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Over the past decades, Unmanned Aerial Vehicles (UAVs) have increasingly been used in a wide variety of missions that range from surveillance to delivery. Unlike aircraft that always carry goods and passengers from an airport to another, UAVs do not systematically implement the same type of mission. UAVs are indeed multi‐mission during their time in operation, and the systems engineering approaches developed for one mission aircraft must be adapted to the multi‐mission context. Therefore, UAV design requires application of mission engineering upstream systems engineering, either to assess there is a UAV system that may accomplish a new mission, or to specify a new UAV system according to a given mission. To achieve that goal, the authors of the paper support the use of Model‐Based Mission Engineering. A three‐layer architecture ‐ purpose, operation, functions or capabilities ‐ is proposed as a design framework for missions. The Goal‐Oriented Requirements Language (GRL) serves as mission description language. The paper extends GRL to better address mission‐based design of UAVs. It is proposed to distinguish between internal and external resources. A goal detailing mechanism is introduced. A degraded mode evaluation becomes possible. GRL tools make it possible to evaluate how much a UAV system ‐ at least, an operator, a ground station, and a UAV ‐ may satisfy every stakeholder in both nominal and degraded modes. The proposed approach is applied to a high voltage surveillance UAV. The case study enables the introduction of four actors—Authority, Client, UAV and MissionSupervisor—that turn out to be generic and can be reused for other missions and UAV designs. [ABSTRACT FROM AUTHOR]

The use of model-based systems engineering (MBSE) has been increasingly explored recently in industries that require multi-discipline engineering coordination. In the European space industry, applying MBSE for the engineering of space systems has been an ongoing undertaking on many missions. In the following paper, the MBSE activities in CAMEO conducted during the A/B1 phases of a typical Earth observation satellite engineered by Airbus are discussed in detail in the form of a case study. The analyses shown are based around the modeling of the spacecraft electrical interfaces in CAMEO. This model was used to automate electrical interface control documents (EICDs) and enable the control of electrical interface development. These methodologies were further put in the context of Airbus' satellite design processes to assess the benefits of an MBSE approach to the current electrical interface engineering procedure and the potential for the reuse of CAMEO models between satellite projects. The reduction in system engineering effort through the reuse of models to modularly create similar satellite systems for efficient concept evaluation and comparison is a clear benefit. [ABSTRACT FROM AUTHOR]

Model‐based systems engineering (MBSE) is rapidly gaining popularity among U.S. industries. Though industry practitioners and academic researchers have identified several advantages in transitioning to MBSE, several adoption challenges of MBSE in industries, such as insufficient tool knowledge, lack of skilled personnel, and resistance in organizations toward a shift to MBSE, are observed. Attesting to the challenges in industry adoption of MBSE, a previous research study by the authors characterized the adoption challenges as tools‐based, knowledge‐based, cultural, political, and cost‐related, and customer understanding and acceptance of MBSE practices. This study is motivated to explore further and address the challenge of low MBSE tool knowledge and lack of skilled personnel with MBSE knowledge for industry adoption. This paper presents a two‐phased research approach framed by an overarching question of the extent to which the MBSE academic curriculum is aligned with industry workforce requirements. In Phase 1 of the study, we survey industry professionals from Defense, Aerospace, Automotive, and other industry clusters to identify MBSE tools, languages, and concepts preferred by industry professionals in a candidate for hire. This is followed by Phase 2 of the survey targeted at academic institutions with Systems and MBSE programs to analyze the extent to which MBSE curricula reflect industry workforce hiring requirements. Further, we also identify the challenges reported in academic institutions in training the Workforce on MBSE. The contributions of this paper are two‐fold: providing a pathway for academic institutions to align their curricula to MBSE industry workforce requirements and triggering discussion in the broader MBSE community to identify strategies for addressing MBSE adoption challenges and training future model‐based systems engineers. [ABSTRACT FROM AUTHOR]

Tracing requirements specification to design and implementation is an essential part of safety standards, as it allows to ensure that safety goals are met throughout the development process. Manual tracing numerous artifacts produced throughout the development process is error‐prone and takes much time. To address these problems, we proposed a tool (Bonner, M.; Zeller, M.; Schulz, G.; Beyer, D.; Olteanu, M., 2023), which allows to establish links between requirements and Model‐Based Systems Engineering (MBSE) in a semi‐automatic way. The underlying algorithms of our tool are embedding similarity computation and classification approaches based on Large Language Models (LLMs). To assess the performance of underlying algorithm we propose an evaluation, where we compare the recall, the precision, and the F2 score of different approaches applied to our datasets. The goal of our evaluation is to understand how well LLMs perform in automatically generating trace links on different datasets. Our evaluation shows that it is worth to invest time in preprocessing the data and fine‐tuning the LLMs to achieve the better recommendations for engineers, which improves the traceability process. [ABSTRACT FROM AUTHOR]

Although Model‐Based Systems Engineering (MBSE) might be understood and applied across diverse communities and industries differently, its fundamental principles and practices described in INCOSE Systems Engineering Handbook, are common. It is known that successful application of MBSE is impossible without a tool, language, and method as well as harmony among these three. The de‐facto standard modeling language for MBSE is Systems Modeling Language (SysML). However, SysML is only a language, and it is not aligned with terminology systems engineers use daily in their work. This paper studies SysML as the standard language to model systems, and MagicGrid as the framework to bridge the gap between Systems Engineering (SE) terminology described in the INCOSE Systems Engineering Handbook and SysML specification. It proposes a new systems engineering meta‐model to describe a common SE terminology and bind it to the SysML concepts. [ABSTRACT FROM AUTHOR]

Systems and Software Engineers often have an uneasy relationship. The job of the systems engineer is to work with the stakeholders to define a set of requirements that meet their needs. These are then allocated to various solution spaces such as electronic hardware, mechanical, procedural, and software among others. For many systems, the functional requirements are almost exclusively software requirements. Correspondingly, as an increasing amount of project manpower, schedule time, and budget are allocated to software, it becomes increasingly important that systems and software engineers communicate effectively. The Systems Modeling Language (SysML) has helped in this regard in that it can provide executable behavioral models with precise semantics to express software requirements in a model. These models define "What is required" without overly constraining the implementation. In addition, SysML can be used to define performance constraints, required concurrency, hardware memory and processor budgets, interfaces, safety critical requirements, etc. These aspects are essential for software engineers to understand the constraints and limitations of their environment. At the System of Systems (SoS)/Enterprise level, defining software/systems employs a similar pattern, but at a higher level of abstraction. In the Unified Architecture Framework, capabilities are defined for the enterprise, with systems and software allocated to realize the capabilities. In the same way that capabilities depend on one another, the implementing systems and software interact to support each other. In the past, enterprise software would be modeled as residing in mainframes in a federated software pattern. Modern software can be modeled throughout the enterprise in a distributed network that can adapt to the changing needs of the enterprise to do load leveling, dynamic and late binding, reconfiguration, and reallocation of hardware resources as necessary. If the domain includes the Industrial Internet of Things (IIOT), then deployment could include edge devices, embedded software, Programmable Logic Controllers (PLC), PCs, servers, cloud computing, and of course mainframes. The Object management Group (OMG) Data Distribution Services (DDS) standard enables these capabilities across these devices in a universal format implemented by multiple vendors. However, before this complex system of systems can be implemented, it must first be architected and designed to ensure that it will be fit for purpose both now and as the complex system of systems expands and evolves. This paper will examine the aspects of modeling software in the UAF, and how it can help guide enterprise and system and software architecture. [ABSTRACT FROM AUTHOR]

Model‐Based Systems Engineering (MBSE) has been utilized within the automotive industry for several years. Increasing complexity due to highly automated, connected vehicles demands methods of coping with this complexity. In most cases, currently, only specific partial aspects or single methods of MBSE are used, which even varies across different companies. This paper aims to examine the current implementation of MBSE based on samples collected from companies acting within the automotive industry. Various aspects are explored, including the scope of application throughout the product life cycle, the use of simulation methods and the collaboration with other disciplines within product development. In the end, an evaluation discusses the reasons for the current state, and recommendations are given. [ABSTRACT FROM AUTHOR]

This paper examines the potential integration of Large Language Models (LLMs) with the Systems Modeling Language version 2 (SysML v2), proposing a novel methodology for systems engineering by capitalizing on the enhanced readability and human‐friendly syntax of SysML v2. Given the emergent sophistication of LLMs and the coincidental development of SysML v2—‐an endeavor that presents a pivot toward naturally articulated model interaction—‐we explore the possibilities and implications of such an intersection. Our investigation posits that LLMs can serve not only as an interpretive layer, allowing for the syntactically simplified manipulation of system models, but also as a catalyst for a knowledge‐driven design approach. We highlight the efficiencies gained by deploying LLMs for SysML v2 interactions, which reduce the dependency on technical expertise traditionally needed for API navigation and model management. Through case studies and analysis, we demonstrate that the conversational engagement with system models facilitated by LLMs can lead to a democratized and accelerated design process. However, this advent is tempered by a critical awareness of potential pitfalls, such as automation bias and overreliance on automated systems—‐underscoring the need for continued human oversight and the examination of ethical considerations. Emphasizing the chance of SysML v2 being inherently English‐based and the parallel maturation of LLMs, this paper suggests that the collaborative utilization of these concurrent advancements may offer an opportune fusion, potentially revolutionizing the way systems are modeled and managed. Future work involves the empirical validation of these approaches and a deeper investigation into interoperability with existing and future systems engineering ecosystems. The ultimate goal is to ensure that this fusion not only complements human expertise but also propels systems engineering into a new era of innovation and holistic design. [ABSTRACT FROM AUTHOR]

The ongoing transformation in the industry from a document‐based systems engineering to a model‐based systems engineering approach reveals gaps in existing modeling standards. Evolution of standards is inevitable. A de facto standard modeling language, SysML (Systems Modeling Language), is undergoing a major transformation in its evolution, with the introduction of SysML version 2, which is a complete redesign of the language architecture. With the major update of SysML, all related standards need to be redesigned. The Unified Architecture Framework (UAF) is not an exception. UAF version 2 is a future version of the standard to be based on SysML V2. Currently, the development of UAF based on SysML V2 is in the very early stages, and various organizations involved in its development are independently researching the way forward. This paper describes one of the research projects to test the feasibility of SysML V2 to address UAF community needs. [ABSTRACT FROM AUTHOR]

This paper aims to assess the impact of the next generation Systems Modeling Language, SysMLv2, on MagicGrid, an established framework for the model‐based systems engineering (MBSE). The research involves the parallel application of SysMLv1 and SysMLv2 to build two models of the problem domain definition by following the steps defined by the framework. The paper compares the modeling concepts of both languages used to create the model, discloses differences, and assesses advantages and disadvantages over each other. While SysMLv2 offers both textual and graphical notations, this study primarily focuses on the graphical representation. The paper concludes with a comprehensive summary of distinctions observed in the application of SysMLv2 versus SysMLv1. As anticipated, SysMLv2 was found a completely fresh modeling language. Significant alterations has been observed in the use case specification and functional analysis. Additionally, the absence of explicit guidelines on the utilization of definitions and usages was identified. [ABSTRACT FROM AUTHOR]

The European Space Agency (ESA) has been developing an MBSE Methodology to address the increased digitalization of systems engineering and facilitate the complex system development in ESA projects and other European space projects. The methodology is based on the European Cooperation for Space Standardization (ECSS) standards for Systems Engineering, and feedback from projects using the methodology. By using the ECSS standards as the starting point, the processes, terminology and expected outputs are familiar to the engineers, lowering the usage barrier within the Agency. This paper describes the background of and effort for establishing the MBSE methodology and a description of the methodology. The paper also reports on the current efforts at ESA for deploying MBSE and the way forward regarding the methodology. [ABSTRACT FROM AUTHOR]

In product development, rarely a product is developed from scratch. In many cases, a product is developed from a prior design or several prior designs. The associated development cost is actually a switching cost (or some called reuse cost), representing the cost incurred from developing the product from prior designs. So far, no proven works in switching cost estimation were found for products developed using MBSE (Model‐Based Systems Engineering). Today, MBSE is being widely adopted. It is important to develop switching cost estimation methods that leverage models and support model‐based development needs. This paper, per the best of our knowledge, is among the firsts that developed switching cost methods for MBSE. Our work identifies different use case scenarios/phases in an MBSE development cycle, and provides corresponding switching cost estimation methods, laying down the fundamental methodology for the model‐based switching cost estimations. Using SysML, an example use case of derivative airplane electrical power system is used to demonstrate the effectiveness of our methods. [ABSTRACT FROM AUTHOR]

The development of systems offers a particular challenge for the interoperability of different tools used by collaborating developers like requirements management, design, or simulation tools. The difficult and time‐consuming process to integrate and exchange data between different systems can lead to data inconsistencies and reduced efficiency in the development process. The integration standard Open Services for Lifecycle Collaboration (OSLC) targets the integration of engineering software applications. Its approach supports loose tool coupling, in which each application autonomously manages its own product data, while providing RESTful web services through which other applications can interact. This paper aims to analyze the suitability of OSLC as an overarching integration mechanism for the complete set of engineering artifacts created during system development. This paper presents use cases for the application of OSLC at the company MAHLE. For these use cases, the employed OSLC based toolchain is assessed. The analysis in this paper confirms that OSLC's capabilities allow users to support traceability and can support the exchange and integrate data according to the defined requirements, but it is not sufficient for sophisticated data processing functionalities, such as safety analysis or simulation. The OSLC integration does correspondingly compare favorably to integration technologies already in use regarding traceability, while transformation of data in domain specific tools is needed to achieve deeper levels of integration. [ABSTRACT FROM AUTHOR]

This paper describes an approach for Hardware‐in‐the‐Loop simulations with SysML models in the Cameo Systems Modeler tool. It is based on a plugin called MQTT Simulation Connector that enables bidirectional communication between the tool and hardware components using the MQTT protocol. The paper presents the applicable requirements and constraints that were considered, describes the MQTT Simulation Connector in detail and shows an example of its use in the form of a Smart Home demonstrator. [ABSTRACT FROM AUTHOR]

The Department of Defense (DoD) employs broad human factors requirements across various applications, resulting in a universal application of the same standards to a multitude of DoD acquisition systems. In unconventional warfare, specifically within missions conducted by US Special Operations Command (USSOCOM), operators face intensified workloads and domain‐specific challenges that current human factors considerations do not adequately address. The objective of this paper aims to introduce a novel framework, the Relational and Technological Capstone (RTC), designed to expand existing Human Systems Integration (HSI) requirements. The objective is to enhance the consideration of human factors in USSOCOM missions by addressing the unique challenges posed by intensified workloads and domain‐specific ontologies. The RTC employs a methodology‐driven approach utilizing both architectural and parametric diagrams. It integrates with Model Based Systems Engineering (MBSE) to improve the design of human‐system interactions, incorporating a Special Operations Task List and Performance Shaping Factors (PSFs) into aggregated parametrics. The results of this paper demonstrate the efficacy of RTC within MBSE, showcasing its value through improved design processes and as a foundation for new programs. The containment tree format aids in developing USSOCOM MBSE and opens possibilities for automation tools. Continual use of RTC contributes to the maturity of MBSE models and diagrams, fostering the evolution of a federation‐of‐models and Program of Record standards. This not only benefits subsequent SOCOM programs and projects but also facilitates cross‐cooperation with other nations in optimizing special operation acquisitions. The ultimate goal is to center the RTC around the operator, ensuring compatibility and optimization across cooperative nations' special operation acquisitions. [ABSTRACT FROM AUTHOR]

The global supply chain is a complex system of systems made up of and relying on other complex systems of systems (SoS) to achieve its goals. To take a typical example, Enterprise A is supplied essential parts on a regular basis to manufacture its products. To place the order requires global financial systems, integrated email systems, the internet, multiple telecommunications systems, and supply software provided by large companies. To deliver the parts may require air and maritime transportation systems, the rail network, interstate highway systems, road haulage companies, state and local transportation systems and so forth. When any of these complex systems fail, the impact can be global, and the results catastrophic. Recent examples include the shortage of Personal Protective Equipment (PPE) during the COVID pandemic, computer chip shortages delaying the assembly and sales of cars, and, most recently, the baby formula shortage. These were due to disruptions in the supply chain caused by an overreliance on single sourced suppliers who failed to deliver, transportation disruptions, outsourcing of critical parts, supplies, medicines to distant countries, and/or an overreliance on "Just In Time" for inventory management. This is the case of placing too many eggs in too few baskets, and often just one basket. Counterfeit or substandard parts and products can enter the supply chain via graft, breaks in chain of custody, or carelessness. This has included critical mechanical parts on aircraft, chips containing spyware, and substandard or out of date medicines substituted for the real thing resulting in serious illness and death. This complex SoS needs to be examined, studied, and understood in the same way as a mission critical system; threats, vulnerabilities, and risks need to be identified and mitigated and assurance cases defined to ensure a solid and reliable supply chain. This paper will look at the supply chain of an example factory system to determine how some of these problems can be predicted, prevented, mitigated, and solved using the UAF, RAAML and assurance case techniques. [ABSTRACT FROM AUTHOR]

The International Council on Systems Engineering (INCOSE) defines systems engineering as "a transdisciplinary and integrative approach to enable the successful realization, use, and retirement of engineered systems, using systems principles and concepts, and scientific, technological, and management methods." The evolution of engineering practices requires new research in the disciplinary intersections of scientific, technological, and management methods, especially when considering the INCOSE System Engineering Vision of 2035, which identified political, economic, social, technical, environmental, and legal factors as becoming modern tenets of system engineering success. Because vast amounts of research have been performed in multidisciplinary engineering areas, this paper examines the research landscape at the intersection of policy modeling and systems engineering by providing a systematic review of the literature to help guide future research based on trends and various guiding considerations. The results of this study will help identify gaps in the field while clarifying future research needs. We have applied the preferred reporting items for systematic reviews and meta‐analyses (PRISMA) protocol, which yielded 38 peer‐reviewed papers related to policy modeling and systems engineering. [ABSTRACT FROM AUTHOR]

The cybertronics challenges evolve around the complexity of systems and increase in detail and data involved. Existing methods and tools can master some of the rising challenges, but a method being able to handle the challenges was not introduced yet. MBSE is a potential approach to solve these problems, but the available methods were developed for modeling physical systems and software, not cybertronics. Because of the diversity of implementation domains participating in cybertronics systems, the modeling methodology must support the holistic management of requirements, properties, and design data. This paper introduces some promising emerging technologies like Arcadia, SysML V2, SysMD and PMM, that have the potential to interact with other methods and tools, closing the gaps in requirements tracing, system modeling, documentation, and verification. One potential methodology is introduced through a design example from requirements to implementation interface. [ABSTRACT FROM AUTHOR]

Implementing a digital engineering infrastructure is a strategic endeavour for any organisation. In this paper an investigation in the feasibility of federated Product Lifecycle Management is presented, starting from a presentation of the guiding architecture pattern and an evaluation of implementation alternatives. Interoperability standards from Open Services for Lifecycle Collaboration (OSLC) are introduced along with presentation of tool infrastructure for automatic generation of OSLC interfaces. Implementation experience validates that this is a viable and attractive alternative for implementing digital engineering. [ABSTRACT FROM AUTHOR]

This paper discusses an ongoing effort at Hyundai to develop a model‐based systems engineering (MBSE) methodology for cross‐domain vehicle architecture development that is practical at the enterprise level. Our approach follows a modular modeling process that complements MBSE. In the age of smart mobility, automobile systems are indeed interdependent elements of a system of systems (SoS). Connectedness favors numerous mobility features that emerge due to the interfaces among these constituent systems. Managing emergent product line variations, changing consumer demands coupled with faster market response require manufacturers to modularize their architecture development processes. This can help scale MBSE across vehicle programs. This study proposes a modular system architecture approach for developing Hyundai's purpose‐built vehicle (PBV) concept that maintains a link to the legacy vehicle breakdown structures already in use. Using the Arcadia method, the 'to‐be' developed electric vehicle is expressed as a hierarchical functional partitioning of the subsystem modules. A physical architecture is defined as a solution to the functional partitioning based on an existing vehicle breakdown in a combined 'top‐down/bottom‐up' workflow thus capturing a realistic system decomposition. In the SoS hierarchy, the PBV is at the top level and is partitioned into multiple levels of nested subsystem architectures owned and developed by designated module teams in a distributed modeling environment. Results of the preliminary architecture modularization effort indicate significant potential for benefits over classical architecture modeling such as iterative knowledge capture, enhanced reusability across projects, products and programs, and distributed vehicle performance development across the extended MBSE enterprise, which includes the tier 1/2 suppliers. [ABSTRACT FROM AUTHOR]

As artificial intelligence (AI) becomes integral across industries, there is a growing opportunity to transform the generation of models for systems engineering. This research investigates the integration of OpenAI's GPT‐4 Turbo into CATIA Magic for Model‐Based Systems Engineering (MBSE), resulting in the creation of AI Systems Modeling Enhancer (AI‐SME). This study explores the comparison between models generated by AI, specifically OpenAI's GPT, and those crafted by human systems engineers. While recognizing challenges in AI‐generated models, this research underscores the potential of AI assistants to enhance the speed and accuracy of SysML model creation. Results demonstrate AI‐SME's successes in generating requirements, block definition diagrams, and internal block diagrams. Despite identified limitations such as redundancy and lack of cohesiveness in AI‐generated models, the study concludes that AI‐SME represents a notable advancement in AI‐assisted systems engineering. [ABSTRACT FROM AUTHOR]

Model‐Based Systems Engineering (MBSE) is the next step in the evolution of systems engineering (SE) in which documents are replaced by descriptive models as the authoritative embodiment of SE knowledge. These descriptive models possess a unique combination of the features and characteristics of documents, software, and data. Conscientiously applying appropriate modeling principles and practices is essential to make informed decisions to moderate the accumulation of model technical debt. This paper briefly explains the concept of technical debt and its adaptation to the domain of descriptive models for MBSE. The paper then describes 18 foundational modeling principles that model architects should consider when making architectural and implementation decisions about their models and describes some of the key model technical debt tradeoffs that result when these principles are not followed. These principles address commonly observed challenges regarding model federation architecture, the selection and use of model layers, the modeling of the domain, and the semantics of modeling constructs. Applying disciplined model architecting practices to conscientiously manage the accrual and payoff of technical debt can make the difference between an enduring model that provides substantial value throughout the life cycle of the modeled entity and a model whose value collapses under the weight of uncontrolled technical debt. [ABSTRACT FROM AUTHOR]

Models are central to understanding systems and to the engineering of systems. Systems engineers employ various types of models to communicate shared understanding, through system life‐cycle models that enable the transformation of functional models to physical models, that are then realized as tangible systems of benefit to society. The recognition of the central nature of models to the engineering of systems resulted in the forming of Model Based Systems Engineering (MBSE) wherein the essence of the system of interest is contained within a system model in contrast to traditional documents. However, the evolution of model‐types employed, both to understand and to engineer systems, appears to largely have been a pragmatic activity driven by the needs of the numerous individual engineering and management subdisciplines. This paper briefly examines extant taxonomy of systems models used in the engineering of systems and in understanding operational systems and considers the question of whether there is a suitable system "meta‐model" that naturally "contains" all types of systems models used therein. It explores this question through a systems‐thinking lens, in conjunction with concepts on mental models from biology and philosophy. This analysis gives rise to framework for systems models and to the proposition that all (systems) models take on one of two forms: as reference models that aid in the engineering of systems or as representative models that aid in understanding operational systems. The paper concludes that it is possible to propose an emergent "model of systems models" that combines these two classes in an evolutionary way. This construct is offered for consideration and refinement by the systems community. [ABSTRACT FROM AUTHOR]

Companies 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. [ABSTRACT FROM AUTHOR]

The National Aeronautics and Space Administration (NASA) is embarking on new, complex, and diverse missions to accomplish its scientific and exploration objectives, and it views digital transformation as a key enabler for those missions. The NASA Model‐Based Systems Engineering (MBSE) Leadership Team (MLT) is leading the charge in the digital transformation of the systems engineering domain at NASA, and it is using the INCOSE Model‐Based Capability Matrix (MBCM) as a roadmap. This paper discusses the modifications and tailoring of the INCOSE MBCM (Hale & Hoheb, 2020) for use at NASA, the process the team has taken on multiple rounds of assessment, findings to date, and work products that have been generated as a result of the assessment. The paper will also discuss findings and potential changes that should be made to the original product. [ABSTRACT FROM AUTHOR]

The National Aeronautics and Space Administration (NASA) has an ongoing Digital Transformation effort and to leverage and showcase the power of Digital Transformation, an effort is underway to develop an integrated, datacentric, model representing NASA's key process requirements. The task was divided into three phases: As Is modeling, Analysis, and To Be Planning. As part of this effort, a team has completed the first Phase I of the modeling task and is nearing completion of the second phase. This effort will capture the key elements as requirements, responsibilities, allocations, roles, products, and associated lifecycle elements. The scope of modeling included NASA's NPR 7120.5 (Project and Program Management), NPR 7123.1 (Systems Engineering) and NPRs 8705.2 (Risk classification for Robotic Missions) and 8705.4 (Human‐Rating Requirements for Space Missions). This paper will summarize the approach, scope, parsing patterns applied, metamodel, and associated workflows for the As‐Is modeling. It will also summarize the results and insights gleaned during that phase, including the review process. These insights have informed the analysis and will be discussed. The analysis modeling phase will also be summarized including how the stakeholders were engaged, how the common elements were handled and dispositioned, and will also describe some of the plans for the future of NASA NPDs and NPRs. [ABSTRACT FROM AUTHOR]

The promise of Model‐Based Systems Engineering (MBSE) and its advertised benefits hinge on the ability of our profession to integrate engineering disciplines and project management across the system life cycle. In particular, connecting system architecture and design decisions to the economics of the system's development is a critically important topic, but has often been overlooked by the system engineering community. Achieving such integration requires two key elements: (1) the standardization of multidisciplinary terms and functions, and (2) the establishment of rules governing relationships between cross‐functional models and modeling environments. This paper contributes to these areas by (1) establishing common terminology describing systems engineering and cost estimating, and (2) proposing specific cost drivers and counting rules within an MBSE environment that can be applied to estimating systems engineering effort using the COSYSMO cost model. COSYSMO is a systems engineering cost model, originally developed in 2005, and was grounded on document‐based systems engineering methods. This paper facilitates the convergence of COSYSMO and MBSE by updating the COSYSMO counting rules to specifically address size driver selection and assessment in a SysML model. It illustrates how advanced modeling tool features streamline and automate cost estimation activities, while queries and crosscutting views offered by modern MBSE tools enhance the completeness, quality, and consistency of parametric cost estimation process. Additionally, it provides guidelines for identifying system model content and level of detail for cost estimating, and proposes an approach to link attributes and properties in a system model to the variables in the COSYSMO cost estimating relationship. [ABSTRACT FROM AUTHOR]

In the dynamic aviation industry, Aerospace Industries grapple with the intricate challenge of certifying products amidst integration requirements from aerospace manufacturers and airworthiness regulations imposed by aviation authorities. This paper underscores the indispensable role of ModelBased Systems Engineering (MBSE) in addressing the multiphase issues inherent in our product complexity. The first focal point is the certification process, where Safran SEATS navigates the complexities imposed by aerospace manufacturers and stringent airworthiness regulations. This intricate certification process demands the strategic deployment of MBSE to streamline and enhance procedural efficiency. The second challenge arises from the abstract nature of style and perceived quality requirements articulated by diverse customers. With the goal of exceeding customer expectations and creating a genuine "WOW" effect, MBSE becomes instrumental in aligning product development with diverse and often oriented customers' needs. The third dimension of complexity stems from the variability in emerging requirements, where innovations swiftly become industry standards. MBSE provides a structured approach to handle this variability, ensuring adaptability and positioning products at the forefront of innovation. Additionally, we dissect the influence of Model‐Based Design (MBD) on design processes, shedding light on its transformative effects. Introducing the concept of a digital twin, we explore its significance in the aerospace domain. Real‐world implementations of digital twin technology examined through concrete examples from aerospace projects. Finally, the presentation addresses uncertainties surrounding program efficiency, a critical consideration in the intensely competitive seat market. This paper unfolds a compelling industrial testimony, showcasing Safran SEATS' journey in overcoming the complexity of digital transformation in Aerospace Industries. It provides solutions to intricate challenges posed by certification, customers' requirements, evolving industry standards, and economic competitiveness, encapsulating the transformative impact of MBSE in our pursuit of excellence. [ABSTRACT FROM AUTHOR]

One of the key roles of National Aeronautics and Space Administration (NASA) is to help mitigate the risk and lower expenses associated with space exploration, science, and discovery to the point where industry and international partners are willing and able to profitably take on larger, more complex missions. To do this, the Agency must undertake a transformation to a more modern integrated Digital Engineering approach to mission definition and planning. This paper highlights NASA's journey in understanding what this Digital Engineering Transformation means for the Agency, the benefits of this transformation to human exploration definition and planning, and the benefits to the current Artemis campaign engineering capability portfolio. [ABSTRACT FROM AUTHOR]

Model‐Based Systems Engineering (MBSE) is the growing practice of systems engineering (SE) in which descriptive models replace documents as the embodiment of SE knowledge. These descriptive models capture SE information in place of documents, are developed in a similar manner to software source code, and are encoded and used in machine‐to‐machine applications as data. This paper describes how the Technical Debt concept widely used in the software domain—rework deferred to the future for expediency—needs to be modified for the domain of descriptive models. Technical Debt is often associated with agile development practices of software or descriptive models, which emphasize the rapid creation and iterative evolution of a Minimum Viable Product (MVP). Consciously applying appropriate modeling principles and practices is essential to make informed decisions during the modeling process to prevent the accumulation of excessive model Technical Debt—particularly during this iterative evolutionary process—which can require substantial rework to correct. The paper establishes a foundation for characterizing the Technical Debt implications of key model architecture and implementation decisions that are made explicitly or implicitly by modelers when developing descriptive models. To illustrate the model Technical Debt concept, several examples of modeling principles pertaining to model purpose and implementation are described along with their implications on model Technical Debt. [ABSTRACT FROM AUTHOR]

Several unique challenges arise in the new field of integration between Model‐Based Systems Engineering (MBSE) models and game‐based digital twin visualizations. First, no known standardized interfaces between the MBSE model and game engine visualization are defined, which can lead to custom or stove‐piped solutions. Additionally, visualizing digital twin models in true to life scale is insufficient with typical desktop computers. The Bi‐Directional Interface Requirements Operational System Test (BIFROST) prototype, funded by the US Army Program Executive Office (PEO) Aviation, seeks to address these challenges. Progress of the BIFROST prototype is covered in the paper. The prototype aims to determine the feasibility and challenges of validating interfaces through visualizing changes to an MBSE model in a 3D game engine. Research was performed to visualize part of an uncrewed aircraft system ground control station in 3D using the Unity game engine. A Mission Control Architecture MBSE model, developed by PEO Aviation, is used to drive the digital twin of the ground control station through a set of virtual reality (VR) controls. Users can visualize, analyze, and test the human‐machine interaction of the 3D models in VR prior to real‐world system changes. This paper presents the recommended interfaces between the MBSE model and 3D engine, lessons learned, and future research areas. [ABSTRACT FROM AUTHOR]

A standardized decision support tool to support test prioritization and decision‐making is a prerequisite to achieving on‐time delivery of weapon systems that are adequately tested and vetted by decision makers within distributed organizations such as the defense industrial base. However, to achieve standardization, the core principles of systems thinking and systems engineering must be utilized in order to realize a holistic and evolvable process and product that integrates Test & Evaluation (T&E) data and information with decision‐making in a consistent format to support program offices. To address this need, a model‐based reference architecture for the standardization of the Integrated Decision Support Key (IDSK) data and decision formats is presented in this paper. The IDSK is a DoD‐mandated decision support tool (artifact) for capturing a program's decisions and the T&E information necessary to support the decisions. The digital‐IDSK reference architecture proposed is developed using a model‐based systems engineering approach and facilitates the generation of standardized data and decision formats that are tailorable, adaptable to incremental future changes, and easy to integrate with other digital engineering artifacts all within a digital engineering ecosystem. In addition, this approach is also applicable not only to defense‐based organizations, but also finds utility within organizations pivoting to a digital engineering strategy for informing product T&E decision‐making. [ABSTRACT FROM AUTHOR]

The four Industry 4.0 design principles information transparency, technical assistance, interconnection and decentralized decisions pose challenges in integrating Information Technology (IT) and Operational Technology (OT) solutions in industrial systems. These different solutions have conflicting requirements, making interfaces between them problematic for both systems and organizations. An Industrial Business Process Twin (IBPT) entity, acting as an intermediary between the realms of IT and OT, has been proposed in a previous work, to effectively reduce the amount of required IT/OT interfaces in an attempt of overcoming this situation. In this work, we investigate the effects of this approach during the design phase. We argue that, by eliminating potentially conflicting direct interfaces between IT and OT stakeholders within the organizational structure, this approach effectively eliminates conflicting communication channels within the system design. To verify our argument, we develop a model of our IBPT concept according to the Reference Architecture Model Industrie 4.0 (RAMI4.0) using an Industry 4.0 scenario addressing the four essential Industry 4.0 design principles. Results show that the IBPT approach indeed eliminates potentially conflicting IT/OT interfaces during the system design phase. [ABSTRACT FROM AUTHOR]

System design in defense systems is a competitive field, in which economical viability relies on a sequence of architectural decisions, aiming at quality, resource and time (Q,R,T) compromises. We observe that low‐cost unmanned ground vehicles (UGV) and drones appear as new threats on current battlefield. To face these new threats, Direction Générale de l'Armement (DGA) have organized challenges around robotization of battlefield, to design future employment doctrines and help technologies to reach maturity in a reasonable time. This article exposes a NATO Architecture Framework (NAF) 3.1‐based workflow that includes return of experience form the field over yearly iterations of such challenges. The capabilities depicted are requirements to match, constituent systems are based on Components‐Off‐The‐Shelf (COTS) answering to both edition of the challenge. This article details how manually re‐injecting feedback from field back to the system model failed to ensure the next iterations of the challenge. Our works propose conclusions on formulation of the "engineering leakage problem" and how resolution of this problem is NP‐Hard and should be addressed using optimization. [ABSTRACT FROM AUTHOR]

Over the past decade, technology has experienced a rapid and widespread evolution, resulting in new capabilities across the defense sector. While these capabilities often bring about beneficial changes, they can also beget unforeseen consequences. As a result, it is becoming increasingly important for the military to understand how this changing technological landscape can impact its missions. To address this issue, we have developed an Integrated Mission Simulation (IMS) to assess the potential impact that different technologies may have on a given mission. The Integrated Mission Simulation combines a mission context model with several technology performance models, which enables users to assess the results of different 'what‐if' scenarios on key performance parameters for a given mission. To illustrate its utility, we present two publicly available scenarios and simulate how known technological advances could have altered the outcomes of those scenarios. [ABSTRACT FROM AUTHOR]

The Systems Engineering (SE) industry employs many people from the neurotypical and neurodivergent communities. This research presents different concepts and potential methods/tools available to promote neurodiversity and the complex interactions between those who are categorized by it, as well as the various relevant institutions it challenges and responds to (psychiatry, education, industry, etc.). Neurodiversity will mean different things at different times. The challenge we face in the industry is finding ways to work on complex systems that include neurodiverse thinking into the overall solution. This paper will attempt to bridge this gap by looking into the meaning of neurodivergence, showing the different ways organizations within the SE industry assess a neurodiverse individual to perform work, and demonstrating how organizations can utilize tools and methodologies to offer more inclusion and reduce feeling invisible within the community. This paper will further explain how modelbased systems engineering (MBSE) and simulation could provide methods and visualizations necessary to provide a cross‐neurotype communication and visualization methodology to convey both abstract and concrete solutions to complex problems in SE. By adopting a neurodiverse perspective, we can alter actual relations; from how we empathize with the neurodivergent community, to how we design adaptable systems that evolve and expand into new functionalities and services. [ABSTRACT FROM AUTHOR]

Due to complexity increases in modern systems and the digitalization paradigm shift, industrial development requires the integration of new technologies and methods to keep product quality high while reducing time to market. One emerging paradigm in the Systems Engineering (SE) discipline is ModelBased methods and technologies, and correspondingly Model‐Based Systems Engineering (MBSE) is seeing increased adoption. With mature MBSE application, several benefits can be expected from the availability of models, even from the very early stages of development, enabling increased communication clarity, cross‐domain collaboration, traceability, and analysis. Notably, MBSE enables (Co‐)simulation even at the early stage of architecture/design by leveraging model‐based capabilities. Co‐simulation specifically enables a smooth and seamless integration of different models defined across layers of abstraction, for example, system logical architecture and system physical architecture. However, while MBSE is assisting with many aspects of development it is still a predominantly isolated set of activities throughout the development, especially on the left‐hand side of the traditional V‐model. In this work we discuss the status of Co‐simulation in industrial MBSE and list several existing challenges, then we propose a novel framework for implementing Co‐simulation and exemplify using a real scenario how we might address the observed challenges. The framework hinges on the newly proposed SSP standard and extends the currently industrially adopted FMI (version 3) standard through embedding the FMI file format using various scripts, demonstrated in the Python language for this paper. Finally, we propose a set of recommendations for future investigations to strengthen Co‐simulation in industrial MBSE. [ABSTRACT FROM AUTHOR]

System architecture design is crucial for forward design in aerostat system engineering, yet a comprehensive research framework has been lacking. This paper presents a new method for stratospheric airship architecture preliminary design and optimization trade-off, grounded in Model-Based Systems Engineering (MBSE) theory. Firstly, a requirement analysis for a stratospheric airship is conducted using SysML, leading to the analysis and acquisition of the airship's mission architecture design. Additionally, a multidisciplinary coupling simulation platform is developed with MATLAB, and the architecture preliminary design's Pareto front is derived using the NSGA-II algorithm. Finally, based on the Pareto optimization set, the TOPSIS algorithm is applied to derive the optimal architecture preliminary design scheme for the airship. The optimization results validate the accuracy of the architecture preliminary design obtained from the requirement analysis, the reliability of the multidisciplinary coupling simulation platform, and the feasibility of the optimization algorithms. This comprehensive study spans the requirement analysis to the optimal architecture scheme, providing theoretical reference and design guidance for the forward design of airship systems engineering. [ABSTRACT FROM AUTHOR]