Model-Based Systems Engineering Approach Research Articles

Human Factors Engineering (HFE) Considerations for Mounting Internal Interfaces in Heavy Vehicles

Trucking fleets often need to install additional displays and consoles in vehicles to interface with the driver. These devices may be used for fleet management, assistance with logistics, or connecting to business applications. However, if these devices are installed without consideration of the drivers, the users may become distracted or frustrated with the system. Therefore, a human factors engineering (HFE) approach to the installation of additional console(s) reduces the likelihood of rework, distractions, and driver inconvenience. Model-based systems engineering (MBSE) approach utilizing best practices for HFE design is presented in this paper. The results of the effort are captured with a prototype assembly bracket used in the production version of the heavy vehicle. The plan-do-study-act (PDSA) model-based human factors systems engineering methodology demonstrates efficiencies in the design and implementation of the display system. This method proved effective as new mounts were fitted in a preproduction electric vehicle before they were released in production.

Model‐based systems engineering and safety assessment: A workflow for mechatronic systems design

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

Applying MBSE to Optimize Satellite and Payload Interfaces in Early Mission Phases

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.

A Model-Based Systems Engineering Approach for Effective Decision Support of Modern Energy Systems Depicted with Clean Hydrogen Production

A Model-Based Systems Engineering Approach for Effective Decision Support of Modern Energy Systems Depicted with Clean Hydrogen Production

Model‐Based Systems Engineering Approach for Designing an Artificial Magnetic Field Generator System for Spacecraft Radiation Protection

AbstractThe hazardous environment of space, dominated by cosmic and solar radiation, poses a significant threat to spacecraft and their occupants. Traditional radiation shielding methods, like passive materials, have limitations in weight and effectiveness. An artificial magnetic field generator system emerges as a promising solution to replicate Earth's magnetosphere, providing a protective magnetic shield against harmful radiation. (Dick, Launius, 2007) This paper presents a Model‐Based Systems Engineering (MBSE) approach to the holistic modeling and design of such a system.Utilizing the MBSE approach, this study models the system's components, their interactions, and the offered services, incorporating Radiation Monitoring, Magnetic Shielding, Power Management, System Health & Diagnostics, and Crew Communication services. The conceptual data model captures key entities and their relationships, ensuring a coherent integration of the system's parts. The activity diagram illustrates the operational flow, providing clarity on the system's dynamic behavior under varying radiation conditions and power reserves. A services taxonomy is developed to hierarchically categorize and ensure the comprehensive functionality of the system.The application of MBSE methodology provides numerous advantages, including a unified visualization of the system's complexities, enhanced stakeholder communication, and a streamlined validation and verification process. Furthermore, the flexibility inherent in the MBSE approach ensures that the system can be easily updated or scaled based on advancements in technology or changing mission requirements. (ECLIPSE Suite, 2022) The MBSE approach's application to the design of an artificial magnetic field generator system for spacecraft presents a robust and systematic method to ensure optimal performance, safety, and adaptability in the perilous realm of space.

A MODULAR SIMULATION‐BASED MBSE APPROACH APPLIED TO A CLOUD‐BASED SYSTEM

AbstractThe current state of the practice of Model‐Based Systems Engineering (MBSE) methodologies, system specification models, and executable system simulations lack the capability of simulation execution within a single system specification model with the fidelity required for time‐dependent simulation towards the design, analysis, and optimization of complex software‐based systems. In this paper we develop and demonstrate a modular simulation‐based MBSE approach capable of filling this gap. To accomplish this within a single system specification model we embed a combination of modeled simulation activities, opaque behaviors, and simulation specific functions to execute and manage the time‐dependent simulation variable arrays. We applied our MBSE approach on the design and analysis of a hybrid on‐prem/cloud data system example that meets the complex, software‐based, and time‐dependent requirements this approach was built to solve. The results show that our approach produces a modular and time‐dependent simulation‐enabled system specification model that accurately estimates cloud‐based system performance and storage cost as a function of time. Emergent system behaviors observed from the simulation results indicate the system model provides foundational design and analysis capabilities that are required for applying system optimization algorithms.

Promoting Neurodiversity Through MBSE and Other Technical Approaches

AbstractThe 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.

Hyundai's Modular MBSE Approach to ‘Purpose Built Vehicle’ Architecture Development

AbstractThis 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.

Implementing the model-based systems engineering (MBSE) approach to develop an assessment framework for healthcare facility design

AbstractThe global elderly population rises, increasing dementia cases. Built environment impact on dementia health outcomes is known, forming the basis for evidence-based design studies. There's a need for a comprehensive assessment framework due to the complexity of interactions among Architectural Variables (AVs) and Health and Care Outcomes (HCOs). This paper proposes using Model-Based Systems Engineering (MBSE) to create such a framework. It collects data from 105 studies on 40 AVs, 36 HCOs, and 396 interactions. MBSE offers a holistic understanding, aiding healthcare facility design decisions.

A semantic model-based systems engineering approach for assessing the operational performance of metal forming process

Metal Forming is a basic and essential industrial process to provide materials for constructing complex products. To design an efficient metal forming process, the functional requirements and operational performance are two important aspects to be considered. In this paper, a semantic Model-based Systems Engineering (sMBSE) approach is proposed to support the design of the entire metal forming process. A multi-architecture modeling language KARMA is used to develop meta-models and architecture models of the metal forming process from the perspectives of mission, operation, function, logic flow and physical structure. Enabled by customized software, the KARMA models are transformed to ontology models, which are then converted to Petri Net (PN) models. Simulations are conducted based on the PN models to evaluate the operational performance of the created processes. A case study based on a real metal forming scenario is conducted to evaluate the proposed approach using quantitative and qualitative analysis. The result proves that the proposed approach enables to formalize the entire architecture modeling for metal forming process; and to provide an efficient approach for evaluating the operational performance of the designed solution for initial verification.

Co-Design and Energy Management for Future Vessels

The maritime industry is undergoing a significant shift towards more sustainable and efficient forms of transportation. As a result, designing Power, Propulsion and Energy (PPE) Systems for future vessels presents new challenges that require a systematic approach that reduces the risk in development and implementation. This paper focuses on three aspects of such a systematic approach: Model-Based System Engineering (MBSE), Co-design, and Verification and Validation. The MBSE approach can be used to mitigate the risks associated with the transition by maintaining a clear traceability of user needs, functional requirements and physical realizations. A rigorous needs analysis and functional design reduces the optimisation design space that results in a significant reduction in the complexity of a design optimisation problem. Further, co-design is discussed as a methodology for a combined optimisation of the hardware and software design where the Modular Energy Management approach supports automated controller generation for the optimisation, a key challenge when optimising PPE systems. An important aspect of the MBSE approach is the use of models for the verification and validation of the developed designs. However, the successful use of models is contingent on their applicability. This paper proposes a way to categorise model confidence for verification and validation studies.

Shaping Extended Product Design and Development with Predictive Maintenance Capability for Digital Servitisation

Traditional business models of selling a product as a single item can no longer satisfy the growing service-oriented needs of customers. Service-oriented business models, like servitisation or product-service systems (PSS), have been introduced to respond to this market demand. Predictive maintenance (PdM) strategy is regarded as a key element in the development of such business models because of its effective role in maximising the availability and usability of products. The PdM strategy requires technologies including, sensing, data acquisition, data analytics algorithms and decision support tools. In traditional business models, these technologies are typically developed by third parties when products are already commissioned or in service, which is sub-optimal. It can be argued that PdM technologies developed by original equipment manufacturers (OEMs) can significantly reduce development costs and increase competitiveness. This paper proposes a new framework for guiding OEMs to develop and integrate relevant PdM technologies during the development of new products in support of their new journey in a digital servitisation business model. This encompasses the full life cycle of the product from customers’ needs/values analysis to after-sales service. The model-based system engineering (MBSE) approach was adopted to implement the proposed framework using the selected system modelling language (SysML) tool, namely Capella, and to verify it in an industrial case study.

Model-Based Systems Engineering Approach to Design a Human Settlement to Better Serve Displaced People

Model-Based Systems Engineering Approach to Design a Human Settlement to Better Serve Displaced People

Operation Principles of the Industrial Facility Infrastructures Using Building Information Modeling (BIM) Technology in Conjunction with Model-Based System Engineering (MBSE)

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.

Architecting a Digital Twin-Based Predictive Maintenance System for Modelling Cable Joint Degradation

The large scale adoption of wind turbines and solar panels in the Netherlands places new demands on the medium voltage power grid. For example, highly varying loads can cause failures in certain cables. Cable joints are natural weak spots prone to faults due to varying currents, creating downtime challenges for public utility companies. Predictive maintenance (PdM) practices are necessary to minimize downtime for users. We present a Model-Based System Engineering approach using formal models and UML views to provide a scalable PdM design ontology for modeling cable joint degradation. We aim to monitor cable joint degradation from different manufacturers under varying conditions throughout the Netherlands in real-time using a Digital Twin (DT) approach. Our design provides high-resolution, real-time synchronization between the DT-based PdM system and the cable joints. The proposed architecture is scalable, robust, and flexible, and the software implementation is publicly available in an open-source repository.

An Overview of Safety and Security Analysis Frameworks for the Internet of Things

The rapid progress of the Internet of Things (IoT) has continued to offer humanity numerous benefits, including many security and safety-critical applications. However, unlocking the full potential of IoT applications, especially in high-consequence domains, requires the assurance that IoT devices will not constitute risk hazards to the users or the environment. To design safe, secure, and reliable IoT systems, numerous frameworks have been proposed to analyse the safety and security, among other properties. This paper reviews some of the prominent classical and model-based system engineering (MBSE) approaches for IoT systems’ safety and security analysis. The review established that most analysis frameworks are based on classical manual approaches, which independently evaluate the two properties. The manual frameworks tend to inherit the natural limitations of informal system modelling, such as human error, a cumbersome processes, time consumption, and a lack of support for reusability. Model-based approaches have been incorporated into the safety and security analysis process to simplify the analysis process and improve the system design’s efficiency and manageability. Conversely, the existing MBSE safety and security analysis approaches in the IoT environment are still in their infancy. The limited number of proposed MBSE approaches have only considered limited and simple scenarios, which are yet to adequately evaluate the complex interactions between the two properties in the IoT domain. The findings of this survey are that the existing methods have not adequately addressed the analysis of safety/security interdependencies, detailed cyber security quantification analysis, and the unified treatment of safety and security properties. The existing classical and MBSE frameworks’ limitations obviously create gaps for a meaningful assessment of IoT dependability. To address some of the gaps, we proposed a possible research direction for developing a novel MBSE approach for the IoT domain’s safety and security coanalysis framework.

Agile Methodology for the Standardization of Engineering Requirements Using Large Language Models

The increased complexity of modern systems is calling for an integrated and comprehensive approach to system design and development and, in particular, a shift toward Model-Based Systems Engineering (MBSE) approaches for system design. The requirements that serve as the foundation for these intricate systems are still primarily expressed in Natural Language (NL), which can contain ambiguities and inconsistencies and suffer from a lack of structure that hinders their direct translation into models. The colossal developments in the field of Natural Language Processing (NLP), in general, and Large Language Models (LLMs), in particular, can serve as an enabler for the conversion of NL requirements into machine-readable requirements. Doing so is expected to facilitate their standardization and use in a model-based environment. This paper discusses a two-fold strategy for converting NL requirements into machine-readable requirements using language models. The first approach involves creating a requirements table by extracting information from free-form NL requirements. The second approach consists of an agile methodology that facilitates the identification of boilerplate templates for different types of requirements based on observed linguistic patterns. For this study, three different LLMs are utilized. Two of these models are fine-tuned versions of Bidirectional Encoder Representations from Transformers (BERTs), specifically, aeroBERT-NER and aeroBERT-Classifier, which are trained on annotated aerospace corpora. Another LLM, called flair/chunk-english, is utilized to identify sentence chunks present in NL requirements. All three language models are utilized together to achieve the standardization of requirements. The effectiveness of the methodologies is demonstrated through the semi-automated creation of boilerplates for requirements from Parts 23 and 25 of Title 14 Code of Federal Regulations (CFRs).

From Requirements to Product: an MBSE Approach for the Digitalization of the Aircraft Design Process

AbstractDuring the aircraft conceptual design phase, many different design options need to be explored and compared in a short time frame. To speed up this process, efforts have been made in the past decades to digitalize parts of the design process, with a focus on the automation of the repetitive and non‐creative tasks inherent to the iterative design process. Whilst many of the newly developed methodologies focus on specific parts of the design process, a holistic model‐based design framework, incorporating the latest design technology developments, is lacking. To fill this gap, this paper presents the latest version of the Design and Engineering Engine (DEE) framework, originally proposed in the early 2000s and progressively matured through the experience of several international research collaborations. The DEE enables the setup and execution of Multidisciplinary Design Analysis and Optimization (MDAO) problems for aircraft (sub)systems, leveraging the automated, rule‐based modeling capabilities offered by Knowledge‐Based Engineering (KBE) and recent developments in the automatic formulation and integration of MDAO workflows. While the traditional MDAO process focuses on a given product architecture, the DEE allows also architectural design studies and makes use of Model‐Based Systems Engineering (MBSE) principles to address the whole design process, from requirements modeling up to the automatic verification of the requirements. In practice, the DEE provides a single conceptual framework or template from which specific design framework instances can be formulated and executed, according to the user's needs. This paper describes the DEE architecture and its implementation concepts. Furthermore, it demonstrates the application of the DEE template to four different scenarios, ranging from a simple requirement verification study, up to the simultaneous synthesis and optimization of an aircraft system and its production process, including multiple system architecture options.

PRELIMINARY DESIGN OF NON-LINEAR SYSTEMS BASED ON GLOBAL SENSITIVITY ANALYSIS AND MODELICA LANGUAGE

AbstractIn the last few years, the growing need of highly reliable and time-effective strategies to perform preliminary design of complex systems has led industries to adopt the Model Based System Engineering (MBSE) approach. In MBSE, systems are split into multiple sub-systems and the relevant physical phenomena are described via analytical or numerical models. When a significant number of design variables are to be considered, a smart approach to reduce the number of analyses to perform would be to make use of the Global Sensitivity Analysis (GSA) to higlight those variables that have a more significant influence on the system output. Moreover, an even more significant reduction of computational cost to perform the GSA can be achieved if the complex system modelled via the MBSE approach is exported under the Functional Mock-Up Interface (FMI) norm. In this context, this paper proposes an original approach to address the study of two constructive solutions of an acceleration measuring device typically used on airbags for which the use of a new solution characterized by a porous material is compared with a classical one.

The Application of Model-Based Systems Engineering to Rural Healthcare System Disaster Planning: A Scoping Review

Disasters and other emergency events have complex effects on human systems, particularly if the events are severe or prolonged. When these types of events happen in rural communities, the resources of the local public health, healthcare, and emergency response organizations can be quickly depleted or overwhelmed. Planning for emergencies can help to mitigate their impact. Model-based systems engineering (MBSE) methods, including computer simulations, can provide insight on how best to prepare for these events and to explore the effects of varying approaches and resource utilization. To best apply these methods for improving disaster management in rural settings, a synthesis of the current body of evidence in this field is needed. The objective of this scoping review was to provide a descriptive overview of the application of computer simulation based on MBSE approaches to disaster preparedness and response for rural healthcare systems. Six studies met inclusion criteria, and varied in terms of MBSE method used, healthcare setting, and disaster type and context considered. We identified a gap in the research regarding the application of MBSE approaches to support rural healthcare disaster preparedness planning efforts. Model-based systems engineering and systems thinking, therefore, represent novel methods for developing tools and computational simulations that could assist rural communities better prepare for disasters.