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 · see citing works

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 · see citing works

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 · see citing works

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<BR>20th AIAA/ASME/AHS Adaptive Structures Conference<BR>14th AIAA · doi:10.2514/6.2012-1818 · Cited by 2,404 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing

Tao, F., & Zhang, M. (2017) · IEEE Access · doi:10.1109/access.2017.2756069 · Cited by 1,397 · see citing works

Shaping the digital twin for design and production engineering

Schleich, B., Anwer, N., Mathieu, L., & Wartzack, S. (2017) · CIRP Annals · doi:10.1016/j.cirp.2017.04.040 · Cited by 1,305 · see citing works

Reengineering aircraft structural life prediction using a digital twin

Tuegel, E. J., Ingraffea, A. R., Eason, T. G., & Spottswood, S. M. (2011) · International Journal of Aerospace Engineering · doi:10.1155/2011/154798 · Cited by 1,119 · see citing works

Digital twin-driven product design framework

Tao, F., Sui, F.-Y., Liu, A., Qi, Q., Zhang, M., Song, B.-Y., Guo, Z.-R., Lu, S. C. Y., & Nee, A. (2019) · International Journal of Production Research · doi:10.1080/00207543.2018.1443229 · Cited by 1,085 · see citing works

Tackling the digitalization challenge: how to benefit from digitalization in practice

Parviainen, P., Tihinen, M., Kääriäinen, J., & Teppola, S. (2022) · International journal of information systems and project management · doi:10.12821/ijispm050104 · Cited by 1,076 · see citing works

Digital twin driven prognostics and health management for complex equipment

Tao, F., Zhang, M., Liu, Y., & Nee, A. Y. C. (2018) · CIRP Annals · doi:10.1016/j.cirp.2018.04.055 · Cited by 1,000 · see citing works

Digitalization: Opportunity and Challenge for the Business and Information Systems Engineering Community

Legner, C., Eymann, T., Heß, T., Matt, C., Böhmann, T., Drews, P., Mädche, A., Urbach, N., & Ahlemann, F. (2017) · Business & Information Systems Engineering · doi:10.1007/s12599-017-0484-2 · Cited by 985 · see citing works

Make more digital twins

Tao, F., & Qi, Q. (2019) · Nature · doi:10.1038/d41586-019-02849-1 · Cited by 799 · see citing works

Toward a Digital Twin for real-time geometry assurance in individualized production

Söderberg, R., Wärmefjord, K., Carlson, J. S., & Lindkvist, L. (2017) · CIRP Annals · doi:10.1016/j.cirp.2017.04.038 · Cited by 543 · see citing works

An application framework of digital twin and its case study

Zheng, Y., Yang, S., & Cheng, H. (2018) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0911-3 · Cited by 534 · see citing works

Digital Twin Service towards Smart Manufacturing

Qi, Q., Tao, F., Zuo, Y. N., & Zhao, D. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.03.103 · Cited by 504 · see citing works

Digital Twin Data Modeling with AutomationML and a Communication Methodology for Data Exchange

Schroeder, G. N., Steinmetz, C., Pereira, C. E., & Espíndola, D. B. (2016) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2016.11.115 · Cited by 495 · see citing works

A Digital Twin-Based Approach for Designing and Multi-Objective Optimization of Hollow Glass Production Line

Zhang, H., Liu, Q., Chen, X., Zhang, D., & Leng, J. (2017) · IEEE Access · doi:10.1109/access.2017.2766453 · Cited by 471 · see citing works

New IT Driven Service-Oriented Smart Manufacturing: Framework and Characteristics

Tao, F., & Qi, Q. (2017) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2017.2723764 · Cited by 434 · see citing works

The role of data fusion in predictive maintenance using digital twin

Liu, Z., Meyendorf, N., & Mrad, N. (2018) · AIP conference proceedings · doi:10.1063/1.5031520 · Cited by 364 · see citing works

The digital twin of an industrial production line within the industry 4.0 concept

Vachalek, J., Bartalsky, L., Rovny, O., Sismisova, D., Morhac, M., & Loksik, M. (2017) · 2017 21st International Conference on Process Control (PC) · doi:10.1109/pc.2017.7976223 · Cited by 339 · see citing works

A fog computing-based framework for process monitoring and prognosis in cyber-manufacturing

Wu, D., Liu, S., Zhang, L., Terpenny, J. P., Gao, R. X., Kurfess, T. R., & Guzzo, J. A. (2017) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2017.02.011 · Cited by 289 · see citing works

Sensor Data and Information Fusion to Construct Digital-twins Virtual Machine Tools for Cyber-physical Manufacturing

Cai, Y., Starly, B., Cohen, P., & Lee, Y.-S. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.07.094 · Cited by 289 · see citing works

Digital Twin Driven Smart Manufacturing

Tao, F., Zhang, M., & Nee, A. Y. C. (2019) · Elsevier eBooks · doi:10.1016/c2018-0-02206-9 · Cited by 284 · see citing works

Part data integration in the Shop Floor Digital Twin: Mobile and cloud technologies to enable a manufacturing execution system

Urbina Coronado, P. D., Lynn, R., Louhichi, W., Parto, M., Wescoat, E., & Kurfess, T. (2018) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2018.02.002 · Cited by 267 · see citing works

Modular based flexible digital twin for factory design

Guo, J., Zhao, N., Sun, L., & Zhang, S. (2018) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0953-6 · Cited by 205 · see citing works

Manufacturing Service Management in Cloud Manufacturing: Overview and Future Research Directions

Tao, F., Li, Z., Liu, Y., Cheng, Y., Wang, L., & Xu, X. W. (2015) · Journal of Manufacturing Science and Engineering · doi:10.1115/1.4030510 · Cited by 193 · see citing works

Digital Twin of a Cutting Tool

Botkina, D., Hedlind, M., Olsson, B., Henser, J., & Lundholm, T. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.03.178 · Cited by 183 · see citing works

A Simulation-Based Digital Twin for Model-Driven Health Monitoring and Predictive Maintenance of an Automotive Braking System

Magargle, R. S., Johnson, L., Mandloi, P., Davoudabadi, P., Kesarkar, O., Krishnaswamy, S., Batteh, J. J., & Pitchaikani, A. (2017) · Linköping electronic conference proceedings · doi:10.3384/ecp1713235 · Cited by 162 · see citing works

Cyber-physical integration for moving digital factories forward towards smart manufacturing: a survey

Cheng, Y., Zhang, Y., Ji, P., Xu, W., Zhou, Z., & Tao, F. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-018-2001-2 · Cited by 161 · see citing works

Combined strength of holons, agents and function blocks in cyber-physical systems

Wang, L., & Haghighi, A. (2016) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2016.05.002 · Cited by 121 · see citing works

Structural Health Management of Damaged Aircraft Structures Using Digital Twin Concept

Seshadri, B. R., & Krishnamurthy, T. (2017) · AIAA/AHS Adaptive Structures Conference · doi:10.2514/6.2017-1675 · Cited by 117 · see citing works

A simulation-based approach for plant layout design and production planning

Zhang, Z., Wang, X., Wang, X., Cui, F., & Cheng, H. (2018) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0687-5 · Cited by 106 · see citing works

Fleet Monitoring and Diagnostics Framework Based on Digital Twin of Aero-Engines

Zaccaria, V., Stenfelt, M., Aslanidou, I., & Kyprianidis, K. (2018) · ASME Turbo Expo: Turbomachinery Technical Conference and Exposition (GT) · doi:10.1115/gt2018-76414 · Cited by 101 · see citing works

A flexible data schema and system architecture for the virtualization of manufacturing machines (VMM)

Angrish, A., Starly, B., Lee, Y., & Cohen, P. H. (2017) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2017.10.003 · Cited by 94 · see citing works

Feature-based control and information framework for adaptive and distributed manufacturing in cyber physical systems

Adamson, G., Wang, L., & Moore, P. (2016) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2016.12.003 · Cited by 88 · see citing works

An accurate and efficient navigation system for omnidirectional robots in industrial environments

Sprunk, C., Lau, B., Pfaff, P., & Burgard, W. (2016) · Autonomous Robots · doi:10.1007/s10514-016-9557-1 · Cited by 79 · see citing works

Cloud manufacturing paradigm with ubiquitous robotic system for product customization

Zhang, Z., Wang, X., Zhu, X., Cao, Q., & Tao, F. (2019) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2019.05.015 · Cited by 70 · see citing works

The Development and use of a Digital Twin Model for Tire Touchdown Health Monitoring

Zakrajsek, A. J., & Mall, S. (2017) · AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (SDM) · doi:10.2514/6.2017-0863 · Cited by 53 · see citing works

A function block based cyber-physical production system for physical human–robot interaction

Yao, B., Zhou, Z., Wang, L., Xu, W., Yan, J., & Liu, Q. (2018) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2018.04.010 · Cited by 52 · see citing works

Dynamic resource allocation optimization for digital twin-driven smart shopfloor

Zhang, H., Zhang, G., & Yan, Q. (2018) · IEEE International Conference on Networking, Sensing and Control (ICNSC) · doi:10.1109/icnsc.2018.8361283 · Cited by 39 · see citing works

Independent Verification and Validation of an Industrial Simulation Model

Robinson, S., & Brooks, R. J. (2009) · SIMULATION · doi:10.1177/0037549709341582 · Cited by 28 · see citing works

A review of designing machine tool for leanness

Gupta, A. K., & Kundra, T. K. (2012) · Sadhana · doi:10.1007/s12046-012-0062-8 · Cited by 24 · see citing works

Optimized throughput improvement of assembly flow line with digital twin online analytics

Sun, H., Li, C., Fang, X., & Gu, H. (2017) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio.2017.8324685 · Cited by 17 · see citing works

A linked data approach for the connection of manufacturing processes with production simulation models

Senington, R., Baumeister, F., Ng, A. H. C., & Oscarsson, J. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.03.243 · Cited by 12 · see citing works

Design of Data Acquisition System Based on Zigbee for Wireless Sensor Networks

Lei, S. (2018) · MATEC Web of Conferences · doi:10.1051/matecconf/201824603036 · Cited by 9 · see citing works

Review of digital twin about concepts, technologies, and industrial applications

Liu, M., Fang, S., Dong, H., & Xu, C. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.017 · Cited by 1,965 · see citing works

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 · see citing works

Digital Twins: A Survey on Enabling Technologies, Challenges, Trends and Future Prospects

Mihai, S., Yaqoob, M., Hưng, Đ. V., Davis, W., Towakel, P., Raza, M., Karamanoglu, M., Barn, B. S., Shetve, D., Prasad, R. V., et al. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3208773 · Cited by 1,115 · see citing works

Digital Twin Technology Challenges and Applications: A Comprehensive Review

Botín-Sanabria, D. M., Mihaita, A.-S., Peimbert-García, R. E., Ramírez-Moreno, M. A., Ramírez-Mendoza, R. A., & Lozoya-Santos, J. D. J. (2022) · Remote Sensing · doi:10.3390/rs14061335 · Cited by 878 · see citing works

Introducing digital twins to agriculture

Pylianidis, C., Osinga, S., & Athanasiadis, I. N. (2021) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2020.105942 · Cited by 720 · see citing works

Digital twin: benefits, use cases, challenges, and opportunities

Attaran, M., & Celik, B. G. (2023) · Decision Analytics Journal · doi:10.1016/j.dajour.2023.100165 · Cited by 704 · see citing works

Digital Twins: State of the art theory and practice, challenges, and open research questions

Sharma, A., Kosasih, E., Zhang, J., Brintrup, A., & Calinescu, A. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2022.100383 · Cited by 587 · see citing works

A review of vibration-based gear wear monitoring and prediction techniques

Feng, K., Ji, J., Ni, Q., & Beer, M. (2022) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2022.109605 · Cited by 561 · see citing works

A systematic review of a digital twin city: A new pattern of urban governance toward smart cities

Deng, T., Zhang, K., & Shen, Z. M. (2021) · Journal of Management Science and Engineering · doi:10.1016/j.jmse.2021.03.003 · Cited by 560 · see citing works

Digital twin-driven intelligent assessment of gear surface degradation

Feng, K., Ji, J., Zhang, Y., Ni, Q., Liu, Z., & Beer, M. (2022) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2022.109896 · Cited by 552 · see citing works

A digital twin smart city for citizen feedback

White, G., Zink, A., Codecá, L., & Clarke, S. (2021) · Cities · doi:10.1016/j.cities.2020.103064 · Cited by 548 · see citing works

A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies

Thelen, A., Zhang, X., Fink, O., Lu, Y., Ghosh, S., Youn, B. D., Todd, M. D., Mahadevan, S., Hu, C. K., & Hu, Z. Y. (2022) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-022-03425-4 · Cited by 471 · see citing works

Digital Twin applications toward Industry 4.0: A Review

Javaid, M., Haleem, A., & Suman, R. (2023) · Cognitive Robotics · doi:10.1016/j.cogr.2023.04.003 · Cited by 466 · see citing works

Human Digital Twin in the context of Industry 5.0

Wang, B., Zhou, H., Li, X., Yang, G., Zheng, P., Song, C., Yuan, Y., Wuest, T., Yang, H., & Wang, L. (2023) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2023.102626 · Cited by 452 · see citing works

The emergence of cognitive digital twin: vision, challenges and opportunities

Zheng, X., Lu, J., & Kiritsis, D. (2021) · International Journal of Production Research · doi:10.1080/00207543.2021.2014591 · Cited by 446 · see citing works

Artificial intelligence and internet of things in small and medium-sized enterprises: A survey

Hansen, E. B., & Bøgh, S. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.08.009 · Cited by 442 · see citing works

Intelligent welding system technologies: State-of-the-art review and perspectives

Wang, B., Hu, S. J., Sun, L., & Freiheit, T. I. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.020 · Cited by 439 · see citing works

Digital twin for smart manufacturing, A review

Soori, M., Behrooz Arezoo, B., & Dastres, R. (2023) · Sustainable Manufacturing and Service Economics · doi:10.1016/j.smse.2023.100017 · Cited by 411 · see citing works

Overview of predictive maintenance based on digital twin technology

Dong, Z., Xia, Z., Zhu, Y., & Duan, J. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e14534 · Cited by 389 · see citing works

Digital Twin: A Comprehensive Survey of Security Threats

Alcaraz, C., & López, J. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3171465 · Cited by 364 · see citing works

Digital Twins in Built Environments: An Investigation of the Characteristics, Applications, and Challenges

Shahzad, M., Shafiq, M. T., Douglas, D., & Kassem, M. (2022) · Buildings · doi:10.3390/buildings12020120 · Cited by 356 · see citing works

Technologies for digital twin applications in construction

Tuhaise, V. V., Tah, J. H. M., & Abanda, F. H. (2023) · Automation in Construction · doi:10.1016/j.autcon.2023.104931 · Cited by 350 · see citing works

Industry 4.0 smart reconfigurable manufacturing machines

Morgan, J., Halton, M., Qiao, Y., & Breslin, J. G. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.03.001 · Cited by 336 · see citing works

Implementation of digital twins in the process industry: A systematic literature review of enablers and barriers

Perno, M., Hvam, L., & Haug, A. (2021) · Computers in Industry · doi:10.1016/j.compind.2021.103558 · Cited by 328 · see citing works

Digital Twins From Smart Manufacturing to Smart Cities: A Survey

Mylonas, G., Kalogeras, A. P., Kalogeras, G., Anagnostopoulos, C., Alexakos, C., & Muñoz, L. (2021) · IEEE Access · doi:10.1109/access.2021.3120843 · Cited by 327 · see citing works

Digital Twin in Aerospace Industry: A Gentle Introduction

Li, L., Aslam, S., Wileman, A., & Perinpanayagam, S. (2021) · IEEE Access · doi:10.1109/access.2021.3136458 · Cited by 316 · see citing works

Digital twin-based designing of the configuration, motion, control, and optimization model of a flow-type smart manufacturing system

Liu, Q., Leng, J., Yan, D., Zhang, D., Wei, L., Yu, A., Zhao, R., Zhang, H., & Chen, X. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.04.012 · Cited by 315 · see citing works

Digital twin modeling method based on biomimicry for machining aerospace components

Liu, S., Bao, J., Lu, Y., Li, J., Lu, S., & Sun, X. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.04.014 · Cited by 310 · see citing works

A Review of Urban Digital Twins Integration, Challenges, and Future Directions in Smart City Development

Mazzetto, S. (2024) · Sustainability · doi:10.3390/su16198337 · Cited by 310 · see citing works

A Survey on Digital Twin for Industrial Internet of Things: Applications, Technologies and Tools

Xu, H., Wu, J., Pan, Q., Guan, X., & Guizani, M. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3297395 · Cited by 304 · see citing works

Digital Twins in the Construction Industry: A Comprehensive Review of Current Implementations, Enabling Technologies, and Future Directions

Omrany, H., Al-Obaidi, K. M., Husain, A., & Ghaffarianhoseini, A. (2023) · Sustainability · doi:10.3390/su151410908 · Cited by 301 · see citing works

Digital twins for collaborative robots: A case study in human-robot interaction

Malik, A. A., & Brem, A. (2020) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2020.102092 · Cited by 299 · see citing works

Digital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review

Chen, Y., Yang, O., Sampat, C., Bhalode, P., Ramachnadran, R., & Ierapetritou, M. (2020) · Processes · doi:10.3390/pr8091088 · Cited by 295 · see citing works

A comprehensive review of model compression techniques in machine learning

Dantas, P. V., da Silva, W. S., Cordeiro, L. C., & Carvalho, C. B. (2024) · Applied Intelligence · doi:10.1007/s10489-024-05747-w · Cited by 287 · see citing works

Blockchain-based data management for digital twin of product

Huang, S., Wang, G., Yan, Y., & Fang, X. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.01.009 · Cited by 277 · see citing works

Digital Twins for the built environment: learning from conceptual and process models in manufacturing

Delgado, J. M. D., & Oyedele, L. O. (2021) · Advanced Engineering Informatics · doi:10.1016/j.aei.2021.101332 · Cited by 272 · see citing works

Human Digital Twin for Fitness Management

Barricelli, B. R., Casiraghi, E., Gliozzo, J., Petrini, A., & Valtolina, S. (2020) · IEEE Access · doi:10.1109/access.2020.2971576 · Cited by 259 · see citing works

Towards Civil Engineering 4.0: Concept, workflow and application of Digital Twins for existing infrastructure

Pregnolato, M., Gunner, S., Voyagaki, E., De Risi, R., Carhart, N., Gavriel, G., Tully, P., Tryfonas, T., Macdonald, J., & Taylor, C. (2022) · Automation in Construction · doi:10.1016/j.autcon.2022.104421 · Cited by 253 · see citing works

Digital twin-based smart assembly process design and application framework for complex products and its case study

Yi, Y., Yan, Y., Liu, X., Ni, Z., Feng, J., & Liu, J. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.04.013 · Cited by 253 · see citing works

Digital Twin-enabled Collaborative Data Management for Metal Additive Manufacturing Systems

Liu, C., Le Roux, L., Körner, C., Tabaste, O., Lacan, F., & Bigot, S. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.05.010 · Cited by 252 · see citing works

Digital twin: Data exploration, architecture, implementation and future

Dihan, M. S., Akash, A. I., Tasneem, Z., Das, P., Das, S. K., Islam, M. R., Islam, M. M., Badal, F. R., Ali, M. F., Ahamed, M. H., et al. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e26503 · Cited by 250 · see citing works

Digital twins: An analysis framework and open issues

Boyes, H. A., & Watson, T. (2022) · Computers in Industry · doi:10.1016/j.compind.2022.103763 · Cited by 241 · see citing works

Systematic review on tool breakage monitoring techniques in machining operations

Li, X., Liu, X., Yue, C., Liang, S. Y., & Wang, L. (2022) · International Journal of Machine Tools and Manufacture · doi:10.1016/j.ijmachtools.2022.103882 · Cited by 239 · see citing works

Digital twin of electric vehicle battery systems: Comprehensive review of the use cases, requirements, and platforms

Naseri, F., Gil, S., Barbu, C., Çetkin, E., Yarimca, G., Jensen, A. C. S., Larsen, P. G., & Gomes, C. Â. G. (2023) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2023.113280 · Cited by 236 · see citing works

Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems

Sleiti, A. K., Kapat, J. S., & Veselý, L. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.02.305 · Cited by 233 · see citing works

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 · see citing works

Digital Twins in Livestock Farming

Neethirajan, S. R., & Kemp, B. (2021) · Animals · doi:10.3390/ani11041008 · Cited by 226 · see citing works

Digital twin and cloud-side-end collaboration for intelligent battery management system

Wang, Y., Xu, R., Zhou, C., Kang, X., & Chen, Z. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.11.006 · Cited by 222 · see citing works

A review of Type V composite pressure vessels and automated fibre placement based manufacturing

Air, A. D., Shamsuddoha, M., & Prusty, B. G. (2023) · Composites Part B Engineering · doi:10.1016/j.compositesb.2023.110573 · Cited by 220 · see citing works

Big data, machine learning, and digital twin assisted additive manufacturing: A review

Jin, L., Zhai, X., Wang, K., Zhang, K., Wu, D., Nazir, A., Jiang, J., & Liao, W. (2024) · Materials & Design · doi:10.1016/j.matdes.2024.113086 · Cited by 220 · see citing works

Challenges of urban digital twins: A systematic review and a Delphi expert survey

Lei, B., Janssen, P. H. T., Stoter, J., & Biljecki, F. (2023) · Automation in Construction · doi:10.1016/j.autcon.2022.104716 · Cited by 217 · see citing works

MES-integrated digital twin frameworks

Negri, E., Berardi, S., Fumagalli, L., & Macchi, M. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.05.007 · Cited by 213 · see citing works

A survey of multimodal information fusion for smart healthcare: Mapping the journey from data to wisdom

Shaik, T., Tao, X., Li, L., Xie, H., & Velasquez, J. D. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.102040 · Cited by 213 · see citing works

Exploring the revolution in healthcare systems through the applications of digital twin technology

Haleem, A., Javaid, M., Singh, R. P., & Suman, R. (2023) · Biomedical Technology · doi:10.1016/j.bmt.2023.02.001 · Cited by 210 · see citing works

Digital Twins for Wastewater Treatment: A Technical Review

Wang, A., Li, H., He, Z., Tao, Y., Wang, H., Yang, M., Savic, D. A., Daigger, G. T., & Ren, N.-Q. (2024) · Engineering · doi:10.1016/j.eng.2024.04.012 · Cited by 203 · see citing works

Impactful Digital Twin in the Healthcare Revolution

Hassani, H., Huang, X., & MacFeely, S. (2022) · Big Data and Cognitive Computing · doi:10.3390/bdcc6030083 · Cited by 200 · see citing works

Developing a conceptual framework for the application of digital twin technologies to revamp building operation and maintenance processes

Zhao, J., Feng, H., Chen, Q., & Garcia de Soto, B. (2022) · Journal of Building Engineering · doi:10.1016/j.jobe.2022.104028 · Cited by 192 · see citing works

Uses of the digital twins concept for energy services, intelligent recommendation systems, and demand side management: A review

Onile, A. E., Machlev, R., Petlenkov, E., Levron, Y., & Belikov, J. (2021) · Energy Reports · doi:10.1016/j.egyr.2021.01.090 · Cited by 191 · see citing works

Digital Twins in greenhouse horticulture: A review

Ariesen-Verschuur, N., Verdouw, C. N., & Teki̇nerdoğan, B. (2022) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2022.107183 · Cited by 187 · see citing works

Infrastructure digital twin technology: A new paradigm for future construction industry

Moshood, T. D., Rotimi, J. O. B., Shahzad, W. M., & Bamgbade, J. A. (2024) · Technology in Society · doi:10.1016/j.techsoc.2024.102519 · Cited by 187 · see citing works

Developing a Digital Twin and Digital Thread Framework for an ‘Industry 4.0’ Shipyard

Pang, T. Y., Restrepo, J. D. P., Cheng, C., Yasin, A., Lim, H., & Miletic, M. (2021) · Applied Sciences · doi:10.3390/app11031097 · Cited by 185 · see citing works

A digital twin-based big data virtual and real fusion learning reference framework supported by industrial internet towards smart manufacturing

Wang, P., & Luo, M. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.11.012 · Cited by 184 · see citing works

Digital Twin-driven Online Anomaly Detection for an Automation System Based on Edge Intelligence

Huang, H., Yang, L., Wang, Y., Xu, X., & Lu, Y. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.02.010 · Cited by 183 · see citing works

Digital Twin and CyberGIS for Improving Connectivity and Measuring the Impact of Infrastructure Construction Planning in Smart Cities

Shirowzhan, S., Tan, W., & Sepasgozar, S. M. E. (2020) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi9040240 · Cited by 183 · see citing works

A deep learning-enhanced Digital Twin framework for improving safety and reliability in human–robot collaborative manufacturing

Wang, S., Zhang, J., Wang, P., Law, J., Călinescu, R., & Mihaylova, L. S. (2023) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2023.102608 · Cited by 181 · see citing works

Digital twins for the automation of the heritage construction sector

Lucchi, E. (2023) · Automation in Construction · doi:10.1016/j.autcon.2023.105073 · Cited by 177 · see citing works

A knowledge-based Digital Shadow for machining industry in a Digital Twin perspective

Ladj, A., Wang, Z., Meski, O., Belkadi, F., Ritou, M., & Cunha, C. M. D. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.07.018 · Cited by 173 · see citing works

Human-Centric Digital Twins in Industry: A Comprehensive Review of Enabling Technologies and Implementation Strategies

Asad, U., Khan, M., Khalid, A., & Lughmani, W. A. (2023) · Sensors · doi:10.3390/s23083938 · Cited by 172 · see citing works

Modeling and implementation of a digital twin of material flows based on physics simulation

Glatt, M. F., Sinnwell, C., Yi, L., Donohoe, S. P., Ravani, B., & Aurich, J. C. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.04.015 · Cited by 166 · see citing works

Digital Twins in Product Lifecycle for Sustainability in Manufacturing and Maintenance

Rojek, I., Mikołajewski, D., & Dostatni, E. (2020) · Applied Sciences · doi:10.3390/app11010031 · Cited by 166 · see citing works

Digital twin-based assembly data management and process traceability for complex products

Zhuang, C., Gong, J., & Liu, J. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.05.011 · Cited by 163 · see citing works

Digital Twins in Healthcare: An Architectural Proposal and Its Application in a Social Distancing Case Study

Benedictis, A. D., Mazzocca, N., Somma, A., & Strigaro, C. (2022) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3205506 · Cited by 158 · see citing works

The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review

Mchirgui, N., Quadar, N., Kraiem, H., & Lakhssassi, A. (2024) · Applied Sciences · doi:10.3390/app142310933 · Cited by 158 · see citing works

The role of digital twins in lean supply chain management: review and research directions

Guo, D., & Mantravadi, S. (2024) · International Journal of Production Research · doi:10.1080/00207543.2024.2372655 · Cited by 157 · see citing works

Conceptual digital twin modeling based on an integrated five-dimensional framework and TRIZ function model

Wu, C., Zhou, Y., Pessôa, M. V. P., Peng, Q., & Tan, R. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.07.006 · Cited by 156 · see citing works

A futuristic perspective on human-centric assembly

Wang, L. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.11.001 · Cited by 154 · see citing works

Blockchain-Empowered Digital Twins Collaboration: Smart Transportation Use Case

Sahal, R., Alsamhi, S. H., Brown, K. N., O’Shea, D., McCarthy, C. T., & Guizani, M. (2021) · Machines · doi:10.3390/machines9090193 · Cited by 153 · see citing works

Collaborative manufacturing technologies of structure shape and surface integrity for complex thin-walled components of aero-engine: Status, challenge and tendency

Zhao, B., Ding, W., Shan, Z., Jun, W. A. N. G., Yao, C., Zhao, Z., Liu, J., Xiao, S., Ding, Y., Tang, X., et al. (2023) · Chinese Journal of Aeronautics · doi:10.1016/j.cja.2023.02.008 · Cited by 152 · see citing works

New Paradigm of Data-Driven Smart Customisation through Digital Twin

Wang, X., Wang, Y., Tao, F., & Liu, A. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.07.023 · Cited by 150 · see citing works

Factors Influencing Adoption of Digital Twin Advanced Technologies for Smart City Development: Evidence from Malaysia

Waqar, A., Othman, I., Almujibah, H. R., Khan, M. B., Alotaibi, S., & Elhassan, A. A. M. (2023) · Buildings · doi:10.3390/buildings13030775 · Cited by 149 · see citing works

Digital Twins in the Construction Industry: A Perspective of Practitioners and Building Authority

Ammar, A., Nassereddine, H., AbdulBaky, N., AbouKansour, A., Tannoury, J., Urban, H., & Schranz, C. (2022) · Frontiers in Built Environment · doi:10.3389/fbuil.2022.834671 · Cited by 148 · see citing works

A review of digital twin applications in construction

Madubuike, O. C., Anumba, C. J., & Khallaf, R. (2022) · Journal of Information Technology in Construction · doi:10.36680/j.itcon.2022.008 · Cited by 147 · see citing works

A survey of Digital Twin techniques in smart manufacturing and management of energy applications

Wang, Y., Kang, X., & Chen, Z. (2022) · Green Energy and Intelligent Transportation · doi:10.1016/j.geits.2022.100014 · Cited by 147 · see citing works

A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence

Mo, F., Rehman, H. U., Monetti, F. M., Chaplin, J. C., SANDERSON, D. R., Popov, A. A., Maffei, A., & Ratchev, S. M. (2023) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2022.102524 · Cited by 146 · see citing works

A digital twin-based decision analysis framework for operation and maintenance of tunnels

Yu, G., Wang, Y. P., Mao, Z., Hu, M., Sugumaran, V., & Wang, Y. K. (2021) · Tunnelling and Underground Space Technology · doi:10.1016/j.tust.2021.104125 · Cited by 145 · see citing works

makeTwin: A reference architecture for digital twin software platform

Tao, F., Sun, X., Cheng, J., Zhu, Y., Liu, W., Wang, Y., Xu, H., Hu, T., Liu, X., Liu, T., et al. (2023) · Chinese Journal of Aeronautics · doi:10.1016/j.cja.2023.05.002 · Cited by 142 · see citing works

Prediction maintenance integrated decision-making approach supported by digital twin-driven cooperative awareness and interconnection framework

Mi, S., Feng, Y., Zheng, H., Wang, Y., Gao, Y., & Tan, J. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.08.001 · Cited by 141 · see citing works

Digital Twin in Electrical Machine Control and Predictive Maintenance: State-of-the-Art and Future Prospects

Falekas, G., & Karlis, A. D. (2021) · Energies · doi:10.3390/en14185933 · Cited by 141 · see citing works

Developing a Skilled Workforce for Future Industry Demand: The Potential of Digital Twin-Based Teaching and Learning Practices in Engineering Education

Hazrat, M. A., Hassan, N. M. S., Chowdhury, A. A., Rasul, M. G., & Taylor, B. A. (2023) · Sustainability · doi:10.3390/su152316433 · Cited by 141 · see citing works

Digital twin data: methods and key technologies

Zhang, M., Tao, F., Huang, B., Liu, A., Wang, L., Anwer, N., & Nee, A. Y. C. (2021) · Digital Twin · doi:10.12688/digitaltwin.17467.1 · Cited by 139 · see citing works

Perceived risks and vulnerabilities of employing digitalization and digital data in agriculture – Socially robust orientations from a transdisciplinary process

Zscheischler, J., Brunsch, R., Rogga, S., & Scholz, R. W. (2022) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2022.132034 · Cited by 137 · see citing works

Digital Twins for Ports: Derived From Smart City and Supply Chain Twinning Experience

Klar, R., Fredriksson, A., & Angelakis, V. (2023) · IEEE Access · doi:10.1109/access.2023.3295495 · Cited by 137 · see citing works

Digital twin-based anomaly detection for real-time tool condition monitoring in machining

Liu, Z., Lang, Z., Gui, Y., Zhu, Y., & Laalej, H. (2024) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2024.06.004 · Cited by 136 · see citing works

Decentralized cloud manufacturing-as-a-service (CMaaS) platform architecture with configurable digital assets

Hasan, M., & Starly, B. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.05.017 · Cited by 135 · see citing works

Digital twin-driven smart supply chain

Wang, L., Deng, T., Shen, Z. M., Hu, H., & Qi, Y. (2022) · Frontiers of Engineering Management · doi:10.1007/s42524-021-0186-9 · Cited by 135 · see citing works

Digital twin-supported smart city: Status, challenges and future research directions

Wang, H., Chen, X., Jia, F., & Cheng, X. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.119531 · Cited by 135 · see citing works

Digital Twin—A Review of the Evolution from Concept to Technology and Its Analytical Perspectives on Applications in Various Fields

Iliuţă, M.-E., Moisescu, M.-A., Pop, E., Ionita, A.-D., Caramihai, S.-I., & Mitulescu, T.-C. (2024) · Applied Sciences · doi:10.3390/app14135454 · Cited by 134 · see citing works

Consistency retention method for CNC machine tool digital twin model

Wei, Y., Hu, T., Zhou, T., Ye, Y., & Luo, W. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.002 · Cited by 134 · see citing works

Digital Twins for IoT-Driven Energy Systems: A Survey

Kabir, M. R., Halder, D., & Ray, S. (2024) · IEEE Access · doi:10.1109/access.2024.3506660 · Cited by 134 · see citing works

Digital Twin Concepts with Uncertainty for Nuclear Power Applications

Kochunas, B. M., & Huan, X. (2021) · Energies · doi:10.3390/en14144235 · Cited by 133 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

Digital Twin

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