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Nanosatellites, as a standardized Space research project with fast and cost-effective development possibilities, have enabled universities in a growing number of emerging countries to develop a wide range of space missions in Low Earth Orbit (LEO). This paper aims to contribute to research efforts to improve the success of university nanosatellite missions using Model-Based Systems Engineering (MBSE) to facilitate the initial project management and design phases. The proposed model-based approach is the result of experience gained from the MASAT1 project, a Moroccan university nanosatellite, and it is based on an architectural framework that allows the system to be described via a set of views. The management and design process is based on a reference framework based on existing standards such as ESA's European Cooperation for Spatial Standardization (ECSS). The choice fell on the Systems Modeling Language (SysML) for the MBSE implementation with the future goal of developing executable SysML Modeling approaches. [ABSTRACT FROM AUTHOR]

Insufficient resources and high costs are hindering industrial development, potentially impeding adaptation to market demands. Overcoming this challenge necessitates advancements in software engineering techniques to streamline processes and meet industrial requirements. Crucially, automating manual tasks and enhancing interoperability between engineering stages can yield efficiency gains. This paper presents a model‐based system engineering approach aimed at automating the transition from design to implementation, incorporating autonomous generation and validation features. Implemented as plugins and utilizing model transformation techniques, this solution targets reducing engineering time and facilitating the adoption of new technologies. Developed, implemented, and tested within the Arrowhead framework, the approach is followed by a discussion on its benefits and limitations. [ABSTRACT FROM AUTHOR]

System modeling language (SysML) diagrams generated manually by system modelers can sometimes be prone to errors, which are time-consuming and introduce subjectivity. Natural language processing (NLP) techniques and tools to create SysML diagrams can aid in improving software and systems design processes. Though NLP effectively extracts and analyzes raw text data, such as text-based requirement documents, to assist in design specification, natural language, inherent complexity, and variability pose challenges in accurately interpreting the data. In this paper, we explore the integration of NLP with SysML to automate the generation of system models from input textual requirements. We propose a model generation framework leveraging Python and the spaCy NLP library to process text input and generate class/block definition diagrams using PlantUML for visual representation. The intent of this framework is to aid in reducing the manual effort in creating SysML v1.6 diagrams—class/block definition diagrams in this case. We evaluate the effectiveness of the framework using precision and recall measures. The contribution of this paper to the systems modeling domain is two-fold. First, a review and analysis of natural language processing techniques for the automated generation of SysML diagrams are provided. Second, a framework to automatically extract textual relationships tailored for generating a class diagram/block diagram that contains the classes/blocks, their relationships, methods, and attributes is presented. [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]

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 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]

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]

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]

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]

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]

As the complexity of modern aircraft systems continues to grow, traditional development methods become increasingly challenging in terms of management and maintenance. Firstly, the development process of aviation flight control system is evaluated in the current system engineering practice, and the shortcomings of traditional development methods and the core principles and advantages of model-based system engineering(MBSE) are expounded, as well as the tools and methods commonly used in implementation. Then, it shows how MBSE supports the process of specification, design, analysis, verification and validation of complex systems by using models in flight control system development. Finally, the future research directions are proposed, including the development of advanced MBSE tools and methods, the prospect of MBSE combined with agile development, and the need to improve interoperability and standardization of MBSE practices. The study in this paper can provide the resources and ideas for aerospace industry professionals and systems engineers interested in using MBSE methodology and tools to improve the design, development, and performance of flight control systems.

Copyright of Journal of Graphics is the property of Journal of Graphics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Graphics is the property of Journal of Graphics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Graphics is the property of Journal of Graphics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, paradigms like production quality or zero-defect manufacturing have emerged, highlighting the need to improve quality and reduce waste in manufacturing systems. Although quality can be analyzed from various points of view during different stages of a manufacturing system's lifecycle, this research focuses on a multidomain simulation model definition oriented toward the analysis of productivity and geometric quality during early design stages. To avoid inconsistencies, the authors explored the definition of descriptive models using system modeling language (SysML) profiles that capture domain-specific semantics defining object constraint language (OCL) rules, facilitating the assurance of model completeness and consistency regarding this specific knowledge. This paper presents a SysML profile for the simulation of geometric deviation propagation in multistage manufacturing systems (SysML4GDPSim), containing the concepts for the analysis of two data flows: (a) coupled discrete behavior simulation characteristic of manufacturing systems defined using discrete events simulation (DEVS) formalism; and (b) geometric deviation propagation through the system based on the geometrical modeling of artifacts using concepts from the topologically and technologically related surfaces (TTRS) theory. Consistency checking for this type of multidomain simulation model and the adoption of TTRS for the mathematical analysis of geometric deviations are the main contributions of this work, oriented towards facilitating the collaboration between design and analysis experts in the manufacturing domain. Finally, a case study shows the application of the proposed profile for the simulation model of an assembling line, including the model's transformation to Modelica and some experimental results of this type of analysis. [ABSTRACT FROM AUTHOR]

System modeling language (SysML) diagrams generated manually by system modelers can sometimes be prone to errors, which are time-consuming and introduce subjectivity. Natural language processing (NLP) techniques and tools to create SysML diagrams can aid in improving software and systems design processes. Though NLP effectively extracts and analyzes raw text data, such as text-based requirement documents, to assist in design specification, natural language, inherent complexity, and variability pose challenges in accurately interpreting the data. In this paper, we explore the integration of NLP with SysML to automate the generation of system models from input textual requirements. We propose a model generation framework leveraging Python and the spaCy NLP library to process text input and generate class/block definition diagrams using PlantUML for visual representation. The intent of this framework is to aid in reducing the manual effort in creating SysML v1.6 diagrams—class/block definition diagrams in this case. We evaluate the effectiveness of the framework using precision and recall measures. The contribution of this paper to the systems modeling domain is two-fold. First, a review and analysis of natural language processing techniques for the automated generation of SysML diagrams are provided. Second, a framework to automatically extract textual relationships tailored for generating a class diagram/block diagram that contains the classes/blocks, their relationships, methods, and attributes is presented.

As military reforms continue to develop, the battlefield environment is becoming increasingly complex, and traditional single-service combat methods have evolved into integrated joint and collaborative information operations that break down service boundaries on land, sea, and air. The level of weapon system confrontation has also evolved into a system-to-system confrontation. Traditional document-based system architecture design methods can no longer address the complexity and emergent challenges of weapon system construction. In this paper, based on model-driven system engineering, an open, integrated, model-driven weapon equipment interaction system that supports human interaction was constructed using the SysML modeling language and Magicdraw modeling tool. The Unreal Engine 4 landscape building function was used to construct a virtual battlefield environment, and a communication server was developed using C# language to perform visual simulation of interoperability between weapon systems. Based on model-driven weapon equipment interoperability, visual simulation is used to ensure that the function of the weapon equipment system meets the requirements of combat and the combat effectiveness of the system is maximized. [ABSTRACT FROM AUTHOR]

The use of system models within model-based systems engineering (MBSE) is essential for improved communication or system documentation. Previous publications have investigated further reuse of these system models, for example, transforming them directly into discipline-specific models for reuse. The authors refer to this as the term “Utilization” of system models. It aims the compensation of modelling efforts and a further integration of linked models within MBSE. Motivated by a lack of common understanding of this term, a systematic literature review of the state of the art is presented. With this systematic overview, a definition and classification system for different use cases and system life cycle stages are created. These are key results to support engineers and researchers in adopting existing or discovering new utilization approaches. This supports the mission of advanced systems engineering and aims the identification of new research directions coming along with SysML v2 and the advanced systems engineering methods.

In recent years, Model‐Based Systems Engineering (MBSE) practices have been applied in various industries to design, simulate and verify complex systems. The verification and validation (V&V) of such systems engineering models are crucial to develop high‐quality systems. However, this is a challenging problem due to the complexity of the models and semantic differences in how different tools interpret the models, which can undermine the validity of the obtained results if they go undiscovered. To address these issues, we propose (i) a subset of the SysML language for which the practical semantic integrity of tools can be achieved and (ii) a cloud‐based V&V framework for this subset, lifting verification to an industrial scale. We demonstrate the feasibility of our approach on an industrial‐scale model from the aerospace domain and summarize the lessons learned during transitioning formal verification tools to an industrial context. [ABSTRACT FROM AUTHOR]

Conceptual‐Design is an early development phase, where innovation and creativeness shape the future system/product. Model‐Based‐Conceptual‐Design (MBCD) attempts to use best‐practices of Model‐Based‐Systems‐Engineering (MBSE) to gain the envisioned benefits of model connectivity. Using MBSE supporting tools can transform Conceptual‐Design into a digital‐engineered process but may impede creativity and innovation. Concurrently, the design domain offers specific methods and tools for innovative Conceptual‐Design. In the current study, we explore an existing Conceptual‐Design framework and offer MBSE interpretation and tools extensions needed for its digital implementation. Through such exploration we highlight MBCD specific insights and discuss modeling‐innovation interrelations. The implementation was accomplished using a domain‐specific enabling software package on top of a market‐accepted UML/SysML platform, extending the language definitions, where appropriate. The framework guided extensions allow generation of innovative bottom‐up alternatives, solution integration, and solutions' comparison. The use of modeling is shown to offer clearer process definition, specific methods assistance, and alternative ranking—both manually and automatically. Consequently, MBCD is accomplished, which supports innovation, while being digitally connected to full‐scale‐development models and the organizational assets at large. Through integration into the orderly Systems‐Engineering process, traceability is maintained, and repeated iterations are supported, where conceptual decisions may be revisited. Additionally, through the introduction of an assets' catalog, cross‐organizational knowledge sharing is accomplished. The paper presents samples of the extensions, using a simplified example of technology design for Future Firefighting. The value of incorporating Conceptual‐Design specific methodology and tools is evaluated through feedback from multiple domain experts. Discussion and future research directions are offered. [ABSTRACT FROM AUTHOR]

In product development, important specification and design decisions must be made at various stages of the lifecycle that include design, manufacturing, operations, and support. However, making these decisions becomes more complex when a multi-disciplinary team of stakeholders is involved in system-level or subsystem-level architecture and design decisions. Model-Based Engineering (MBE) approaches are enabling a digital thread of connected data and models. This work demonstrates a novel MBE approach that incorporates a model-based systems engineering (MBSE) method and a multi-criteria decision-making (MCDM) method to determine the best architecture solution that aligns with stakeholder needs and objectives over multiple domains. This approach demonstrates the connection of a system descriptive model, modeled using the systems modeling language (SysML), to underlying physics-based engineering models for the purpose of better predicting the technical performance of systems during the architecture development phase. This approach is demonstrated for a common aerospace communications application, a software-defined radio. This novel MBE approach supports digital transformation at organizations and allows for earlier design validation, enabling designers to test and select the best system architecture from many candidates and validate that the design meets stakeholder needs. [ABSTRACT FROM AUTHOR]

Abstract Risk assessment is one of the important processes in the social implementation of robots. In risk assessment and safety design of systems with various stakeholders, modeling and visualization of related elements are important not only for designers but also for users. We examined the use of SafeML in the process and proposed its extension for the purpose for missing elements.

It is required to shift from separate life cycle (LC) stages to a single project implemented in the model-based systems engineering (MBSE) paradigm. However, MBSE software (SW) tools based on Systems Modeling Language (SysML) are complex and expensive. The paper raises the question, "Is it possible to make available MBSE SW and methodological tools (SMT) to a wide audience of users?" To address this question the following MBSE tools were considered: SysML, Quality Function Deployment (QFD) and House of Quality (HoQ). Their drawbacks were identified and solutions were proposed. All solutions were synthesized into a single methodological toolkit that allows in the automated way to create and update SysML requirement diagrams. Its implementation improves the quality of current projects by up to 10%, speeds up the planning process of analog projects by 60% and allows to implement projects in the MBSE paradigm wherever costly SysML SW tools are not available.

In recent years, paradigms like production quality or zero-defect manufacturing have emerged, highlighting the need to improve quality and reduce waste in manufacturing systems. Although quality can be analyzed from various points of view during different stages of a manufacturing system’s lifecycle, this research focuses on a multidomain simulation model definition oriented toward the analysis of productivity and geometric quality during early design stages. To avoid inconsistencies, the authors explored the definition of descriptive models using system modeling language (SysML) profiles that capture domain-specific semantics defining object constraint language (OCL) rules, facilitating the assurance of model completeness and consistency regarding this specific knowledge. This paper presents a SysML profile for the simulation of geometric deviation propagation in multistage manufacturing systems (SysML4GDPSim), containing the concepts for the analysis of two data flows: (a) coupled discrete behavior simulation characteristic of manufacturing systems defined using discrete events simulation (DEVS) formalism; and (b) geometric deviation propagation through the system based on the geometrical modeling of artifacts using concepts from the topologically and technologically related surfaces (TTRS) theory. Consistency checking for this type of multidomain simulation model and the adoption of TTRS for the mathematical analysis of geometric deviations are the main contributions of this work, oriented towards facilitating the collaboration between design and analysis experts in the manufacturing domain. Finally, a case study shows the application of the proposed profile for the simulation model of an assembling line, including the model’s transformation to Modelica and some experimental results of this type of analysis.

Risk assessment is one of the important processes in the social implementation of robots. In risk assessment and safety design of systems with various stakeholders, modeling and visualization of related elements are important not only for designers but also for users. We examined the use of SafeML in the process and proposed its extension for the purpose for missing elements. [ABSTRACT FROM AUTHOR]

In product development, important specification and design decisions must be made at various stages of the lifecycle that include design, manufacturing, operations, and support. However, making these decisions becomes more complex when a multi-disciplinary team of stakeholders is involved in system-level or subsystem-level architecture and design decisions. Model-Based Engineering (MBE) approaches are enabling a digital thread of connected data and models. This work demonstrates a novel MBE approach that incorporates a model-based systems engineering (MBSE) method and a multi-criteria decision-making (MCDM) method to determine the best architecture solution that aligns with stakeholder needs and objectives over multiple domains. This approach demonstrates the connection of a system descriptive model, modeled using the systems modeling language (SysML), to underlying physics-based engineering models for the purpose of better predicting the technical performance of systems during the architecture development phase. This approach is demonstrated for a common aerospace communications application, a software-defined radio. This novel MBE approach supports digital transformation at organizations and allows for earlier design validation, enabling designers to test and select the best system architecture from many candidates and validate that the design meets stakeholder needs.

Systems engineering has gained in maturity over the last decades and started a transition from document-centric approaches to Model-Based Systems Engineering (MBSE). Several papers have discussed the benefits and potential, but also the limitations, of using MBSE, based on literature surveys and analyze feedback from academia and industry. The current paper explores a complementary avenue and aims at giving students and industry practitioners a set of keys and decision criteria to select MBSE languages, tools and methods. Languages, tools and methods are categorised and selection criteria are proposed for a panorama of languages that goes beyond SysML and other techniques commonly associated with MBSE. In addition, research avenues for the future of MBSE are identified. The discussion relies on the authors’ experience in teaching and using system engineering and MBSE in both academia and industry, as well as on the experience shared within the framework of Concorde, a French project dedicated to drone systems design methodologies.

A study of model‐based systems engineering (MBSE) applied to a small‐lift launch facility is presented. The research uses Systems Modeling Language (SysML) products and functional diagrams to document the ground systems on a launch pad servicing a small class payload (0–2 tons). With the projected growth in launch cadence of small‐lift rockets in the coming decade, there is a need to design increasingly complex launch systems with greater efficiency. The potential improvements in project communication, quality, and productivity are explored by developing a model following the ISO/IEC 15288 technical process framework and the International Council on Systems Engineering (INCOSE) Object‐Oriented Systems Engineering Method (OOSEM) methodology. The stakeholder requirements are defined and analyzed to provide traceability to individual systems and subsystems. An architecture is proposed by generating engineering artifacts such as piping and instrumentation drawings. The concepts are verified and validated by performing engineering trade studies concentrated on the pneumatic and fuel subsystems. [ABSTRACT FROM AUTHOR]

With the goal of improving the quality of model-based development and to reduce testing effort, DevOps practices have gained more and more importance. However, most system engineers are not DevOps specialists, and there are a lot of manual steps involved when writing build pipelines and configurations of simulations. For this purpose, an abstract graph-based metadata model is proposed. This allows the autogeneration of scenario descriptions for simulations and code for the build server where the simulation environment is set up and executed. This is demonstrated by applying this process to the DCP standard. In this paper, we will discuss three simple use cases which are motivated by practical problems that arise in complex development environments and how the proposed solutions can be used to tackle them. Detailed descriptions and implementations of the use cases show how the proposed methods can be applied in practice and help solve the described problems. Furthermore, a Python implementation of a DCP master and a simple FMI-to-DCP wrapper are presented in this work. [ABSTRACT FROM AUTHOR]