Model-Based Systems Engineering Model Research Articles

A Technical Approach to the Digital Signature of MBSE Models

AbstractTo fully realize the benefits of Model‐Based Systems Engineering (MBSE), users of an MBSE model need to be able to verify its authenticity and integrity. A digital signature is a common cryptographic technique that enables users to sign digital content and verify the integrity of the signed content. This enables users to verify that the signed content is truly from the author who signed the content and is a common practice in digital documentation. MBSE models have unique qualities that separate themselves from other digital documentation, thus specific digital signature approaches need to be implemented for MBSE models.This paper describes an approach to apply digital signatures to MBSE models. The approach explores some characteristics of MBSE models and enables the digital signing of a portion of a model using a signer's digital certificate. The approach allows for the verification of the signed model content against the signature and indicates if information is altered from what the signer intended. This paper captures the technical challenges and lessons learned applying this approach as a prototype to an existing MBSE modeling tool. These findings from this paper can be used to guide the development of a digital signature capability in MBSE modeling tools.

Using VR to Validate and Visualize MBSE‐Designed Interfaces

AbstractSeveral 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.

A Method for Human Systems Integration Requirements within Model Based Systems Engineering

AbstractThe 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.

Recommendations for the Model-Based Systems Engineering Modeling Process Based on the SysML Model and Domain Knowledge

Model-based systems engineering (MBSE) is a modeling approach used in industry to support the formalization, analysis, design, checking and verification of systems. In MBSE modeling, domain knowledge is the basis of the modeling. However, modeling does not happen overnight; it requires systematic training and a significant investment of resources. Unfortunately, many domain experts lack the expertise required for modeling, even though they know the domain well. The question arises about how to provide system modelers with domain knowledge at the right time to support the efficient completion of modeling. Since MBSE research that integrates AI is just beginning to take off, no public dataset is available. In this paper, aerospace SysML models are constructed based on spacecraft-related domain knowledge to form SysML model data. The validation rules are studied to validate the SysML model data, and combined with the concept of the recommended system, a recommendation method for the MBSE modeling process based on the knowledge and SysML model is proposed. A GLOVE language model is pre-trained by using domain knowledge and general knowledge; the model data are also used to fine-tune the GLOVE language model combined with the pre-training to recommend some domain development processes. The recommendation list is manually quality-verified and fed into the pre-training phase, while new requirement texts are continuously added in the fine-tuning phase, resulting in a more relevant and accurate recommendation list. Experiments show that the incremental recommender system can not only effectively recommend SysML models, but also improve the quality and efficiency of MBSE development.

Linking Model-Based Systems Engineering (MBSE) and Multidisciplinary Analysis and Optimization (MDAO) for Early Design of Helicopter Primary Parameters

The design of a helicopter involves multiple disciplines and a large number of technical parameters with conflicting objectives, leading to the challenges of multidisciplinary coupling in design and optimization. In the context of the application of Model-Based Systems Engineering (MBSE) in complex product design, how to bridge the gap between MBSE and Multidisciplinary Design Analysis and Optimization (MDAO) to accelerate the early design process of helicopters remains an urgent problem to be addressed. The paper proposed an optimization framework that links MBSE and MDAO models for the design optimization problem of helicopters. On the MBSE side, the design optimization problem of helicopters was defined through the descriptive SysML model. On the MDAO side, the specific domain analysis model and optimization analysis workflow were established. The integration of design data was achieved through stereotype plugins and design components, bridging the gap between MBSE and MDAO, and providing accurate engineering data for system design verification. The paper provided an optimization case of a helicopter, with the optimal mission performance of the helicopter as the objective function. Through MDAO analysis, the design optimization of fuel consumption, take-off weight, and rotor dynamics parameters was completed, achieving an integrated process of system design and optimization.

Integration of Cameo Systems Modeler with Simulink for Co‐Orbital Engagement Mission Engineering

AbstractTesting the suitability of tactics for never‐used complex systems in a brand‐new warfare domain and forecasting the impact of these new tactics on system's requirements and design is challenging. The Model‐Based Systems Engineering (MBSE) approach seems to be the key to dealing with such complexity. However, to be truly effective this approach requires integration of the descriptive and physics‐based models. This integration results in an executable MBSE model that enables realistic mission analysis of system architecture prior to physically prototyping it. An executable model should significantly improve and enhance the feasibility of analysis of any mission during the early design phases. This paper aims to enhance the fidelity of a system model developed in the Cameo Systems Modeler by integrating it with a high‐fidelity dynamic model developed in the MATLAB/Simulink development environment. Specifically, this paper deals with a two‐satellite co‐orbital engagement mission and walks through all steps of the integration process. The paper also provides an example of mission analysis and reshaping the design space based on the results produced by running the developed integrated executable model.

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.

Design Ontology Supporting Model-Based Systems Engineering Formalisms

Model-based systems engineering (MBSE) provides an important capability for managing the complexities of system development. MBSE empowers the formalism of system architectures for supporting model-based requirement elicitation, specification, design, development, testing, fielding, etc. However, the modeling languages and techniques are heterogeneous, even within the same enterprise system, which leads to difficulties for data interoperability. The discrepancies among data structures and language syntaxes make information exchange among MBSE models more difficult, resulting in considerable information deviations when connecting data flows across the enterprise. Therefore, this article presents an ontology based upon <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">graphs</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">objects</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">points</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">properties</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">roles</i> , and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">relationships</i> with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">extensions</i> (GOPPRRE), providing metamodels that support the various MBSE formalisms across lifecycle stages. In particular, knowledge graph models are developed to support unified model representations to further implement ontological data integration based on GOPPRRE throughout the entire lifecycle. The applicability of the MBSE formalism is verified using quantitative and qualitative approaches. Moreover, the GOPPRRE ontologies are used to create the MBSE formalisms in a domain-specific modeling tool, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MetaGraph</i> , for evaluating its availability. The results demonstrate that the proposed ontology supports the formal structures and descriptive logic of the systems engineering lifecycle.

A Semantic Ontology-Based Approach to Support Model-Based Systems Engineering Design for an Aircraft Prognostic Health Management System

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.

Controlling the Complexity of Hierarchical Scheduling Frameworks

Hierarchical scheduling frameworks are a new scheduling paradigm where multiple system schedules are integrated (one-within-another). HSFs presents a multi-layered complexity problem that system engineers are struggling to contain. A promising trend in the aerospace and defense industry is to employ Digital Engineering’s Model-Based Systems Engineering (MBSE) to deal with the complexity of HSFs. MBSE permits the abstraction of application-specific details that can radically speed up system design exploration. Thus, this paper investigates how the output from an HSF algorithm can be converted into an MBSE modeling language that enables architectural exploration for resource allocation. The Unified Modeling Language (UML) Modeling and Analysis of Real-Time and Embedded Systems (MARTE) Profile is the chosen unified modeling language of MBSE. The modeling language is used with an HSF application for demonstration purposes. The approach in this paper seeks to limit tool use by combining an inline verification method (Genetic Algorithm) with a new MBSE workflow.

Managing knowledge and parameter dependencies with MBSE in textile product development processes

Abstract Today’s mechanical engineering companies are confronted with challenges like new material technologies, shorter product life cycles, increasing interdisciplinarity of the various departments as well as product development across distributed company locations. In the context of lightweight design, Tailored Textiles offer promising potentials to reduce product weight and manufacturing costs. Tailored Textiles are textiles with integrated local reinforcements whose textile properties can be adapted locally during the production due to the textile structures, so that process steps and therefore time and costs can be reduced. However, the production-oriented design of Tailored Textiles is currently very complex. One reason for this is the large number of stakeholders that are involved in the process. In order to make this complexity manageable, it is necessary to develop a common understanding of the textile process chain and to improve communication between different stakeholders. Another major challenge is the identification and management of technical parameter dependencies over the entire product development process (PDP). The aim pursued by this work is to link the technical parameter level of different expert models with the process level of Tailored Textiles PDP, so that expert knowledge is externalized to other stakeholders In this context, Model-Based Systems Engineering (MBSE) is a promising approach. Through the formalized application of modeling, MBSE allows the process accompanying development of a system model, which enables the visualization of the parameter dependencies within the product development process. In this paper, a methodological approach is presented which initially involves modeling the PDP for Tailored Textiles in a product data management system (PDMS). The process is then linked to a MBSE modeling tool. In the modeling tool, the analyzed parameters and their dependencies are set up and visualized. Following this procedure, the feasibility of the design will be evaluated based on a use case.

Frenemies: OPM and SysML Together in an MBSE Model

AbstractA Frenemy is “a person with whom one is friendly despite a fundamental dislike or rivalry.” (OED, 2018). The Systems Modeling Language (SysML) and the Object Process Methodology (OPM) are two such frenemies. OPM and SysML are different means of achieving Model‐Based Systems Engineering (MBSE), each with their own benefits, issues, supporters and detractors. The National Defense Industry Association (NDIA) defines MBSE as “an approach to engineering that uses models as an integral part of the technical baseline that includes the requirements, analysis, design, implementation, and verification of a capability, system, and/or product throughout the acquisition life cycle.” (NDIA, 2011) SysML is based on the Unified Modeling Language (UML) and includes diagrams that can be used to specify system requirements, behavior, structure and parametric relationships. SysML provides a means of defining high‐level abstract systems down to detailed physical systems. OPM is a “conceptual modeling language and methodology for capturing knowledge and designing systems. Based on a minimal universal ontology of stateful objects and processes that transform them, OPM can be used to formally specify the function, structure, and behavior of artificial and natural systems in a large variety of domains.” (ISO, 2015) OPM is used in some systems engineering graduate courses. Students graduating from these institutions are struggling to integrate the differing styles, philosophies, concepts and processes of SysML and OPM. A literature search reveals some papers that contrast SysML and OPM, but none that describe how the two can work together. This paper discusses a synergy of SysML and OPM in a SysML tool rather than promoting one language over another.

Enabling complexity management through merging business process modeling with MBSE

Integral products are characterized by multiple functional use of components, resulting in more compact and lighter products. However, those benefits come along with a significant increase in development process complexity. This complexity represents a significant risk in the value-creation chain. For the efficient fulfilment of customer needs and market requirements, strategies are required to cope with the complexity of integral products. A promising approach in this context is Model Based Systems Engineering (MBSE). Through the formalized application of modeling, MBSE allows the development of a system model to support the development process. The model enables a visualization of the process complexity and thus an identification of the essential complexity drivers. This knowledge is mandatory for the coordinated initiation of countermeasures. However, MBSE is not yet fully integrated in today’s product development processes (PDP). One reason for this is an insufficient interconnection between system models and business processes. This paper presents an approach for merging MBSE with business processes. The procedure comprises the modeling of exemplary business processes in a product data management system (PDMS). These processes are linked to a MBSE modeling tool via a RESTful API. Synergetic potentials of this connection are pointed out, based on scenarios from requirements management, product configuration and risk management. Finally, a discussion takes place regarding the degree of maturity to master complexity in business processes with MBSE.

Model-Based Systems Engineering for Aircraft Design With Dynamic Landing Constraints Using Object-Process Methodology

We present a model-based systems engineering (MBSE) framework using object-process methodology (OPM, ISO 19450) for civil transport aircraft design with dynamic landing constraints. The framework integrates the aircraft system development life cycle processes into a holistic MBSE model, incorporating into it the specific aircraft dynamic loads model-based design (MBD) domain. Using this framework, we also perform model-based requirements analysis, validation, and verification. The model parameter set is governed by a unified format used for both the MBSE and MBD domains. The resulting model enables aircraft design processes to start being formalized at the early conceptual design stage and carry on to detailed design, adding value to system lifecycle processes by integrating and streamlining the MBSE and MBD domains into a more holistic framework with seamless transition between these two major stages.

5.1.1 Parametric Analysis Through a Model‐based Reference Architecture for Medical Device Development

AbstractThis paper presents a proof of concept for the integration of the INCOSE Biomedical‐Healthcare Model Based Systems Engineering (MBSE) Challenge Team's modeling framework with a model‐based analysis method. This project investigated the inclusion of numerical analysis of an infusion pump and anesthesia using mathematical models integrated into the team's larger scope SysML drug delivery system medical device development modeling framework. The results of this work demonstrate how the results of a stochastic analysis can be integrated into a larger MBSE model. The inclusion of these results makes it possible for high level decisions to be informed by detailed engineering model analysis to give medical device designers the necessary data to speed development and utility of the devices they propose.

A Combined Design Structure Matrix (DSM) and Discrete Differential Evolution (DDE) Approach for Scheduling and Organizing System Development Tasks Modelled using SysML

During a system engineering process there are an important number of tasks that need to be organized, mapped together and recursively considered. The tasks that are mapped together are exchanging different flows of information and material. In this type of iterative processes, significant savings in term of development time can be made by providing a method that is optimizing the amount of feedbacks and iterations to the minimal level simply required for the successful development of the system. Task scheduling in a system engineering process can become extremely complex. Nevertheless it is a crucial step of the early stages of the systems engineering process for time-to-market, cost-efficiency and quality reasons. In this article, the authors are proposing to combine a computational approach (Discrete Differential Evolution) with Model Based Systems Engineering (MBSE) for minimizing iterations and reducing lead-time development. The present article is contributing to recent research works using Design Structure Matrixes (DSM) and computational methods for visualizing and analyzing systems engineering processes. The paper is proposing a framework integrating a model-based approach and a DSM based analysis of the process architecture to assist system engineers in organizing and scheduling tasks. As a result, this framework allows engineers to automatically populate DSMs generated from MBSE models developed in SysML. A specific stereotype is proposed to represent system development tasks in SysML. The sequencing of the engineering tasks is optimized with the application of a Discrete Differential Evolution algorithm (DDE) taking into account the different constraints. The practical use of the proposed framework is demonstrated on the case study of a mobile robot developed for the Eurobot competition. The article also discusses the possibility to use the current framework to analyze the impact of requirement changes on the scheduling of development tasks.

Essential Model‐Based Systems Engineering — Applied and Practical

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