Enabling technologies and tools for digital twin

Digital Twin in Industry: State-of-the-Art

Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2873186 · Cited by 4,391

Digital Twin in manufacturing: A categorical literature review and classification

Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W. (2018) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2018.08.474 · Cited by 3,612

Digital twin-driven product design, manufacturing and service with big data

Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., & Sui, F. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-017-0233-1 · Cited by 2,920

The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles

Glaessgen, E., & Stargel, D. (2012) · 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA · doi:10.2514/6.2012-1818 · Cited by 2,404

Data-driven smart manufacturing

Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2018.01.006 · Cited by 1,934

Deep learning for smart manufacturing: Methods and applications

Wang, J., Ma, Y., Zhang, L., Gao, R. X., & Wu, D. (2018) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2018.01.003 · Cited by 1,740

Digital twin and big data towards smart manufacturing and Industry 4.0: 360 degree comparison

Qi, Q., & Tao, F. (2018) · IEEE Access · doi:10.1109/access.2018.2793265 · Cited by 1,716

A Review of the Roles of Digital Twin in CPS-based Production Systems

Negri, E., Fumagalli, L., & Macchi, M. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.07.198 · Cited by 1,669

Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison

Tao, F., Qi, Q., Wang, L., & Nee, A. Y. C. (2019) · Engineering · doi:10.1016/j.eng.2019.01.014 · Cited by 1,589

About The Importance of Autonomy and Digital Twins for the Future of Manufacturing

Rosen, R., von Wichert, G., Lo, G., & Bettenhausen, K. D. (2015) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2015.06.141 · Cited by 1,474

Chemistry-driven Predictive Modelling of Mechanical Performance in 42CrMo4 (AISI 4140) Steel with Machine Learning

Gupta, S. D., Anand, A., & Krishna, R. (2026) · doi:10.1177/iif.261438647

Next generation risk assessment and new approach methodologies for sustainable management of heavy metal contaminated environments: A critical review

Singh, P. K., Kumar, I., Kumar, U., Singh, R. P., Singh, R. S., & Sharma, R. K. (2026) · Environmental Pollution · doi:10.1016/j.envpol.2026.128415

Adapting the Five-Dimensional Digital Twin Model for On-Demand and Reconfigurable Continuous Flow Chemistry: An Ontological Approach

dib, I., Cunha, C. M. D., & Felpin, F. (2026) · IFIP advances in information and communication technology · doi:10.1007/978-3-032-38598-7_42

Enhancing automation and manufacturing with digital twin systems

Jindal, S., Mishra, A., & Mishra, A. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-45573-5.00033-1

Evidence-Grounded Hybrid Framework for ISO/IEC 17025 Laboratory Operations Audits: A Neuro-Symbolic Decision-Support Approach

Rasyid, S. A., Wiranata, A., Usman, K., Wibowo, S. A., Hantoro, G. D., Syamsul, M., & Prihatini, Y. I. (2026) · Logistic and Operation Management Research (LOMR) · doi:10.31098/lomr.v5i1.4258

Improving equipment reliability in semiconductor wafer fabrication through advanced diagnostic engineering frameworks

Idris, A. (2023) · International journal of machine tools and maintenance engineering. · doi:10.22271/27074544.2023.v4.i1a.79

Introduction to Prototyping: Definitions, Concepts and Enabling Technologies

Kabir, M. R., & Ray, S. (2026) · Synthesis lectures on engineering, science, and technology · doi:10.1007/978-3-032-18938-7_1

Neuroadaptive retailing: How quantum-enhanced biometric systems drive consumer engagement through cognitive and emotional alignment

Sun, J., Faraz, A., Sarfraz, M., & Gul, R. F. (2026) · Acta Psychologica · doi:10.1016/j.actpsy.2026.107177

Analysis of Non-Quality Drivers and Their Root Causes in Development-to-Production Processes

Gamliel, A., & Barron, Y. (2026) · Sustainability · doi:10.3390/su18115597

An Enhanced CAPE-OPEN–Based Digital Twin Platform Architecture for Chemical Processes

Zhao, J., Zhao, W., Sun, X., Xia, L., & Xiang, S. (2026) · ACS Omega · doi:10.1021/acsomega.6c00575

Digital finance literacy, digital infrastructure and digital exclusions: an empirical survey of disadvantaged rural communities in India

Rajarathinam, K. K., Vlachos, I., & Annamalai, C. (2026) · Agricultural Finance Review · doi:10.1108/afr-05-2024-0082

A zone-wise physics-informed surrogate for thermal field reconstruction and operation-window decision support in straight-grate pellet induration

Dai, Z., Wang, Y., Liu, Z., & Zhang, J. (2026) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2026.131765

Spatiotemporal collaborative digital twin structural health monitoring based on dynamic multi-fidelity models

Lu, H., Liu, L., Gao, Z., Yao, Y., Tang, J., Cao, X., & Sun, Y. (2026) · Computers in Industry · doi:10.1016/j.compind.2026.104502

Multi-domain fusion meta-model for digital twin in precision manufacturing: design, implementation and verification

Li, Q., Zeng, P., Wu, Q., Zhang, Z., & Zhang, H. (2026) · Complex & Intelligent Systems · doi:10.1007/s40747-026-02348-7

Semantic modelling of AI-integrated digital twins for enhanced transparency

Shu, Y., Hellicar, A., WANG, W., & Rahman, A. (2026) · Journal of Intelligent Information Systems · doi:10.1007/s10844-026-01065-4

A Long-Term Construction Memory System for Infrastructure Digital Twins with LLM-Augmented Retrieval: A Six-Layer Architecture for Cognitive Memory Encoding, RAG-Based Reasoning, and Lifecycle Decision SupportPreprint

Kim, D. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6947979

A review of digital twin methods and applications for bearings under marine operating constraints

Shi, J., Guo, Z., Gu, J., Zhang, Z., Mi, Z., & Du, F. (2026) · Ships and Offshore Structures · doi:10.1080/17445302.2026.2684687

Towards a Fully Digitalised Filament Winding ProcessPreprint

Mimra, C., Hall, M., Tien, C. M. T., Pattarakunnan, B., Palepu, A., Teakle, P., & Shelley, T. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6968495

Design methodologies and maintenance strategies of air conditioning outdoor unit assembly production line for intelligent manufacturing

Yu, S., Zhou, Z., Feng, Y., Li, G., Yin, X., Li, B., Ma, X., & Li, C. (2026) · Advances in Mechanical Engineering · doi:10.1177/16878132261458445

Decentralized Cooperative Power Dispatch Based on Multi-Agent Reinforcement Learning and Offline Digital Twin Technology for Building Integrated Photovoltaics and Energy Storage System Clusters

Li, Q., Xing, H., Zhu, H., & Li, Z. (2026) · Buildings · doi:10.3390/buildings16132526

Digital Approaches for the Protection of Inner Mongolia’s Paper-Cutting Art as Intangible Cultural Heritage

Chen, J., Daud, W. S. A. W. M., & Omar, M. A. (2026) · Herança · doi:10.52152/heranca.v9i2/1257

Towards Digital Twins success: A mediating analysis of symbolic and functional benefitsPreprint

Raguseo, E., Elia, G., Khan, R. N., & Pigni, F. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6998766

A Safety-Case-Driven Hybrid Digital Twin for Centrifugal Compressor Health Monitoring

Mujawo, H., & Alimi, O. A. (2026) · Machines · doi:10.3390/machines14070712

Simulation and experimental verification of vibration signals for bearing faults in the framework of digital twin

Li, Y. J., Liu, C., Xue, X., & Wu, G. (2026) · Industrial Lubrication and Tribology · doi:10.1108/ilt-12-2025-0567

Data-driven smart wire arc additive manufacturing: a qualification-oriented cyber-physical system framework

Mattera, G., Caggiano, A., & Kusiak, A. (2026) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-026-18517-4

ФОРМУВАННЯ ПОВНОГО ЕЛЕКТРОННОГО ВИЗНАЧЕННЯ ВИРОБУ У СИСТЕМІ ТЕХНІЧНОЇ ПІДГОТОВКИ ВИРОБНИЦТВА БПЛА ЛІТАКОВОГО ТИПУ

Vorobyov, Y., Майорова, К. В., Bogach, O., & Gavrylov, I. (2026) · Aerospace technic and technology · doi:10.32620/aktt.2026.3.07

Context-aware visual digital shadow for augmented monitoring: A Bi-modal discrete event simulation framework

Park, J., & Kim, J. W. (2026) · Simulation Modelling Practice and Theory · doi:10.1016/j.simpat.2026.103317

An improved unsupervised domain adversarial transfer network for motor eccentricity monitoring assisted by simulation data

Zhou, Y., Dong, L., & Shuai, Z. (2026) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2026.114645

Siemens' Industrial Internet of Things and Digital Twin Pioneers New Pathways for Digital Transformation in Manufacturing

Xu, Z. (2026) · Journal of business and marketing. · doi:10.62517/jbm.202609214

Doc2DT: An LLM-Driven Knowledge Graph Abstraction Framework for Digital Twin Generation from Unstructured Engineering DocumentsPreprint

Lee, Y., Choi, S., & Lee, S. W. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7079738

Digital Twin-Based Intelligent Transformation of an Igniter Production Line

Wang, X., Li, C., Lin, Y., Chen, L., Yang, K., Deng, Q., & Jing, H. (2026) · Open Journal of Modelling and Simulation · doi:10.4236/ojmsi.2026.143007

Scan-to-Twin: Digital Twins for Sustainable and Resilient Brownfield Port Supply Chains

Mishra, S., Upadhyay, A., Maheshwari, M., Jain, I., Upadhyay, C. K., Mishra, S., & Kumar, B. C. (2026) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-3-032-30573-2_1

When digital twins meet too much transparency: agile manufacturing as a capability pathway to operational performance

Zhong, D., Cao, J., Wu, Y., He, G., & Chen, J. (2026) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-02-2026-0365

Synchronizing aeronautical Digital Twins in complex stakeholder environments via 3D scanning

Rauscher, F., Fuchs, M., Biedermann, J., & Nagel, B. (2026) · CEAS Aeronautical Journal · doi:10.1007/s13272-026-00992-w

Introduction

Liu, S., Zheng, P., & Bao, J. (2026) · Springer eBooks · doi:10.1007/978-981-95-8236-5_1

Physics-informed reality modeling: Behavior-aware reality capture representation of civil infrastructure

Nuraliyev, S., & Luleci, F. (2026) · Journal of Infrastructure Intelligence and Resilience · doi:10.1016/j.iintel.2026.100229

Digital Twin Simulation and Verification System Design and Implementation for Satellite Production Lines

Zhao, F. (2026) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2026-99-1804

DIGITAL TWINS FOR PROJECT MANAGERS: SIMULATING SUCCESS BEFORE THE FIRST LINE OF CODE

Stan, N. M., Titu, A. M., Badea, D., & BĂTUȘARU, C. M. (2026) · Annals of the Academy of Romanian Scientists Series on Economy Law and Sociology · doi:10.56082/annalsarscieco.2026.2.25

Towards digital twin-driven wind tunnel testing: A review of architectures and enabling technologies

Zhao, Z., Zuo, C., Ran, L., Xiong, J., Zhao, J., Zhu, Y., & Yi, X. (2026) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2026.101163

Digital transformation and productivity growth in European light manufacturing industries: evidence from panel data (2015–2022)

Cheng, D., & Rasool, Z. (2026) · Economics of Innovation and New Technology · doi:10.1080/10438599.2026.2704968

Mathematical Physics and the Study of Complex Quantum Systems

BatuBara, A. U., Ali, Z., & Vandika, A. Y. (2024) · Research of Scientia Naturalis · doi:10.70177/scientia.v1i6.1585

Digital Twins for Building Sustainability: A Life Cycle-Oriented Critical Review

Aiasrah, R., Wehbi, R., Ikalović, V., Aljer, A., & Sadek, M. (2026) · Sustainable Cities and Society Advances · doi:10.1016/j.scsadv.2026.100091

Exploring Application of DfMA + DfAM Design Principles for Additively Manufactured Parts with integration of Digital Twins - A Review

Harsha, N., Gaonkar, A. K., & Adinarayanappa, S. M. (2025) · IEEE Conference on Engineering Informatics (ICEI) · doi:10.1109/icei68356.2025.11603682

Digital Twin for Gear Wear Monitoring and Prediction

Feng, K., Ni, Q., & Zhou, H. (2026) · CRC Press eBooks · doi:10.1201/9781003686736

Modeling and simulation of a multi-level digital twin ecosystem for the circular economy

Aouani, S., Marangé, P., Robin, V., & Traoré, M. K. (2026) · SIMULATION · doi:10.1177/00375497261467054

Ten questions concerning stack effect issues in high-rise buildings

Jo, J.-H., Lim, H., Yoon, S., & Jing, J. (2026) · Building and Environment · doi:10.1016/j.buildenv.2026.115049

Safety-Constrained Multimodal Digital Twins for Zero-Defect Industrial Workcells

Sharma, A., & Mallala, N. (2026) · International Conference on Intelligent Technologies (CONIT) · doi:10.1109/conit69683.2026.11621740

Digital twins and cyber-physical systems for sustainable manufacturing: Enabler or illusion?

Dandi, M. (2026) · Journal of Engineering and High Technology · doi:10.55942/jeht.v2i1.2110

Analysing student learning pathways in educational systems using CRNN-based multichannel temporal modelling

Gan, X., & Hou, Y. (2026) · Connection Science · doi:10.1080/09540091.2026.2682059

Hybrid digital twin integrated Conv–BiLSTM for induction motor bearing fault detection, diagnosis and supervisory control

Iftikhar, K., & Khan, M. T. (2026) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-026-18867-z

To Charge or Not to Charge: Autonomous Battery Digital Twin for Electric Vehicles

Poola, L., Hasabnis, K. R., & Prabhakar, T., V (2026) · IEEE Vehicular Networking Conference (VNC) · doi:10.1109/vnc69225.2026.11629144

A Layered Decision Architecture for Circular Construction Supply Chains: Integrating Capabilities, Constraints, and Alignment

Lindblad, F. (2026) · Sustainability · doi:10.3390/su18179121

Enhancing Intelligent Manufacturing: A Human-AI Cooperation Structure Employing Big Language ModelsPreprint

Liu, Y. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7239480

The influence of digital twins on the rise of Industry 5.0: a scoping review covering future scope and research challenges

Lipsa, S., Dash, R. K., Cengiz, K., & Akleylek, S. (2026) · PeerJ Computer Science · doi:10.7717/peerj-cs.3929

Helical groove modeling based on a constraint-enhanced radial boundary extraction method

Meng, X., Zheng, J., Jiang, S., & Jiang, Q. (2026) · CIRP journal of manufacturing science and technology · doi:10.1016/j.cirpj.2026.08.001

The impact of digital twins on the transformation of employment and staff competencies

Smirnov, A., & Брызгалов, А. А. (2026) · Theoretical economics · doi:10.52957/2221-3260-2026-6-192-205

Digital twin application in school facilities management

salunke, S., Nanda, S., Kumari, S., & Tyagi, A. K. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-41632-3.00013-8

Recent developments in smart classrooms/smart schools in India

Kumari, S., Prabha, C., & Roy, N. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-41632-3.00020-5

Data-Driven Digital Twin Framework for Predictive Monitoring of Industrial Systems

Elmissaoui, T., & Hassine, H. (2026) · International Conference on Control, Automation and Diagnosis (ICCAD) · doi:10.1109/iccad69956.2026.11643069

Design of an Industrial Iot-Based Key Equipment Management and Energy Optimization System

Yu, S., Wang, Y., Ma, W., Gao, L., & Jie, Y. (2026) · International Conference on Information Communication, IoT Technology, and Smart Cities (IITS) · doi:10.1109/iits69561.2026.11648459

A multi-level analysis of Digital Twin implementation challenges using RAMI 4.0 and LASFA frameworks

Boareto, P. A., Loures, E. D. F. R., Deschamps, F., Santos, E. A. P., Szejka, A. L., Panetto, H., & Filho, M. F. (2026) · International Journal of Production Research · doi:10.1080/00207543.2026.2719846

Can digital twins redefine destination management? A socio-technical framework from a machine learning driven systematic review

Ali, W., & Çobanoğlu, C. (2026) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-11-2025-1654

A Data-Centric Deterministic State-Transition Architecture for CAD-to-CNC Integration in Structured 2.5-Axis Machining

Omirou, S. L. (2026) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-026-11582-7

Architectural Design Decisions for Entanglement Between Digital Twins and Microservices-Based Systems

Macías, A., Ntentos, E., Zdun, U., & Navarro, E. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-36590-3_19

Digital Twin-Driven Deep Reinforcement Learning for Dynamic Scheduling of Satellite Assembly Pulsed Production Lines

Ma, Z., Zhang, C., Liu, T., & Zhang, S. (2026) · International Conference on Electronics and Communication, Network and Computer Technology (ECNCT) · doi:10.1109/ecnct70535.2026.11661481

A Specification-Aware Interval Type-2 Fuzzy Framework for Explainable Operational Analytics in Continuous ManufacturingPreprint

HOPALI, E. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7366085

Strategic Management of Airport Readiness for Digital-Twin-Enabled Smart-Energy Systems: A Reliability-Aware Bayesian Decision Framework

Mızrak, F., & Elbir, U. (2026) · Energies · doi:10.3390/en19174048

AI-Enabled Digital Twins for Underground UAV Communication: A Survey, Taxonomy, and Research Roadmap

Javaid, S., Fahim, H., Cheng, B., Li, G., & He, B. (2026) · IEEE Sensors Reviews · doi:10.1109/sr.2026.3728774

A Digital Twin Model for the Management of Indoor Environmental Quality in Developing Economies

Akinshipe, O., & Aigbavboa, C. O. (2026) · Routledge eBooks · doi:10.1201/9781003743330

Digital Twin-Enabled Operational Capabilities for Environmental Sustainability: A Multiple Case StudyPreprint

Alzahrani, H. K., Braziotis, C., & Ciano, M. P. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7411434

A digital twin-based manufacturing quality inspection workshop for combine harvesters

Guo, Z., Ni, X., Li, F., ShuMao, W., Song, Z., & Chen, D. (2026) · Journal of Mechanical Science and Technology · doi:10.1007/s12206-026-0836-2

Digital twin technology in dentistry: Applications, challenges, and future perspectives in precision oral healthcare

Olawade, D. B., Fidelis, P. C., Olawuyi, O. F., Olasilola, R., Makanjuola, B. D., & Alabi, J. O. (2026) · Digital Dentistry Journal · doi:10.1016/j.ddj.2026.100119

DIGITAL TWIN-BASED PREDICTIVE MAINTENANCE OF SMART MANUFACTURING EQUIPMENT

THAKARE, K. M., Awari, G. K., AMJADKHA, P. R., & SALMAN, S. P. (2026) · American Journal of AI Cyber Computing Management · doi:10.64751/ajaccm.2026.v6.n2.881

Auditing Digital Twins: A Risk and Control Framework for Trustworthy Enterprise Decision SystemsPreprint

Abouzaid, O. (2026) · Research Square · doi:10.21203/rs.3.rs-10830895/v1

DEVELOPMENT AND IMPLEMENTATION OF A DIGITAL CONTROL SUBROUTINE FOR IMPROVING MACHINING ACCURACY IN CNC MILLING MACHINES

MURADOV, M. E. O. (2026) · Measuring and computing devices in technological processes · doi:10.31891/2219-9365-2026-87-47

Design of a Five-Dimension Digital-Twin Layout Model for a Modular Battery-Assembly Plant

Dr. Arvind A R, M. N. N., Mr. Chinnadurai, J., & Dr. R. Murugan, M. M. S. (2026) · International Journal of Advanced Research in Science Communication and Technology · doi:10.48175/ijarsct-38256

Digital Twin of an Automated Production Line

Georgieva, V., & Tsanev, H. (2026) · International Conference on Electronics, Engineering Physics and Earth Science (EEPES) · doi:10.3390/engproc2026154079

Adaptive Digital Twin-enabled Decision Support for Building-Water ManagementPreprint

Rajan, G., Li, S., & Sattar, S. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7471139

Methodological Research on Rapidly Constructing General-Purpose Core Models for Digital Twin Objects

Zeng, L., & Zhang, Y. (2026) · International Conference on Machine Learning, Natural Language Processing and Modeling · doi:10.1145/3832928.3832969

Tech meets green: drivers of customer purchase behaviour for digital twin-enabled sustainable products

Afaq, A., Ahmad, S. A., Gaur, L., & Kotecha, K. (2026) · International Journal of Systems Assurance Engineering and Management · doi:10.1007/s13198-026-03420-8

A Cost-Benefit Framework for Assessing Digital Twin Value in Manufacturing: Development and Industrial Evaluation

Kober, C. (2026) · IFIP advances in information and communication technology · doi:10.1007/978-3-032-38606-9_25

AI-Augmented Digital Twins in Large Industrial Companies: From Use Cases to Industrialisation

de Ocaña, A. S., & Bruch, J. (2026) · IFIP advances in information and communication technology · doi:10.1007/978-3-032-38606-9_28

AI-enabled environmental digital twins: a new paradigm for predictive environmental research

Qin, Y., Wu, Y., Liu, Y., Huang, Y., Yi, H., Li, X., Zhang, X., Song, L., Lin, Y., Lu, D., et al. (2026) · Artificial Intelligence & Environment · doi:10.66178/aie-0026-0021

Digital Twin Entanglement: Enhanced measurement & reference benchmarking

Morandi, R., Picone, M., Bicocchi, N., Fogli, M., & Giannelli, C. (2026) · Future Generation Computer Systems · doi:10.1016/j.future.2026.108808

Digital Twin Empowering Whole-Lifecycle Governance of Urban Infrastructure: A Review of Technological Embedding, Organizational Change, and Institutional Reconstruction

Chen, X., Li, B., Zhao, Y., Zheng, C., & Zhang, Y. (2026) · Buildings · doi:10.3390/buildings16183742

AI-Driven Digital Twins for Offshore Oil & Gas Platforms: A Systematic Literature Review and Conceptual Framework

Gorgonho, M. (2026) · Springer series in geomechanics and geoengineering · doi:10.1007/978-981-95-9869-4_80

Automated openBIM-enabled semantic interoperability framework for arch dam digital twins in safety monitoring

Zhang, S., Zhang, S., Wang, C., Tan, Y., & Wang, X. (2026) · Automation in Construction · doi:10.1016/j.autcon.2026.107279

Computer vision as a data source for digital twins in manufacturing: A Sim2Real pipeline

Farhat, N., David, P., Rif, L., & Garcia, N. C. (2026) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2026.101207

Tax digital twin: A reference architecture for continuous enterprise tax compliance

Kumar, M., & Vaitinadin, M. (2025) · Journal of Economics Finance and Accounting Studies · doi:10.32996/jefas.2025.7.7.3

Model of a Digital Twin for a High-Efficiency Hybrid Cogeneration System

Melnyk, A., Tymchyshyn, V., Tkacz, E., Vitrovyy, A., Мазур, І.-С., & Tymchyshyn, B. (2026) · International Conference on Advanced Computer Information Technologies (ACIT) · doi:10.1109/acit69831.2026.11699953

THE CONVERGENCE OF COMPUTER-AIDED DRAUGHTING AND DISCRETE EVENT SIMULATION IN MANUFACTURING: A SYSTEMATIC STATE-OF-THE-ART REVIEW

Chikwata, P. C., Chigocho, B., Chitewe, M. S., Chikwanha, M. B., & Chari, T. (2026) · World Journal of Advanced Engineering Technology and Sciences · doi:10.30574/wjaets.2026.20.3.0455

Digital Twins for Advancing Emergency Management in the Built Environment: A Systematic Review of Core Capabilities, Trends, and Future Directions

Liu, Q., & Liu, R. (2026) · Journal of Construction Engineering and Management · doi:10.1061/jcemd4.coeng-18643

Human-centric digital twins in industry 5.0: technologies, applications, and future directions

Khan, S., Tumrani, S., Nam, N. V., Ahmed, M., Khan, A., & Khan, M. (2026) · Frontiers in Robotics and AI · doi:10.3389/frobt.2026.1983733

Toward quality-assured intelligent welding processes for aerospace structures: From process monitoring to digital closed-loop manufacturing

Peng, X., Peng, S., Wang, Z., & Ma, G. (2026) · Journal of Manufacturing Processes · doi:10.1016/j.jmapro.2026.09.081

Contract-Admissible AI Integration for Renewable-Aware Manufacturing Systems: A Formal and Evidence-Controlled FrameworkPreprint

Zaidi, A. H. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7548524

Digital Twin with Embedded Energy Consumption Prediction for Collaborative Robotic Manipulators

Yan, J., Hu, B., Yu, B., & Wang, P. (2026) · International Conference on Automation and Computing (ICAC) · doi:10.1109/icac70325.2026.11712314

Multiphysics-coupled digital twin modeling and virtual-real consistency updating method for aerospace electromechanical servo mechanisms

Zhang, Z., Li, C., Changhua, H., Hu, J., Mingzhe, L., Wan, X., Wang, P., & Pang, Y. (2026) · Aerospace Science and Technology · doi:10.1016/j.ast.2026.113954

Vector Quantization of Complex Sensor Data in Limited Network Bandwidth and Edge Hardware Constrained Digital Twins

Varghese, A., Starly, B., & Iquebal, A. S. (2026) · Manufacturing Letters · doi:10.1016/j.mfglet.2026.08.060

Digital Twin-Driven Framework for Automated Generation of Digital Product Passports

Jiang, X., Jain, V., Singh, S. A., Johnson, M., & Farahani, S. (2026) · Manufacturing Letters · doi:10.1016/j.mfglet.2026.08.077

A System-Level Perspective on Drift in Digital Twins

Mesropyan, T., Groth, P., & Degeler, V. (2026) · ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS) · doi:10.1145/3837062.3841569

Digital twin modeling

Tao, F., Xiao, B., Qi, Q., Cheng, J., & Ji, P. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2022.06.015 · Cited by 1,255

Digital twin: a state-of-the-art review of its enabling technologies, applications and challenges

Hu, W., Zhang, T., Deng, X., Liu, Z., & Tan, J. (2021) · Journal of Intelligent Manufacturing and Special Equipment · doi:10.1108/jimse-12-2020-010 · Cited by 228

Five-Dimension Digital Twin Modeling and Its Key Technologies

Tao, F., Zhang, M., & Nee, A. (2019) · Digital Twin Driven Smart Manufacturing · doi:10.1016/b978-0-12-817630-6.00003-5 · Cited by 45

Digital Twin: An Investigation of the Characteristics, Visions, Challenges, and Opportunities

El-Douh, A. A.-R., & Abdel-aziem, A. H. (2023) · International journal of advances in applied computational intelligence. · doi:10.54216/ijaaci.040105 · Cited by 1

Digital Twin

Kaur, J., Bhambri, P., & Rani, S. (2024) · CRC Press eBooks · doi:10.1201/9781003395416-6 · Cited by 5