance safety, and informed decision‐making in NPP. The study also leads to a number of interesting directions of future work such as synchronization through Product Lifecycle Management, integration with Building Information Modeling, Model‐Based Commissioning/Decommissioning, and Model‐Based Cyber System Security tailored for nuclear power systems.

Model‐Based Systems Engineering Approach for Designing an Artificial Magnetic Field Generator System for Spacecraft Radiation Protection

AbstractThe hazardous environment of space, dominated by cosmic and solar radiation, poses a significant threat to spacecraft and their occupants. Traditional radiation shielding methods, like passive materials, have limitations in weight and effectiveness. An artificial magnetic field generator system emerges as a promising solution to replicate Earth's magnetosphere, providing a protective magnetic shield against harmful radiation. (Dick, Launius, 2007) This paper presents a Model‐Based Systems Engineering (MBSE) approach to the holistic modeling and design of such a system.Utilizing the MBSE approach, this study models the system's components, their interactions, and the offered services, incorporating Radiation Monitoring, Magnetic Shielding, Power Management, System Health & Diagnostics, and Crew Communication services. The conceptual data model captures key entities and their relationships, ensuring a coherent integration of the system's parts. The activity diagram illustrates the operational flow, providing clarity on the system's dynamic behavior under varying radiation conditions and power reserves. A services taxonomy is developed to hierarchically categorize and ensure the comprehensive functionality of the system.The application of MBSE methodology provides numerous advantages, including a unified visualization of the system's complexities, enhanced stakeholder communication, and a streamlined validation and verification process. Furthermore, the flexibility inherent in the MBSE approach ensures that the system can be easily updated or scaled based on advancements in technology or changing mission requirements. (ECLIPSE Suite, 2022) The MBSE approach's application to the design of an artificial magnetic field generator system for spacecraft presents a robust and systematic method to ensure optimal performance, safety, and adaptability in the perilous realm of space.

ASPICE compliance development of Cyber‐Physical Systems by using Model‐Based Systems Engineering

AbstractCurrent automotive Industry is facing numerous challenges. Business model is transitioning from ownership to shared mobility. Mobility of the future is becoming smarter, safer, more secured and connected. Distributed interconnected automotive systems will deliver added‐value mobility services. In the meantime, industrial standards require description of systems engineering practices as well as the practices justification. Automotive SPICE (ASPICE), a standard of software development best practices for automotive industry, for example, was one of the first to support the development of system and software now include hardware and cybersecurity. Traditional systems engineering development approaches are not any more appropriate. The current automotive system complexity requires new approaches like Model‐Based Systems Engineering (MBSE), using modeling and simulation. To address compliance to industry standards, traditional quality approaches consisting of or defining a quality system with a set of processes (e.g. Requirement elicitation process, documentation process…) are no more sufficient. Addressing these challenges require a digital transformation with two pillars. The first pillar is an MBSE methodology such as Cyber MagicGrid (Dassault Systèmes MBSE method) to define a set of best practices to develop a system. The second pillar is a quality management system that relies on the MBSE methodology rather than on a set of enterprise processes to address compliance with standards. Benefits of this approach is in acceleration of the digital enterprise transformation which is achieved by capitalizing the know‐how and considering the industry standards constraints.

Applying MBSE in Space Based Systems Development

AbstractA core challenge in modern systems engineering is executing the Digital Transformation to produce Digital Engineering (DE) products that meet traditional program needs. Model Based Systems Engineering (MBSE) focuses the formal application of models to support the systems engineering process, but is often difficult to apply in practice due to a lack of a well‐defined methodology. This paper first introduces an openly available MBSE methodology concentrating on a development process for system architecture models, a style guide defining how the process steps are executed, and a validation suite which serves as a tool to help execute development. Then, this paper describes the experience in applying this process to a DoD program developing a space‐based sensor system to a Critical Design Review (CDR) level of maturity. Real‐life successes and lessoned learned are described through model metric data pulled directly from the SysML development model. This paper concludes by identifying opportunities for future research/work from which to further build the DE/MBSE capabilities of the model.

FuSE Agility as a Foundation for Sound MBSE Lifecycle Management

ABSTRACTOver the past several years, numerous industries have increased their adoption of the systems modeling language (SysML®) and model‐based systems engineering (MBSE) as a core practice within their engineering lifecycles. However, the introduction of SysML and MBSE methodologies has not yet yielded many of the originally envisioned benefits. System models are becoming larger and more complex and many large MBSE projects continue to experience problems with model integration, repository performance, and model lifecycle management. The root cause is the failure to recognize the MBSE digital environment as a complex engineering information processing system that requires the same rigor and development processes as the system‐of‐interest (SoI) it is designing. This article describes how three future of systems engineering (FuSE) agility foundation concepts (system of innovation, effective stakeholder engagement, and continuous integration) directly address some of the problems seen in adoption, deployment, and sustainment of the MBSE digital environment as an SoI.

Implementation and Assessment of a Comprehensive Model-Based Systems Engineering Methodology with Regard to User Acceptance in Practice

Model-Based Systems Engineering (MBSE) is becoming increasingly popular, not only in research but also in industrial companies. However, MBSE approaches (i.e. methods, frameworks, ontologies, and tools) are usually developed at a scientific level, so that they are too generic and formal for a company's internal use leading to acceptance issues in industrial practice. Against this background, this contribution presents a comprehensive user-oriented MBSE methodology tackling this lack of acceptance in industrial practice. Based on ten previously derived fields of action for individual and organizational acceptance of MBSE approaches, a first positive evaluation of the MBSE methodology has been received. In this contribution, a further developed MBSE methodology is presented, which is created in cooperation of partners from research and industry. Assessment of this further developed MBSE methodology with six companies across different industries shows a positive impact on acceptance in comparison to existing MBSE approaches across the identified fields of action. Major improvements are seen regarding the perceived performance and benefit of MBSE, the usability of the modeling tool, and the communication within a development team. Smaller improvements are noted regarding the establishment of a clear target picture and modeling process, as well as in tackling ambiguity when modeling in a development team. In addition, research at one of the industrial partners shows that company-specific tailoring and implementation of the developed MBSE methodology can be performed in a fast and straightforward way.

Towards the Modelling of European Railway System Architecture

To master the increasing complexity of railway system, many European railway architecture initiatives are moving towards the application of Model Based System Engineering (MBSE) at overall railway system level or subsystems levels. Most of these initiatives apply the MBSE in their specific scopes. There is no common or unified MBSE methodology and related domain modelling language. Railway domain experts are usually not familiar with general-purpose modelling languages such as UML/SysML and need to collaborate with modelling experts to construct the future digital model of European railway system reference architecture. This paper presents a MBSE methodology and unified modelling language for the railway domain. The methodology is developed in LinX4Rail project, and the domain specific modelling language is used to model the preliminary description of LinX4Rail Architecture.

Model Based System Engineering (MBSE) and design assurance process in the context of mitigation of design errors during the development of highly integrated and complex aerospace systems.

Over the years, aircraft and spacecraft designs incorporated highly integrated and/or complex systems that can manage complex scenarios during its operation. In addition to the inherent complexity and/or high level of integration of those systems, the development process applied to aerospace programs is also challenged by other factors: program schedule, budget, multidisciplinary teams, new industry emerging technologies, large number of different processes and procedures that guide the activities along the development life cycle, and others. Given the fact many tasks executed during the development of such systems require human interaction, that yields the introduction of design errors that can contribute to the occurrence of non-desired system behaviors during operation phase. It is already recognized by the civil aviation industry that it is unfeasible to have a deterministic test set to demonstrate that such systems are completely free of such design errors. In that context, a huge effort is applied by the industry, by using qualitative methods to mitigate the occurrence of design errors during the development phases. This paper discusses how MBSE methodology applied together with a design assurance process could prevent such design errors, and presents an analysis showing how some events in aerospace industry where a design error was one of the contributing factors could be avoided.

SES-X: A MBSE Methodology Based on SES/MB and X Language

Model-based systems engineering (MBSE) is a leading paradigm for the analyses and development of complex systems. However, the development of modeling and simulation infrastructure supporting MBSE is lacking, which limits the application of MBSE. To address this problem, this paper proposes an SES-X methodology that integrates system modeling (following SES philosophy) with system simulation (supported by X language) to support the full lifecycle of MBSE modeling, including system analysis, architecture decomposition, physical modeling, and simulation. In the process, SES-X performs two levels of model pruning for model verification and simulation efficiency. This paper also conducts a case study on a car model to illustrate the effectiveness of the SES-X methodology.

Creating Value with MBSE in the High‐Tech Equipment Industry

ABSTRACTThe Netherlands has a strong presence in the high‐tech equipment industry sector with world‐wide renowned organizations. Systems engineering is a key capability that is well‐established in this sector. The industry now sees model‐based systems engineering (MBSE) as indispensable to bringing systems engineering capabilities to the next level. Despite this, MBSE is not a fully established practice in this sector as in other industries. ESI has initiated a study to understand the background of the sector's interest in MBSE, the challenges to address with MBSE, experiences with, and fit of current MBSE methodologies versus the characteristics of this sector. This article reports on the results of this study. It highlights innovation in MBSE to address the needs and characteristics of the high‐tech equipment industry.

Applying Systems Modeling Language in an Aviation Maintenance System

The aviation system has experienced an increasing demand over the last decade since it is considered one of the optimal means of transportation. As a result of this increasing demand, aviation organizations have been forced to focus on passenger safety by keeping aircraft airworthy at all times and by investing in the maintenance sector. Recent literature shows that the maintenance sector is still using outdated technology to maintain documentation of an aircraft's maintenance system. This article proposes the use of model-based system engineering (MBSE) as an approach to document aircraft maintenance systems. Systems modeling language (SysML) provides the maintenance system with a more systematic application that would automatically update maintenance records and provide stakeholders with more precise documentation. SysML is expressed through the use of structural and behavioral diagrams for the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EA-6B</i> aircraft. This article also provides a look into the use of SysML in the modeling of complex system architecture and the interaction between various systems. The integration of reliability studies and SysML is showcased through a case study. A failure mode and effect analysis is performed to show the usability of SysML in conducting reliability analysis. This article serves as a foundation for practitioners who aim to use MBSE methodology to solve the current setbacks existing in the maintenance aviation sector.

Combining dimensional analysis with model based systems engineering

AbstractThe 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.

Realizing Interoperability between MBSE Domains in Aircraft System Development

Establishing interoperability is an essential aspect of the often-pursued shift towards Model-Based Systems Engineering (MBSE) in, for example, aircraft development. If models are to be the primary information carriers during development, the applied methods to enable interaction between engineering domains need to be modular, reusable, and scalable. Given the long life cycles and often large and heterogeneous development organizations in the aircraft industry, a piece to the overall solution could be to rely on open standards and tools. In this paper, the standards Functional Mock-up Interface (FMI) and System Structure and Parameterization (SSP) are exploited to exchange data between the disciplines of systems simulation and geometry modeling. A method to export data from the 3D Computer Aided Design (CAD) Software (SW) CATIA in the SSP format is developed and presented. Analogously, FMI support of the Modeling &amp; Simulation (M&amp;S) tools OMSimulator, OpenModelica, and Dymola is utilized along with the SSP support of OMSimulator. The developed technology is put into context by means of integration with the M&amp;S methodology for aircraft vehicle system development deployed at Saab Aeronautics. Finally, the established interoperability is demonstrated on two different industrially relevant application examples addressing varying aspects of complexity. A primary goal of the research is to prototype and demonstrate functionality, enabled by the SSP and FMI standards, that could improve on MBSE methodology implemented in industry and academia.

A generic hierarchical System of Systems Engineering (SOS) Approach for Model based System Engineering (MBSE) Projects

AbstractModel based systems engineering (MBSE) has been accepted worldwide by many industries, including the automotive industry, for several years. Hundreds of projects have already been developed and deployed using MBSE approaches. MBSE is gaining importance because it provides systems advantageous life cycle processes, such as returns of investments and meeting the demands of global marketplaces, as they become increasingly complex. Consequently, the number and pace of deployment using MBSE approaches will increase in the future.Our current work objective is to define a generic MBSE methodology compatible with Systems Engineering Body of Knowledge (SEBOK) functional decomposition principles, ‘Automotive open systems architecture’ (AUTOSAR) developments and compliant to ‘Automotive software performance improvement and capability determination’ (ASPICE) processes using the ‘systems modelling language’ (SysML). We have proposed a generic SysML process framework, a hierarchical system of systems (SOS) engineering approach and automation solutions. We have shown that the proposed solution helps meet the defined objectives. The work is targeted and relevant for automotive industry MBSE practitioners. In general, the research, apart from transportation and mobility industries, can also be used in other industries.

Model Based Functional Safety – How Functional Is It?

As the engineering world embraces Model Based System Engineering (MBSE), the system safety discipline should also enfold and support MBSE methodology and approaches. The need for Model Based Functional safety, as part of the established system safety and software safety process, is becoming apparent due to existing and developing system design complexity. This paper is intended to show how valuable Model Based Functional Safety approaches can be when evaluating safety signification functions of complex software-intensive integrated systems. Using models can improve the accuracy during the Functional Hazard Analysis (FHA) and can help validate Fault Tree Analyses (FTA) and subsequent system safety analysis (SSA) process and results because the model focuses on the architecture, the physical system, the computer system, as well as the applicable software/middleware/Programmable Logic Devices (PLDs). Model Based Functional Safety may utilize use cases, structural architecture models, activity diagrams, sequence diagrams, functional flow diagrams, and state/mode models to depict safety attributes and to influence explicit safety requirements. SysML may be used to depict critical functions, functional threads, safety features, and expected behavior. Such augmented models (safety models) can also be used to analyze potential off nominal failure conditions and system behavior for various scenarios when conducting FHAs and subsequently detailed system and software safety analyses. This paper will provide an example of the MBSE framework and concepts for tool use in the functional safety analysis and the utilization of attributed models and artifacts to supplement system safety documentation.

Use of Model-Based System Engineering methodology and tools for disruption analysis of supply chains: A case in semiconductor manufacturing

In the age of complex and large-scale systems, Model-Based System Engineering (MBSE) is increasingly becoming a sine qua non in industry due in large part to a wider use of software applications and an increased move towards standardization. In this study, we research the application of the MBSE methodology (definition, design, analysis, and synthesis) to disruption management with a specific focus on a semiconductor supply chain case study. Within this methodology we use three MBSE tools, namely OWL, BPMN, and SysML, with the main focus being on definition of the problem to ensure that the “correct” problem is solved. The article does not report on any new research into the MBSE tools, but applies the available tools. Many of these tools have limitations, especially in the area of analysis and synthesis, that have been overcome if not widely adopted, in the area of product design (i.e., finite element analysis and simulation, etc.), which is a limitation in the type of systems studied here, i.e., a supply chain system which is a discrete event system. Through the application of the MBSE methodology and the application of the three MBSE tools, a comparison is provided that highlights further opportunities and obstacles, but which ultimately demonstrates a positive proof that the MBSE methodology is necessary for revealing sources of systematic disruptions within a complex integrated industrial information system.

Towards Holistic System Models Including Domain-Specific Simulation Models Based on SysML

In the face of the rapid growth in the scale and complexity of multidisciplinary systems, being able to develop reliable systems under ever-faster changing and more individual market requirements is becoming more and more challenging. The Model-Based Systems Engineering (MBSE) approach has already been researched heavily, and started to be introduced for the management of complexity, maintaining consistency, and reducing development costs and the time-to-market. However, a major drawback of the current MBSE methodologies is the lack of capability to integrate with domain-specific simulation models to investigate design concepts in the early phases of the development process. In order to address this issue, we propose a holistic system modeling approach that allows system engineers to link descriptive system models with domain-specific simulation models. In this paper, the Systems Modeling Language (SysML) is used as the standard architecture modeling language. A system modeling approach in SysML based on the system’s functional architecture for system design and validation is defined. The approach was developed to integrate domain-specific models into the system model using a SysML modeler with the capability of running and reusing simulation tasks via the coupling of external tools, which helps to bridge the existing gap between models on the system level and detail level. The feasibility of the proposed approach will be evaluated based on the case study of a wind turbine (WT) system. The study shows that our approach has the potential to enable the consistent, parameter-based interlinkage of domain-specific models based on always-up-to-date data, and to assist engineers in making design decisions to meet the system requirements accurately and rapidly in different engineering fields.