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Digital Twin's Anatomy: A Cross-Sector Framework With Healthcare Validation

IEEE ACCESS 2025年 13卷 21306-21334页

作者： Araghi, Sina Namaki Liu, Zhengyu Sarkar, Arkopaul Louge, Thierry Karray, Mohamed Hedi Tarbes Univ Technol UTTOP Engn Sch ENIT Prod Engn Lab LGP F-65000 Tarbes France

Digital twins (DT) in manufacturing, healthcare, and across different industrial domains are often over-simplified as solely a virtual representation of a physical object or service. Such a definition constitutes a dilemma in distinguishing DTs from digital models, digital shadows, digital threads, and cyber-physical systems. In this article, we aim to elucidate the concept of digital twins and its definition. Therefore, we go through the connotation of digital twins, which has its roots in space exploration and product-life cycle management, and describe the four evolution stages of DT developments. This article employs an ontological approach to clearly and comprehensively define digital twins and related key concepts, including digital models, assets, prototypes, shadows, and threads. Additionally, it presents a structured framework detailing the meta-model and the reference-level ontology of digital twins. To evaluate the proposed structure, definitions, and its important entities, we have examined our framework against 73 peer-reviewed papers in the healthcare sector from 2018 until July 2024. The evaluation and classification criteria of the selected works were based on four research questions. These criteria are driven by the core definitions provided by the main cross-domain digital twin researchers and this article's proposed anatomy of digital twins.

关键词： Digital twins digital threads digital threads model-based system engineering model-based system engineering cyber-physical systems ontology ontology digital transformation digital transformation Industry 4.0 Industry 4.0 cross-domain digital twin applications cross-domain digital twin applications

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Product complexity management enabled by a model-based approach

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COMPUTERS & INDUSTRIAL engineering 2025年 200卷

作者： Hu, Zhenchao Chen, Jinwei Li, Yuanfu Lu, Jinzhi Zhang, Huisheng Kiritsis, Dimitris Shanghai Jiao Tong Univ Shanghai 200240 Peoples R China Beihang Univ Beijing 100191 Peoples R China Ecole Polytech Fed Lausanne CH-1015 Lausanne Switzerland

As contemporary engineered systems become more interdependent, there is a growing need to manage their system complexity. However, system complexity only exists as implicit and heterogeneous information. This situation makes it difficult to obtain and analyze system complexity. This paper proposes a model-based approach to supporting system complexity management, called MBCM, where system complexity includes dynamic complexity and structural complexity. The proposed approach includes complexity modeling and complexity analysis. For complexity modeling, a graph-matrix hybrid complexity modeling approach is proposed to describe the dynamic and structural complexity information. Graph-based architecture models are developed by a unified meta-meta modeling approach. The connections among different architecture models are then described using a design structure matrix. For complexity analysis, a general complexity metric provides dynamic and structural complexity values for the designer to evaluate the system. Moreover, automatic ontology modeling is introduced to integrate complexity modeling and complexity analysis. Finally, a case study on aero-engine design was conducted. The complexity management processes of three different scenarios were compared in this case study. The comparison results show that our approach could sensitively represent increased product complexity from both dynamic and structural aspects. Thus, the proposed approach is general and applicable to any engineered system and can support the trade-off between complex product design schemes.

关键词： Complexity management Complexity modeling Complexity analysis model-based system engineering Design structure matrix Ontology modeling

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Heterogeneous knowledge graph-driven subassembly identification with ensemble deep learning in Industry 4.0

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2025年第9期63卷 3175-3191页

作者： Zhang, Chao Jing, Yanzhen Zhou, Guanghui Yan, Hairui Chang, Fengtian Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710054 Peoples R China Changan Univ Sch Construct Machinery Xian Peoples R China

In the context of Industry 4.0, model-based definition (MBD) has been an effective approach to creating 3D models contained all heterogeneous information needed to define a product, which proposes new challenges for the traditional subassembly identification method that only considers the geometric information of a product in assembly sequence planning. To bridge the gap, we propose a novel heterogeneous knowledge graph-driven subassembly identification method to enhance assembly sequence planning in the model-based systems engineering (MBSE) paradigm. Specifically, a heterogeneous knowledge graph is first constructed based on the shape information and engineering details of an MBD model. Next, an ensemble deep learning approach that combines graph neural networks with the community detection algorithm is proposed to effectively detect the subassembly from the MBD model. Finally, the feasibility and effectiveness of the proposed method are demonstrated through an example of car suspension subassembly identification, providing insight into the industrial implementation.

关键词： Knowledge graph ensemble deep learning model-based definition model-based system engineering subassembly identification

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Surrogate model-based cognitive digital twin for smart remote maintenance of fusion reactor: modeling and implementation

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NUCLEAR FUSION 2024年第12期64卷 126007-126007页

作者： Yao, Zhixin Wu, Huapeng Song, Yuntao Cheng, Yong Pan, Hongtao Wu, Muquan Li, Ming Qin, Guodong Wang, Qi Zhang, Xi Shenzhen Univ Coll Phys & Optoelect Engn Shenzhen 518060 Peoples R China Chinese Acad Sci Inst Plasma Phys Hefei Inst Phys Sci Hefei 230031 Peoples R China Lappeenranta Univ Technol Lappeenranta Finland Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan 430074 Peoples R China

A remote maintenance robot system (RMRS) plays a critical role in safeguarding the fusion energy experimental device's security and stability. State-of-the-art intelligent technology such as cognitive digital twins (CDTs) is widely considered capable of improving complex equipment's performance and reducing management burden using a visualized system. However, the CDT virtual space cannot mirror the RMRS which is a kind of flexible multi-body system in real-time and with high fidelity. Therefore, we propose a CDT modeling method based on a surrogate model for the RMRS. Firstly, model-based system engineering is leveraged to build a structural modular architecture, which can decrease the modeling complexity of CDT and increase the modeling efficiency. Then, the surrogate models are self-learning within the CDT physical space, which reconstructs the RMRS's real-time dynamic performances and endows CDT with cognitive capabilities. Finally, after integrating the CDT system, a smart decision-making plan that compensates for the operation error is generated for RMRS's accurate control. We take a China Fusion engineering Test Reactor (CFETR) multi-purpose overload robot (CMOR) as an example to demonstrate the implementation process. According to the results, CDT can achieve real-time (230 ms time delay) high-fidelity (5 mm control error) monitoring and accurate control, and CMOR conducts smart maintenance based on the simulation results. This method improves the efficiency of remote maintenance and provides solutions for high-duty cycle time of CFETR, it can also be applied to other tokamak fusion energy devices.

关键词： cognitive digital twin model-based system engineering surrogate model error compensation-based precision control fusion reactor smart maintenance

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Handling complexity of large high-level specifications in simulation environment: the case of transformational model-battle management

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JOURNAL OF DEFENSE modelING AND SIMULATION-APPLICATIONS METHODOLOGY TECHNOLOGY-JDMS 2024年

作者： Alshareef, Abdurrahman Kim, Doohwan King Saud Univ Coll Comp & Informat Sci Dept Informat Syst POB 2454 Riyadh 11451 Saudi Arabia RTSync Corp Chandler AZ USA

modeling system requirements at a high level can significantly facilitate the communication of mental models across highly heterogeneous entities. Two major challenges may arise during such a process. The first is the degree to which details of the higher-level specifications can capture and effectively handle. Especially, when the model contains more nuanced descriptions of parallel execution and temporal pacing. The second challenge arises when realizing such specifications downstream due to ambiguities and incompleteness encountered in higher-level semiformal artifacts. We propose a formal specification and transformation of higher-level artifacts, particularly in the operational activity model of the Department of Defense Architecture Framework (OV-5 DoDAF). We create an isomorphic activity model corresponding to each activity in the Transformational model-Battle Management. Then, we generate a code for simulating the models as Markov Discrete Event system Specifications. We demonstrate the size and other aspects of the experiments that can be conducted based on the generated simulation and the level of complexity in such an approach. We highlight aspects of managing complexity using model transformations and code generation techniques in a full-cycle model-based system engineering approach, expediting the process toward arriving at the concrete realization of simulation models that only originated from minimal high-level metamodels and artifacts.

关键词： Activity diagrams model-based system engineering system modeling language theory of modeling and simulation transformational model-battle management Unified modeling Language

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Analysis of system Radiation Effects Using Markov Chains

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2025年第4期72卷 1108-1115页

作者： Hansen, D. L. Manich, T. Zavatkay, I. L3 Harris T&RF San Diego CA 92123 USA L3 Harris SAS Rochester NY 14606 USA

Continuous time Markov chains (CTMCs) provide a mathematical framework for calculating system upset rates. The method is able to handle the calculation in cases where the system has multiple devices each of which may have a multitude of possible failure mechanisms. It can also account for the fact that failure mode effects can vary based on the current operating state. This article uses the concepts of CTMCs to calculate failure rates in a flight-like satellite system. The method is used to determine the most vulnerable part of the system and identify where hardening techniques are most useful. Different system hardening methods are compared.

关键词： Mathematical models Satellites systems modeling Language Random access memory Orbits Field programmable gate arrays Circuit faults Vectors Termination of employment systems operation Heavy ion Markov chain model-based system engineering prediction tool single event effects (SEE) systems modeling language (SysML)

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Toward Conceptual Analysis of Cyber-Physical systems Projects Focusing on the Composition of Legacy systems

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IEEE ACCESS 2023年 11卷 58136-58158页

作者： Ivo, Andre A. S. Ribeiro, Sheila Granato Mattiello-Francisco, Fatima Bondavalli, Andrea Natl Ctr Monitoring & Alert Nat Disasters CEMADEN BR-12247016 Sao Jose Dos Campos Brazil Natl Inst Space Res INPE BR-12227010 Sao Jose Dos Campos Brazil Univ Florence Dept Math & Informat I-50142 Florence Italy

The increase in connectivity and the continued need to evolve existing systems impose on system engineers the reality of dealing with system of systems (SoS) concept in practice. The composition of legacy systems presents significant challenges, especially when a Cyber-Physical system (CPS) is involved. Due to the complexity of the interactions between CPS computational solutions and the physical environment, added to the operational independence of CPS as constituent system, emergent behaviors might unpredictably emerge when the CPS and other system run to collaborate being difficult to control. The purpose of this article is to present the Discovery and Requirement Canvas method and its contributions on highlighting emergent behavior. Introduced in the context of EMBED-SoSE approach, the method supports the process of designing a CPSoS in the early phases of a project, when the stakeholders' needs, constraints, and alternatives must be analyzed in terms of the integration possibilities of existing constituent systems. An experimental study conducted with 22 senior professionals from the software and aerospace industries validates the practicability of the method Discovery & Requirement Canvas demonstrating its efficacy. The results of the experiment are compared using descriptive and inferential statistics. In addition, the method was applied to a real-world case study in the field of monitoring natural disasters.

关键词： system of systems cyber-physical systems Internet of Things systems engineering model-based system engineering

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Architecting decentralized control in large-scale self-adaptive systems

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COMPUTING 2023年第9期105卷 1849-1882页

作者： Andersson, Jesper Caporuscio, Mauro D'Angelo, Mirko Napolitano, Annalisa Linnaeus Univ Vaxjo Sweden Ericsson Res Gothenburg Sweden IMT Sch Adv Studies Lucca Italy

Architecting a self-adaptive system with decentralized control is challenging. Indeed, architects shall consider several different and interdependent design dimensions and devise multiple control loops to coordinate and timely perform the correct adaptations. To support this task, we propose Decor, a reasoning framework for architecting and evaluating decentralized control. Decor provides (i) multi-paradigm modeling support, (ii) a modeling environment for MAPE-K style decentralized control, and (iii) a co-simulation environment for simulating the decentralized control together with the managed system and estimating the quality attributes of interest. We apply the Decor in three case studies: an intelligent transportation system, a smart power grid, and a cloud computing application. The studies demonstrate the framework's capabilities to support informed architectural decisions on decentralized control and adaptation strategies.

关键词： Reasoning framework model-based system engineering Multi-paradigm modeling Co-simulation

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A Survey of Advanced Information Fusion system: from model-Driven to Knowledge-Enabled

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DATA SCIENCE AND engineering 2023年第2期8卷 85-97页

作者： Zhu, Di Yin, Hailian Xu, Yidan Wu, Jiaqi Zhang, Bowen Cheng, Yaqi Yin, Zhanzuo Yu, Ziqiang Wen, Hao Li, Bohan Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing 211106 Peoples R China Nanjing Univ Aeronaut & Astronaut Key Lab Adv Technol Small & Medium UAVs Minist Ind & Informat Technol Nanjing 210016 Peoples R China Yantai Univ Coll Comp & Control Engn Yantai 264005 Shandong Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Aerosp Engn Nanjing 210016 Peoples R China

Advanced knowledge engineering (KE), represented by knowledge graph (KG), drives the development of various fields and engineering technologies and provides various knowledge fusion and knowledge empowerment interfaces. At the same time, advanced system engineering (SE) takes model-based system engineering (MBSE) as the core to realize formal modeling and process analysis of the whole system. The two complement each other and are the key technologies for the transition from 2.0 to 3.0 in the era of artificial intelligence and the transition from perceptual intelligence to cognitive intelligence. This survey summarizes an advanced information fusion system, from model-driven to knowledge-enabled. Firstly, the concept, representative methods, key technologies and application fields of model-driven system engineering are introduced. Then, it introduces the concept of knowledge-driven knowledge engineering, summarizes the architecture and construction methods of advanced knowledge engineering and summarizes the application fields. Finally, the combination of advanced information fusion systems, development opportunities and challenges are discussed.

关键词： system engineering Knowledge engineering Knowledge graph model-based system engineering Information system

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model-based Automated Safety Analysis Method for Safety-critical system 5

Model-based Automated Safety Analysis Method for Safety-crit...

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5th International Conference on Mechatronics Technology and Intelligent Manufacturing (ICMTIM)

作者： Xu, Xinyan Wei, Ran Wang, Haochi Dalian Univ Technol Sch Control Sci & Engn Dalian Liaoning Peoples R China

ISBN: (纸本)9798350363272;9798350363265

In safety-critical systems, the repercussions of system failures can be dire, encompassing significant losses in terms of human lives, property damage, and environmental impact. As systems grow in complexity, the burden of conducting safety analyses escalates as well. To streamline the system development process and alleviate this workload, automated safety analysis methods are indispensable. In this paper, we introduce an innovative automated safety analysis technique that hinges on the iterative utilisation of Failure Mode and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) - termed the FMEA and FTA iterative analysis (FMEA-FTAia). Central to FMEA-FTAia is the integration of the system model with the system failure model, establishing a cohesive linkage to the fault tree model for unified change management. While FMEA delves into an exhaustive examination of component failure modes, FTA pinpoints vulnerabilities within the system. By integrating FMEA and FTA, a comprehensive safety analysis framework is formed. Additionally, in this article we propose a novel fault tree generation methodology. Furthermore, we discuss a model-based tool - FMEA-FTAia tool - designed to support the implementation of FMEA-FTAia and facilitate efficient safety analysis processes. And we designed the Analysis Architecture Metamodel (SAAM) to support FMEA-FTAia tool.

关键词： FMEA FTA Safety-critical system model-based system engineering

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