Model-Based System, Safety and Security Co-Engineering Method and Toolchain for Medical Devices Design

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.

Nowadays, systems such as motor vehicles, medical devices, or industrial machines are designed according to functional safety requirements. The main criterion is the safety integrity level (SIL), which is mainly based on failure probabilities. A development approach based on models, also called Model-Based Systems Engineering (MBSE), is increasingly coming into focus for a highly regulated development process. Probabilistic safety and reliability analyses for calculating failure probabilities and applying these in MBSE are currently only integrated to a limited extent. Merging partial development processes increases confidence and couples the design process with all stakeholders. This paper presents a general method that develops domain-specific extensions based on specifications from Object Management Group (OMG) regarding risk analysis and assessment modeling for more practical applicability of MBSE for functional safety.

This paper describes research into the application of Model-Based Systems Engineering (MBSE) tools and processes to Risk-Informed Design (RID). RID enables system risk analyses early in the lifecycle of spaceflight projects allowing designers to use risk as a design commodity and part of the overall trade space. RID uses a “minimum functionality” approach, whereby a minimal, single-string system design is first envisioned that only meets basic performance requirements without any regard to overall reliability or safety. Risk analyses are then used to apply informed design enhancements based on their contribution to risk reduction. A recent application of RID was the Altair Lunar Lander Project that was intended for human lunar exploration under NASA’s Constellation Program. The Altair project’s approach and results are reviewed and analyzed in this paper as a specific application of RID. In traditional projects, several tools such as Relex, Windchill or SAPHIRE, are used in parallel to apply risk informed design techniques. These analyses also traditionally occur later in the design cycle when changes are more difficult to implement. Safety and reliability analyses typically have no direct connection with the system architecture model, which accurately depicts the physical and functional constructs of a system, including the “ilities.” The model is directly impacted by the results of the analyses. This creates a time-consuming iterative process of analyses and modification because of the need to integrate several tools and teams. To improve this process, the research described here investigated the use of a single, cloud-based MBSE CAD tool called Innoslate that integrates failure analysis into the system architecture model. The specific focus of the research was on the analysis of system failure events through the use of a system architecture-modeling tool and the establishment of an MBSE process that enables system engineers to make risk-informed system modifications during development. The conclusion of the research was that MBSE in general, and Innoslate specifically, is capable of providing an integrated, effective and quantitative means of developing a risk-informed system design using a minimum functionality baseline process. This can be applied to human and robotic spaceflight systems and other systems with similar complexity. The research demonstrated that random distributions could be added to failure probabilities in order to add “noise” to the results, a task that can be laborious, if not impossible, if performed using a calculator or spreadsheet. The research also demonstrated an end-to-end MBSE process that was applied to a basic system model and the Altair Project. Recommendations for future work conclude the paper.

Commercial viability for new unmanned aircraft in markets such as the European Union (EU) requires moving closer to population centers, flying Beyond Visual Line of Sight (BVLOS), and operating in busier airspaces – transitioning to medium-risk SORA SAIL III and SAIL IV operations. This requires a paradigm shift from primarily startup-style, minimalist system architecture modeling, documentation, and safety analyses–if any–towards the rigor expected in classical certification processes (e.g. ARP4754 and ARP4761). Model-based systems engineering (MBSE) and safety analysis (MBSA) methodologies have the potential to greatly aid in this transition: central models can more efficiently capture technical complexity, leverage component redundancy, and allow for easier sharing and re-use of system elements among specialized engineering tools. Larger all-encompassing MBSE/MBSA tools are expected to be particularly useful for their flexibility–providing for current and future needs, as more sophisticated details or analyses can be derived from simpler starting points and existing model elements. This project developed proof-of-concept examples within the Ansys SAM and medini analyze tools to demonstrate their usefulness for supporting SORA SAIL III and IV applications. This team included colleagues from the automotive domain to showcase the relative ease of producing the required evidence within just two Ansys tools–which is otherwise a time-consuming and confusing ordeal, typically using several disconnected programs. UAS designers and operators are encouraged to start with the information and examples produced by this project to accelerate their transition towards SAIL III and IV applications.

This chapter presents an example outlining the process and results of a software security risk analysis. Unlike other types of security risk analyses, a software security analysis focuses on the design and implementation of the online application rather than the network and physical environment in which the application is deployed. An example is used to illustrate the benefits of a software security risk analysis and demonstrate how software security extends and complements conventional security and business risk analyses.

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.

Model-Based Systems Engineering (MBSE) supports the development of complex systems through capturing, communicating, and managing system specifications with an emphasis on the use of modeling languages, tools, and methods. It is a well-known fact that varying levels of effort are required to implement MBSE in industries based on the complexity of the systems a given industry is associated with. This paper shares the results of a survey to industry professionals from Defense, Aerospace, Automotive, Consultancy, Software, and IT industry clusters. The research goal is to understand the current state of perception on what MBSE is and the use of MBSE among different industry clusters. The survey analysis includes a comparison of how MBSE is defined, advantages on the use of MBSE, project types, specific life cycle stage when MBSE is applied, and adoption challenges, as reported by the survey participants. The researchers also aim to trigger discussions in the MBSE community for identifying strategies to address MBSE related challenges tailored to a specific industry type.

The Prognostic and Health Management (PHM) system of an aircraft has complex structures and diverse functions. It is highly coupled with other systems, such as the avionics system and flight management system. The Model-based Systems Engineering (MBSE) method is effective to support the design and verification of the aircraft PHM system. As a powerful semantic web construction method, ontology has been widely used to express design information, such as the concepts and the relationships between them. However, traditional graphical MBSE models have a natural weakness in transforming into ontology. In this paper, a semantic MBSE method is proposed to support the transform of the ontology model. Firstly, according to the design characteristics of the aircraft PHM system, a meta-model library of the aircraft PHM system is developed to support the design and evaluation. An MBSE modeling method based on requirement analysis, function analysis, logical architecture design, and physic architecture design is applied in the PHM design process. Secondly, the semantic system modeling language KARMA based on “graph, object, property, point, relationship, role, and extension” (GOPPRRE) is used to transfer the graphical MBSE model to the semantic MBSE model, which can be easily transformed to an ontology model. Finally, an ontology based on semantic modeling is developed to describe the MBSE entities and to support MBSE design. In this paper, a case study of an aircraft fuel PHM system is carried out to validate the proposed method. Based on the developed meta-model library, a complete MBSE design process for the aircraft PHM system is realized. And then an ontology model supporting PHM system design is generated from the semantic MBSE model. The MBSE ontology provides a shareable capability to help designers communicate effectively. Quantitative analysis based on ontology is also provided to verify the complexity and scale of the MBSE design process. Moreover, logical reasoning ability can also be provided to support the early requirement traceability for MBSE design. In general, the case study results show the feasibility and effectiveness of the proposed method for the aircraft PHM system design.

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

A systematic co-engineering of safety and security analysis in requirements engineering process

A multidisciplinary team of eighteen faculty, staff, and students at a large Midwestern University is preparing online instructional materials on model-based systems engineering (MBSE) for current and potential employees of organizations that are either transitioning to model-based systems engineering or planning to do so in the near future. Our goal is to design, develop, deploy, and evaluate a suite of instructional modules, making them as effective and flexible as possible for employees with a wide variety of education, experience, and job responsibilities. It is essential for us to prepare materials that are well-aligned with the needs of organizations whose employees will be working in the digital environment using model-based systems engineering. This paper outlines the actions we are finding to be effective in aligning our modules with organizations' needs. The effort to align our materials with industry needs began before the project was officially launched. Some of our team members with MBSE expertise had industry connections and were able to identify people in several organizations who were either experts in, or advocates for adoption of, MBSE. Our team developed a series of questions for those industry contacts and held hour-long conversations with representatives of eleven organizations. We asked a series of questions ranging from which categories of employees would require training in MBSE and what topics should be covered to how employees are accustomed to receiving training and what technology they would have available to them for MBSE training. The questions were often open-ended, allowing us to gather information beyond what we knew to ask about. Some of the key contacts at organizations agreed to serve on an advisory board which meets semi-annually. At those meetings, we ask board members to give us more detailed, and current, information on MBSE topics to be covered, ways employees prefer to interact with instructional materials, and how we can best integrate our materials into an organization's ongoing training program. Those responses are influencing the development and deployment of our instructional modules. As each module is completed, it is sent to a subgroup of the advisory board (or their designees) for a thorough review. Reviewers, who participate in the process voluntarily, are asked questions about content quality, how well the modules motivate learners, instructional design, and so on. Typically, three to five reviewers provide feedback, with detailed comments as well as ratings on a Likert-like scale. Finally, a few employees with varied amounts of MBSE experience take the completed module and provide feedback on their level of satisfaction with the module and their thoughts on its value and effectiveness. The purpose of this paper is to describe the actions we have taken to align our instructional modules with employers' needs and to discuss the lessons we have learned so far.

Model-Based System Engineering (MBSE) provides a number of ways on how to create, validate, and verify the complex system design; unfortunately, the inherent security aspects are addressed neither by the SysML language that is the main MBSE enabler nor by popular MBSE methods. Although there are many common points between MBSE and security requirements engineering, the key advantages of MBSE (such as managed complexity, reduced risk and cost, and improved communication across a multidisciplinary team) have not been exploited enough. This paper reviews security requirements engineering processes and modeling methods and standards and provides the MBSE security profile as well, which is formalized with the UML 2.5 profiling capability. The new UML-based security profile conforms to the ISO/IEC 27001 information security standard. In addition to the MBSE security profile, this paper also presents the security profile application use case and the feasibility study of current status for security and systems engineering processes.

Engineering design researchers develop theories and methods aimed at enhancing the design process and creating systems that deliver maximum value. As engineered systems have become more complex, the systems engineering community has adopted digital environments like Model-Based Systems Engineering (MBSE) to handle documentation, knowledge transfer, and analyses. However, a gap between research and practice has been acknowledged by the lack of existing design theories and methods being transferred into MBSE. While vendors and practitioners create new methods for MBSE, there is a significant need to transfer design theory into operationalized capabilities in MBSE environments. In this paper, we explore and demonstrate how design margins, a design research concept that designers can use to navigate system changeability, can be transferred into an operational state in a digital engineering environment. We implement margins in an MBSE environment because existing MBSE change management processes are reactive. There is a need for end-to-end change management processes. Incorporating margins provides opportunities for proactive change management in that engineers can address changes before they occur through strategic design and redesign. We present a 6-step workflow that establishes the requirements, architecture, metrics, and analyses (RAM-A) packages in SysML so that system parameter margins and design variable flexibilities can be modelled, calculated, and communicated. We also discuss implications of misalignment between MBSE and engineering design nomenclature, features of the proposed approach that support changeability analysis, and aspects of MBSE modeling tools that support the implementation of engineering design methods. Future work should investigate the scalability of the approach, with a focus on scoping the margin and changeability analysis to maintain high return on investment.

Topology-based Safety Analysis for Safety Critical CPS

Mechatronic systems become ever more complex because of their increasing number of interconnected safety critical components and sophistication. MBSE (Model‐based Systems Engineering) and MBSA (Model‐Based Safety Assessment) are the most commonly adopted approaches to deal with the design and safety analysis of mechatronic systems. Unfortunately, both approaches are normally adopted separately, especially in the earlier phases of system design, thus leading to a lack of communication between system engineers and the safety team. This work aims to fill that gap at a high level, that is, through process interaction. This paper proposes an enhanced V‐model for the design of safety‐critical mechatronic systems. It relates a system development process with specific safety assessment methods. Specifically, the proposed workflow details exchange flows between the RFLP (Requirements, Functional, Logical, Physical) method, the FHA (Functional Hazard Analysis), the FMEA (Failure Mode and Effects Analysis), the MBSA and simulation, and the FTA (Fault Tree Analysis). These analyses are complemented with multiphysics modeling and simulation to observe system behavior in functional and failure scenarios, with the aim of requirements verification. The design workflow has been applied to a winged Unmanned Aerial Vehicle to apply the parallel process and the necessary interaction of MBSE and MBSA approaches. The information flows between the individual activities proved effective for designing a safe system before the verification phase. The main benefit of the proposed workflow is providing both the design and safety team with some interaction points, thus avoiding a lack of safety‐critical analysis in the early phases of system design.