Search Results (29)

Model-Based Systems Engineering (MBSE) has gained significant attention from both industry and academia as an effective approach to managing product complexity. Despite its progress, current MBSE concepts, tools, languages, and methodologies face notable challenges in industrial applications, particularly in addressing design variability, ensuring model consistency, and enhancing operational efficiency. Based on the authors’ industry observations and literature analysis, this paper identifies the primary limitations of traditional MBSE, and introduces MBSE 2.0, a next-generation evolution characterized by comprehensive, integrated, and intelligent features. Key enabling technologies, such as model governance, integrated design methods, and AI-enhanced system design, are explored in detail. Additionally, several preliminary explorations were introduced under the guidance of the MBSE 2.0 philosophy. This study introduces the MBSE 2.0 concept to stimulate discussion and guide future efforts in academia and industry, emphasizing key advancements and highlighting several key and pressing perspectives to alleviate current limitations in industrial practice. Full article

Rising consumer demand and stricter regulations regarding sustainability are leading to an increasing consideration of sustainability aspects during product development. To evaluate environmental impacts, life cycle assessments (LCAs) are established as the most comprehensive method. However, the extensive data-need for setting up the life cycle inventory (LCI) model limits their widespread application. Moreover, LCAs are normally conducted post-development, offering no support in decision making during the development process. An approach is needed that provides product-specific information during product development to be used in LCAs to allow the execution of LCAs already during product development. Model-based systems engineering (MBSE) promises to meet this need by providing a framework for seamless interdisciplinary product development. A central element in many MBSE approaches is a SysML system model that describes the architecture and behavior of the product and provides all relevant information for needed domain-specific models. In this contribution, a novel approach is presented utilizing a SysML system model to automatically execute an impact assessment within an LCA tool. For this, the minimum data-need for setting up LCI models in established LCA tools is analyzed, and a framework for modeling life cycles in SysML system models is presented. To allow an automated execution of an LCA, an interface between a SysML tool and an LCA tool is implemented. In the example of a laser-structured metal part, this contribution shows that SysML system models are suited to provide the needed product-specific data for setting up LCI models and that they can be utilized to execute LCAs already during product development. Full article

Model-based systems engineering (MBSE) offers significant advantages over traditional document-based approaches, particularly in improving the clarity, traceability, and efficiency of requirements engineering (RE). However, MBSE also introduces challenges, particularly in maintaining consistent semantics and handling evolving system models. This paper presents ARMADE, an agile requirements management and definition environment developed at DLR, which aims to address these challenges. ARMADE enables the flexible, user-friendly modeling of system requirements using a data model that incorporates natural language patterns. The tool supports the dynamic adaptation of metamodels and facilitates collaborative, project-wide requirements management. A case study based on two systems of systems (SoS) from the EU-funded HE COLOSSUS project—firefighting and advanced aerial mobility (AAM)—demonstrates ARMADE’s ability to manage complex, interdisciplinary requirements. The study highlights the tool’s potential to reduce data inconsistencies, improve adaptability, and enhance the overall efficiency of the RE process. By enabling seamless updates and changes to requirements, ARMADE shows promise as a versatile solution for dynamic metamodeling in complex systems, with potential applications extending beyond aeronautics to various industries reliant on intricate requirements management. Full article

This article proposes a novel methodology aimed at streamlining the system’s development process. By examining existing state-of-the-art approaches and the capabilities inherent in Model-Based Systems Engineering (MBSE) tools, the article introduces a methodology centered around transforming a descriptive Systems Modeling Language (SysML) model into a digital twin. This virtual representation of the physical asset leverages real-time data and simulations to mirror its behavior and characteristics. When integrated with MBSE, this synergy allows for a comprehensive and dynamic approach, enhancing innovation by providing a holistic and adaptable framework for designing, analyzing, and optimizing complex systems throughout their lifecycle. The practical application of this Real-Time Communication and Data Acquisition (RT-CDA) methodology is implemented in a context and operational scenario of an electric unmanned autonomous vehicle employing both Software-in-the-Loop (SITL) and Hardware-in-the-Loop (HITL) approaches. The methodology empowers systems engineers to iteratively update and refine their system model’s fidelity based on real-world testing insights. The article specifically demonstrates the real-time communication capabilities achieved between an electric unmanned autonomous vehicle (a physical asset) and a descriptive (SysML) model, illustrating the real-time data aspect integral to the concept of a digital twin. This study serves as a foundation for future endeavors, envisioning real-time communication among virtual and physical models to construct comprehensive digital twins of complex systems to predict behavior and performance. Full article

The automotive industry is experiencing a surge in system complexity driven by the ever-growing number of interacting components, subsystems, and control systems. This complexity is further amplified by the expanding range of component options available to original equipment manufacturers (OEMs). OEMs work in parallel on more than one vehicle model, with multiple vehicle variants for each vehicle model. With the increasing number of vehicle variants needed to cater to diverse regional needs, development complexity escalates. To address this challenge, modern techniques like Model-Based Systems Engineering (MBSE), digitalization, and Artificial Intelligence (AI) are becoming essential tools. These advancements can streamline concept development, optimize thermal and HVAC system design across variants, and accelerate the time-to-market for next-generation EVs. The development of battery electric vehicles (BEVs) needs a strong focus on thermal management systems (TMSs) and heating, ventilation, and air conditioning (HVAC) systems. These systems play a critical role in maintaining optimal battery temperature, maximizing range and efficiency, and ensuring passenger comfort. This article proposes a digital prototype (DP) and AI-based methodology to specify BEV thermal system and HVAC system components in the concept phase. This methodology uses system and variant thinking in combination with digital prototype (DP) and AI to verify BEV thermal system architecture component specifications for future variants without extensive simulation. A BEV cabin cooling requirement of 22 °C to be achieved within 1800s at a high ambient temperature (45 °C) is required, and its verification is used to prove this methodology. Full article

This paper presents a case study on integrating Agile Systems Engineering methodologies in the preliminary design phase of satellite systems, focusing on the ³ColStar satellite mission. Through Model-Based Systems Engineering (MBSE), technical consistency was rigorously managed across various architectural documents, ensuring coherency and minimizing errors. Furthermore, the preliminary design was developed, with the implementation of the Arcadia Method, supported by the Capella modeling tool. This allowed the digitalization of the system, which was represented by models that contain requirements, architecture, and interfaces between the different parts of the system. At the same time, the preliminary design process was streamlined and completed within an accelerated time frame of 4 months, with weekly sprints driving progress based on the scrum methodology. This case study highlights the effectiveness of Agile Systems Engineering principles to improve the team communication accuracy, communication, and efficiency of satellite systems preliminary design, providing valuable insights for future missions. Full article

Market trends in the space sector suggest a notable increase in satellite operations and market value for the coming decade. In parallel, there has been a shift in the industrial and academic sectors from traditional Document-Based System Engineering to Model-based systems engineering (MBSE) combined with Concurrent engineering (CE) practices. Due to growing demands, the drivers behind this change have been the need for quicker and more cost-effective design processes. A key challenge in this transition remains to determine how to effectively formalize and exchange data during all design stages and across all discipline-specific tools; as representing systems through models can be a complex endeavor. For instance, during the Preliminary design (PD) phase, the integration of system models with external mathematical models for simulations, analyses, and system budgeting is crucial. The introduction of CubeSats and their standard has partly addressed the question of standardization and has aided in reducing overall development time and costs in the space sector. Nevertheless, questions about how to successfully exchange data endure. This paper focuses on formalizing a CubeSat model for use across various stages of the PD phase. The entire process is conducted with the exclusive use of open-source tools, to facilitate the transparency of data integration across the PD phases, and the overall life cycle of a CubeSat. The paper has two primary outcomes: (i) developing a generic CubeSat model using Systems modeling language (SysML) that includes data storage and visualization through the application of Unified modeling language (UML) stereotypes, streamlining in parallel information exchange for integration with various simulation and analysis tools; (ii) creating an end-to-end use case scenario within the Nanostar software suite (NSS), an open-source framework designed to streamline data exchange across different software during CE sessions. A case study from a theoretical academic space mission concept is presented as the illustration of how to utilize the proposed formalization, and it serves as well as a preliminary validation of the proposed formalization. The proposed formalization positions the CubeSat SysML model as the central data source throughout the design process. It also supports automated trade-off analyses by combining the benefits of SysML with effective data instantiating across all PD study phases. Full article

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

The use of different techniques and tools is a common practice to cover all stages in the development life-cycle of systems generating a significant number of work products. These artefacts are frequently encoded using diverse formats, and often require access through non-standard protocols and formats. In this context, Model-Based Systems Engineering (MBSE) emerges as a methodology to shift the paradigm of Systems Engineering practice from a document-oriented environment to a model-intensive environment. To achieve this major goal, a formalised application of modelling is employed throughout the life-cycle of systems to generate various system artefacts represented as models, such as requirements, logical models, and multi-physics models. However, the mere use of models does not guarantee one of the main challenges in the Systems Engineering discipline, namely, the reuse of system artefacts. Considering the fact that models are becoming the main type of system artefact, it is necessary to provide the capability to properly and efficiently represent and retrieve the generated models. In light of this, traditional information retrieval techniques have been widely studied to match existing software assets according to a set of capabilities or restrictions. However, there is much more at stake than the simple retrieval of models or even any piece of knowledge. An environment for model reuse must provide the proper mechanisms to (1) represent any piece of data, information, or knowledge under a common and shared data model, and (2) provide advanced retrieval mechanisms to elevate the meaning of information resources from text-based descriptions to concept-based ones. This need has led to novel methods using word embeddings and vector-based representations to semantically encode information. Such methods are applied to encode the information of physical models while preserving their underlying semantics. In this study, a text corpus from MATLAB Simulink models was preprocessed using Natural Language Processing (NLP) techniques and trained to generate word vector representations. Then, the presented method was validated using a testbed of MATLAB Simulink physical models in which verbalisations of models are transformed into vectors. The effectiveness of the proposed solution was assessed through a use case study. Evaluation of the results demonstrates a precision value of 0.925, a recall value of 0.865, and an F1 score of 0.884. Full article

The current industrial facility market necessitates the digitization of both production and infrastructure to ensure compatibility. This digitization is presently accomplished using Building Information Modeling and digital twin technologies, as well as their integrated usage, which enhances convergence and adds further value to facility assets. However, these technologies primarily focus on the physical components of industrial facilities, neglecting processes, requirements, and functions. To address these gaps, the inclusion of the Model-Based System Engineering approach, a proven benchmark in systems engineering, is essential. This inclusion is the main objective of this research. This article outlines methods and principles for integrating Model-Based System Engineering into the informational modeling of existing industrial facilities to address current market gaps. It offers practical steps for such integration and compares it to other methods, positioning Model-Based System Engineering as a pivotal tool for enhancing the value of industrial facility digital assets. The main findings include the proposal of BIM and MBSE integration, which aims to create a competitive advantage for industrial facilities by improving customer service and operational efficiency, requiring collaboration from various stakeholders. Full article

This paper shows how a methodical development and configuration of modular product family concepts and their effects on economic targets can be implemented in SysML. For this purpose, different sources of inconsistency between different methodical tools are highlighted and the need for research is shown. As a solution approach, a methodical framework is presented, which can be used to implement product development methods for the developing of modular product family modeling by means of Model-Based Systems Engineering (MBSE) in the modeling language SysML. By applying the framework, it is shown on the one hand how a product family of vacuum cleaner robots as a simple example can be modularized in a methodical, model-based manner. On the other hand, a configuration system and an impact model of modular product families are connected with the system model and applied to a product family of laser systems as an industrial use case. This made it clear that the framework can be used to model various methodical topics of product family modeling in a consistent manner, to enable higher-level analyses with the use of MBSE tools. This can reduce errors, decrease effort and increase traceability across different methodical tools. Full article

In a trend towards digital continuity, model-based systems engineering is becoming widely adopted for the design of complex systems, supporting system development from the very first stages. A narrow panel of methods and tools are available on the market; they offer different scopes and approaches, are more or less intuitive to follow, and are sometimes supported by tools. Among them, the Architecture Analysis & Design Integrated Approach (ARCADIA) is becoming popular and is gradually spreading in different industrial fields to model a wide variety of systems at different stages of their development and from different points of view. It is implemented using an open-source tool called Capella. Few feedback on its use in industrial settings have been published, while other feedback remains confidential. The goal of this paper is to analyze the interests and limitations of ARCADIA/Capella. To reach this goal, we experimented with ARCADIA/Capella in several projects and chose one to explain how the method and tool proceeded. In addition, we conducted a survey to obtain industrial feedback. As a result, the paper gives an overview of the relevance of ARCADIA/Capella in projects and of its usefulness, effectiveness, and adaptability in modeling different types of systems. It also provides some perspectives for the evolution of the method and the tool according to industrial feedback. Full article

In recent years, the methodology of Model-Based System Engineering (MBSE) has become relevant to the design of complex products, especially when safety critical systems need to be addressed. It allows, in fact, the deployment of product development directly through some digital models, allowing an effective traceability of requirements, being allocated upon the system functions, components, and parts. This approach enhances the designer capabilities in controlling the product development, manufacturing and after-market services. However, the application of such a methodology requires overcoming several technological barriers, especially in terms of models integration. The interoperability and management of several models—developed within different software to cover multiple levels of detail across several technical disciplines—is still very difficult, despite the level of maturation achieved by Systems Engineering. This paper describes a possible approach to provide such a connection between tools to allow a complete multi-disciplinary and heterogeneous simulation to analyse complex systems, such as safety-critical ones, which are typical of aerospace applications. Such an application is within a defined industrial context, placing particular attention on the compatibility of the approach with the legacy processes and tools. Full article

This scientific article discusses the process of digital transformation of enterprises, analyzed as complex technical systems. Digital transformation is essential for businesses to remain competitive in the global marketplace. One of the effective tools for such a transformation is model-based systems engineering (MBSE). However, there is a gap in the practical application of knowledge regarding the uniform principles for the formation of a digital representation of complex technical systems, which limits the realization of the cross-industry potential of digital transformation in the economy. The motivation for this study is to identify common cross-industry principles for the formation of digital representations of complex technical systems that can lead companies to a sustainable and successful digital transformation. The purpose of this work is to identify and formulate these principles through an analysis of publications, using an inductive approach and classifying them by the category of application. As a result of the study, 23 principles were obtained, and the degree of their use in various industries associated with complex technical systems was determined. The results of this study will help to solve the problem of cross-industry integration and guide systemic changes in the organization of enterprises during their digital transformation. Full article

Model-Based Software Engineering (MBSE) is an architecture-based software development approach. Agile, on the other hand, is a light system development approach that originated in software development. To bring together the benefits of both approaches, this article proposes an integrated Agile MBSE approach that adopts a specific instance of the Agile approach (i.e., Scrum) in combination with a specific instance of an MBSE approach (i.e., Model-Based System Architecture Process—“MBSAP”) to create an Agile MBSE approach called the integrated Scrum Model-Based System Architecture Process (sMBSAP). The proposed approach was validated through a pilot study that developed a health technology system over one year, successfully producing the desired software product. This work focuses on determining whether the proposed sMBSAP approach can deliver the desired Product Increments with the support of an MBSE process. The interaction of the Product Development Team with the MBSE tool, the generation of the system model, and the delivery of the Product Increments were observed. The preliminary results showed that the proposed approach contributed to achieving the desired system development outcomes and, at the same time, generated complete system architecture artifacts that would not have been developed if Agile had been used alone. Therefore, the main contribution of this research lies in introducing a practical and operational method for merging Agile and MBSE. In parallel, the results suggest that sMBSAP is a middle ground that is more aligned with federal and state regulations, as it addresses the technical debt concerns. Future work will analyze the results of a quasi-experiment on this approach focused on measuring system development performance through common metrics. Full article