Digital twins in industry 4.0

Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems

Grieves, M., & Vickers, J. (2017) · Transdisciplinary Perspectives on Complex Systems · doi:10.1007/978-3-319-38756-7_4 · Cited by 3,727 · 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: Enabling technologies, challenges and open research

Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020) · IEEE Access · doi:10.1109/access.2020.2998358 · Cited by 2,965 · 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

Characterising the Digital Twin: A systematic literature review

Jones, D., Snider, C., Nassehi, A., Yon, J., & Hicks, B. (2020) · CIRP Journal of Manufacturing Science and Technology · doi:10.1016/j.cirpj.2020.02.002 · Cited by 2,422 · 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

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: values, challenges and enablers from a modeling perspective

Rasheed, A., San, O., & Kvamsdal, T. (2020) · IEEE Access · doi:10.1109/access.2020.2970143 · Cited by 1,952 · 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

From cloud computing to cloud manufacturing

Xu, X. W. (2011) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2011.07.002 · Cited by 1,806 · see citing works

DIGITAL TWIN: MANUFACTURING EXCELLENCE THROUGH VIRTUAL FACTORY REPLICATION

RajratnaKharat, V. B. P. (2018) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.1493930 · Cited by 1,784 · see citing works

DIGITAL TWIN: MANUFACTURING EXCELLENCE THROUGH VIRTUAL FACTORY REPLICATION

Prof. RajratnaKharat*1, V. B. (2018) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.1493929 · Cited by 1,768 · see citing works

Digital Twin-driven smart manufacturing: Connotation, reference model, applications and research issues

Lu, Y., Liu, C., Wang, K. I., Huang, H., & Xu, X. W. (2019) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2019.101837 · Cited by 1,753 · 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

Enabling technologies and tools for digital twin

Qi, Q., Tao, F., Hu, T., Anwer, N., Liu, A., Wei, Y., Wang, L., & Nee, A. Y. C. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2019.10.001 · Cited by 1,579 · see citing works

Towards a semantic Construction Digital Twin: Directions for future research

Boje, C., Guerriero, A., Kubicki, S., & Rezgui, Y. (2020) · Automation in Construction · doi:10.1016/j.autcon.2020.103179 · Cited by 1,477 · 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

Digital Twin—The Simulation Aspect

Boschert, S., & Rosen, R. (2016) · Mechatronic Futures · doi:10.1007/978-3-319-32156-1_5 · Cited by 1,158 · 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

Leveraging Digital Twin Technology in Model-Based Systems Engineering

Madni, A. M., Madni, C. C., & Lucero, S. D. (2019) · Systems · doi:10.3390/systems7010007 · Cited by 1,050 · 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

Industrial Product-Service Systems—IPS 2

Meier, H., Roy, R., & Seliger, G. (2010) · CIRP Annals · doi:10.1016/j.cirp.2010.05.004 · Cited by 994 · see citing works

The Role and Impact of Industry 4.0 and the Internet of Things on the Business Strategy of the Value Chain—The Case of Hungary

Nagy, J., Oláh, J., Erdei, E., Máté, D., & Popp, J. (2018) · Sustainability · doi:10.3390/su10103491 · Cited by 736 · see citing works

Simulation in the design and operation of manufacturing systems: state of the art and new trends

Mourtzis, D. (2019) · International Journal of Production Research · doi:10.1080/00207543.2019.1636321 · Cited by 620 · see citing works

Digital twins to personalize medicine

on behalf of the Swedish Digital Twin Consortium, Björnsson, B., Borrebaeck, C., Elander, N., Gasslander, T., Gawel, D. R., Gustafsson, M., Jörnsten, R., Lee, E. J., Li, X., et al. (2020) · Genome Medicine · doi:10.1186/s13073-019-0701-3 · Cited by 566 · 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

Review on cyber-physical systems

Liu, Y., Peng, Y., Wang, B., Yao, S., & Liu, Z. (2017) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2017.7510349 · Cited by 511 · 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

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

Industrial Big Data as a Result of IoT Adoption in Manufacturing

Mourtzis, D., Vlachou, E. O., & Milas, N. T. (2016) · Procedia CIRP · doi:10.1016/j.procir.2016.07.038 · Cited by 452 · see citing works

The use of Digital Twin for predictive maintenance in manufacturing

Aivaliotis, P., Georgoulias, K., & Chryssolouris, G. (2019) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2019.1686173 · Cited by 439 · see citing works

Simulation in Manufacturing: Review and Challenges

Mourtzis, D., Doukas, M., & Bernidaki, D. (2014) · Procedia CIRP · doi:10.1016/j.procir.2014.10.032 · Cited by 359 · 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

Digital twin-driven supervised machine learning for the development of artificial intelligence applications in manufacturing

Alexopoulos, K., Nikolakis, N., & Chryssolouris, G. (2020) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2020.1747642 · Cited by 315 · 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

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

Blockchain for digital twins: recent advances and future research challenges

Yaqoob, I., Salah, K., Uddin, M., Jayaraman, R., Omar, M., & Imran, M. (2020) · IEEE Network · doi:10.1109/mnet.001.1900661 · Cited by 256 · see citing works

The Airframe Digital Twin: Some Challenges to Realization

Tuegel, E. (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:10.2514/6.2012-1812 · Cited by 255 · 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

Integrating the Digital Twin of the manufacturing system into a decision support system for improving the order management process

Kunath, M., & Winkler, H. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.03.192 · Cited by 233 · see citing works

The digital twin implementation for linking the virtual representation of human-based production tasks to their physical counterpart in the factory-floor

Nikolakis, N., Alexopoulos, K., Xanthakis, E., & Chryssolouris, G. (2018) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2018.1529430 · Cited by 225 · see citing works

Digital Twin Reference Model Development to Prevent Operators’ Risk in Process Plants

Bevilacqua, M., Bottani, E., Ciarapica, F. E., Costantino, F., Donato, L. D., Ferraro, A., Mazzuto, G., Monteriù, A., Nardini, G., Ortenzi, M., et al. (2020) · Sustainability · doi:10.3390/su12031088 · Cited by 223 · see citing works

Digital twin for adaptation of robots’ behavior in flexible robotic assembly lines

Kousi, N., Gkournelos, C., Aivaliotis, S., Giannoulis, C., Michalos, G., & Makris, S. (2019) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.12.020 · Cited by 217 · see citing works

Global production networks: Design and operation

Lanza, G., Ferdows, K., Kara, S., Mourtzis, D., Schuh, G., Váncza, J., Wang, L., & Wiendahl, H. (2019) · CIRP Annals · doi:10.1016/j.cirp.2019.05.008 · Cited by 214 · see citing works

On thermal modeling of Additive Manufacturing processes

Foteinopoulos, P., Papacharalampopoulos, A., & Stavropoulos, P. G. (2017) · CIRP journal of manufacturing science and technology · doi:10.1016/j.cirpj.2017.09.007 · Cited by 209 · see citing works

Design and implementation of a digital twin application for a connected micro smart factory

Park, K. T., Nam, Y. W., Lee, H. S., Im, S. J., Noh, S. D., Son, J. Y., & Kim, H. (2019) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2019.1599439 · Cited by 194 · see citing works

Digital twins of human robot collaboration in a production setting

Malik, A. A., & Bilberg, A. (2018) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.10.047 · 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

Cyber-physical Machine Tool – The Era of Machine Tool 4.0

Liu, C., & Xu, X. W. (2017) · Procedia CIRP · doi:10.1016/j.procir.2017.03.078 · Cited by 178 · see citing works

Digital twin-based cyber physical production system architectural framework for personalized production

Park, K. T., Lee, J.-H., Kim, H.-J., & Noh, S. D. (2019) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-019-04653-7 · Cited by 178 · see citing works

Digital Twin of Experimental Smart Manufacturing Assembly System for Industry 4.0 Concept

Židek, K., Piteľ, J., Adámek, M., Lazorík, P., & Hošovský, A. (2020) · Sustainability · doi:10.3390/su12093658 · Cited by 178 · see citing works

Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning

Pérez, L., Rodríguez-Jiménez, S., Rodríguez, N., Usamentiaga, R., & García, D. (2020) · Applied Sciences · doi:10.3390/app10103633 · Cited by 163 · see citing works

Digital Twin for Machining Tool Condition Prediction

Qiao, Q., Wang, J., Ye, L.-K., & Gao, R. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.04.049 · Cited by 157 · see citing works

Life Cycle Simulation for the design of Product–Service Systems

Garetti, M., Rosa, P., & Terzi, S. (2012) · Computers in Industry · doi:10.1016/j.compind.2012.02.007 · Cited by 156 · see citing works

Challenges and Potentials of Digital Twins and Industry 4.0 in Product Design and Production for High Performance Products

Wagner, R., Schleich, B., Haefner, B., Kuhnle, A., Wartzack, S., & Lanza, G. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.04.219 · Cited by 145 · see citing works

Digital twin enhanced human-machine interaction in product lifecycle

Ma, X., Tao, F., Zhang, M., Wang, T., & Zuo, Y. N. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.04.330 · Cited by 131 · see citing works

Challenges and future perspectives for the life cycle of manufacturing networks in the mass customisation era

Mourtzis, D. (2016) · Logistics Research · doi:10.1007/s12159-015-0129-0 · Cited by 123 · see citing works

Mass Personalization with Industry 4.0 by SMEs: a concept for collaborative networks

Torn, I. A. R., & Vaneker, T. (2019) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.12.022 · Cited by 121 · see citing works

Programming of Industrial Robots Using Virtual Reality and Digital Twins

Burghardt, A., Szybicki, D., Gierlak, P., Kurc, K., Pietruś, P., & Cygan, R. (2020) · Applied Sciences · doi:10.3390/app10020486 · Cited by 117 · see citing works

Review of Cyber-Physical System Architecture

Hu, L. Q., Xie, N., Kuang, Z., & Zhao, K. (2012) · IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW) · doi:10.1109/isorcw.2012.15 · Cited by 116 · see citing works

A Reconfigurable Modeling Approach for Digital Twin-based Manufacturing System

Zhang, C., Xu, W., Liu, J., Liu, Z., Zhou, Z., & Pham, D. T. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.03.141 · Cited by 107 · see citing works

Design and Planning of Manufacturing Networks for Mass Customisation and Personalisation: Challenges and Outlook

Mourtzis, D., & Doukas, M. (2014) · Procedia CIRP · doi:10.1016/j.procir.2014.05.004 · Cited by 104 · see citing works

In-process monitoring of part geometry in fused filament fabrication using computer vision and digital twins

Moretti, M., Rossi, A., & Senin, N. (2020) · Additive manufacturing · doi:10.1016/j.addma.2020.101609 · Cited by 101 · see citing works

Modelling and quantification of industry 4.0 manufacturing complexity based on information theory: a robotics case study

Mourtzis, D., Fotia, S., Boli, N., & Vlachou, E. (2019) · International Journal of Production Research · doi:10.1080/00207543.2019.1571686 · Cited by 99 · see citing works

The development of a digital twin for machining processes for the application in aerospace industry

Hänel, A., Schnellhardt, T., Wenkler, E., Nestler, A., Brosius, A., Corinth, C., Fay, A., & Ihlenfeldt, S. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.04.017 · Cited by 91 · see citing works

A Unified Digital Twin Framework for Real-time Monitoring and Evaluation of Smart Manufacturing Systems

Qamsane, Y., Chen, C.-Y., Balta, E. C., Kao, B.-C., Mohan, S., Moyne, J. R., Tilbury, D. M., & Barton, K. L. (2019) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/coase.2019.8843269 · Cited by 87 · see citing works

Towards improving the future of manufacturing through digital twin and augmented reality technologies

Rabah, S., Assila, A., Khouri, E., Maier, F., Ababsa, F., bourny, V., Maier, P., & Mérienne, F. (2018) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.10.070 · Cited by 86 · see citing works

The Digital Shadow of production – A concept for the effective and efficient information supply in dynamic industrial environments

Bauernhansl, T., Hartleif, S., & Felix, T. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.03.188 · Cited by 84 · see citing works

Development of Skills and Competences in Manufacturing Towards Education 4.0: A Teaching Factory Approach

Mourtzis, D. (2018) · Lecture notes in mechanical engineering · doi:10.1007/978-3-319-89563-5_15 · Cited by 81 · see citing works

Challenges of Digital Twin in High Value Manufacturing

Singh, S. K., Shehab, E., Higgins, N., Fowler, K., Tomiyama, T., & Fowler, C. (2018) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2018-01-1928 · Cited by 71 · see citing works

Application of IoT-Aided Simulation to Manufacturing Systems in Cyber-Physical System

Tan, Y., Yang, W., Yoshida, K., & Takakuwa, S. (2019) · Machines · doi:10.3390/machines7010002 · Cited by 71 · see citing works

Intelligent predictive maintenance and remote monitoring framework for industrial equipment based on mixed reality

Mourtzis, D., Angelopoulos, J., & Panopoulos, N. (2020) · Frontiers in Mechanical Engineering · doi:10.3389/fmech.2020.578379 · Cited by 70 · see citing works

A Digital Twin Reference for Mass Personalization in Industry 4.0

Aheleroff, S., Zhong, R., & Xu, X. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.04.023 · Cited by 62 · see citing works

Integrated Production and Maintenance Scheduling Through Machine Monitoring and Augmented Reality: An Industry 4.0 Approach

Mourtzis, D., Vlachou, E., Zogopoulos, V., & Xanthi, F. (2017) · IFIP advances in information and communication technology · doi:10.1007/978-3-319-66923-6_42 · Cited by 59 · see citing works

Towards Machine Shop 4.0: A General Machine Model for CNC machine-tools through OPC-UA

Mourtzis, D., Milas, N. T., & Athinaios, N. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.09.045 · Cited by 59 · see citing works

A framework for personalized production based on digital twin, blockchain and additive manufacturing in the context of Industry 4.0

Guo, D., Ling, S., Li, H., Ao, D., Zhang, T., Rong, Y. K., & Huang, G. Q. (2020) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/case48305.2020.9216732 · Cited by 55 · see citing works

The Digital Shadow as Enabler for Data Analytics in Product Life Cycle Management

Riesener, M., Schuh, G., Dölle, C., & Tönnes, C. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.01.083 · Cited by 51 · see citing works

The Digital Twin Paradigm for Smarter Systems and Environments: The Industry Use Cases

(2020) · Advances in computers · doi:10.1016/s0065-2458(20)x0003-9 · Cited by 49 · see citing works

A molecular dynamics based digital twin for ultrafast laser material removal processes

Stavropoulos, P., Papacharalampopoulos, A., & Athanasopoulou, L. (2020) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-020-05387-7 · Cited by 46 · see citing works

Chatter model for enabling a digital twin in machining

Afazov, S. M., & Scrimieri, D. (2020) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-020-06028-9 · Cited by 44 · see citing works

A Hierarchical Digital Twin Model Framework for Dynamic Cyber-Physical System Design

Shangguan, D., Chen, L., & Ding, J. (2019) · International Conference on Mechatronics and Robotics Engineering (ICMRE) · doi:10.1145/3314493.3314504 · Cited by 43 · see citing works

Digital Twin of manufacturing systems: a case study on increasing the efficiency of reconfiguration

Talkhestani, B. A., & Weyrich, M. (2020) · at - Automatisierungstechnik · doi:10.1515/auto-2020-0003 · Cited by 42 · see citing works

Using finite element analysis to develop a digital twin of a manufacturing bending operation

Hinchy, E., Carcagno, C., O'Dowd, N., & McCarthy, C. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.03.031 · Cited by 42 · see citing works

A Digital Twin for Automated Root-Cause Search of Production Alarms Based on KPIs Aggregated from IoT

Papacharalampopoulos, A., Giannoulis, C., Stavropoulos, P. G., & Mourtzis, D. (2020) · Applied Sciences · doi:10.3390/app10072377 · Cited by 40 · see citing works

A three-stage quality diagnosis platform for laser-based manufacturing processes

Stavropoulos, P. G., Papacharalampopoulos, A., Stavridis, J., & Sampatakakis, K. (2020) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-020-05981-9 · Cited by 40 · see citing works

Design and development of a flexible manufacturing cell in the concept of learning factory paradigm for the education of generation 4.0 engineers

Mourtzis, D., Angelopoulos, J., & Dimitrakopoulos, G. (2020) · Procedia Manufacturing · doi:10.1016/j.promfg.2020.04.035 · Cited by 39 · see citing works

Towards a digital twin for manufacturing processes: applicability on laser welding

Papacharalampopoulos, A., Stavropoulos, P., & Petrides, D. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.05.020 · Cited by 37 · see citing works

Machine Tool 4.0 in the Era of Digital Manufacturing

Mourtzis, D. (2020) · European Modeling & Simulation Symposium (EMSS) · doi:10.46354/i3m.2020.emss.060 · Cited by 29 · see citing works

From Open CNC Systems to Cyber-Physical Machine Tools: A Case Study

Deng, C., Guo, R., Zheng, P., Liu, C., Xu, X. W., & Zhong, R. Y. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.03.110 · Cited by 28 · see citing works

Towards a Digital Twin for Thermal Processes: Control-centric approach

Papacharalampopoulos, A., & Stavropoulos, P. G. (2019) · Procedia CIRP · doi:10.1016/j.procir.2020.01.015 · Cited by 28 · see citing works

Digital Twin Based Optimization of a Manufacturing Execution System to Handle High Degrees of Customer Specifications

Barni, A., Pietraroia, D., Züst, S., West, S., & Stoll, O. (2020) · Journal of Manufacturing and Materials Processing · doi:10.3390/jmmp4040109 · Cited by 28 · see citing works

Design of customised products and manufacturing networks: towards frugal innovation

Mourtzis, D. (2018) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2018.1509131 · Cited by 27 · see citing works

Holistic approach for integrating customers in the design, planning, and control of global production networks

Hochdörffer, J., Buergin, J., Vlachou, E., Zogopoulos, V., Lanza, G., & Mourtzis, D. (2018) · CIRP journal of manufacturing science and technology · doi:10.1016/j.cirpj.2018.07.004 · Cited by 25 · see citing works

Machine Tool: From the Digital Twin to the Cyber-Physical Systems

Armendia, M., Alzaga, A., Peysson, F., Fuertjes, T., Cugnon, F., Öztürk, E., & Flum, D. (2019) · Springer eBooks · doi:10.1007/978-3-030-02203-7_1 · Cited by 25 · see citing works

Virtualise manufacturing capabilities in the cloud: requirements, architecture and implementation

Wang, X. V., & Xu, X. W. (2014) · International Journal of Manufacturing Research · doi:10.1504/ijmr.2014.066665 · Cited by 19 · see citing works

Adaptive Scheduling in the Era of Cloud Manufacturing

Mourtzis, D. (2020) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-3-030-43177-8_4 · Cited by 15 · see citing works

Simulation-based Verification with Experimentable Digital Twins in Virtual Testbeds

Dahmen, U., & Roßmann, J. (2018) · Springer eBooks · doi:10.1007/978-3-662-56714-2_16 · Cited by 13 · see citing works

Cycle Time Estimation Model for Hybrid Assembly Stations Based on Digital Twin

Mourtzis, D., Angelopoulos, J., & Siatras, V. (2020) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-57993-7_20 · Cited by 8 · see citing works

Analytical basics of digital twin for CNC round grinding process

Викторовна, А. А., Переверзев, П. П., Reshetnikov, B., & Irshin, A. V. (2020) · Materials Today Proceedings · doi:10.1016/j.matpr.2020.08.244 · Cited by 8 · see citing works

Manufacturing Process Control Through a Digital Twin: Encoding IssuesPreprint

Papacharalampopoulos, A., Michail, C. K., & Stavropoulos, P. G. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3718017 · Cited by 8 · see citing works

Smart Products in Smart Manufacturing Systems: An Opportunity to Utilize AR?

Gross, J., & Wuest, T. (2020) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-57993-7_55 · Cited by 2 · see citing works

A literature review and design methodology for digital twins in the era of zero defect manufacturing

Psarommatis, F., & May, G. (2022) · International Journal of Production Research · doi:10.1080/00207543.2022.2101960 · Cited by 143 · see citing works

Digital twin for human-robot collaboration enhancement in manufacturing systems: Literature review and direction for future developments

Baratta, A., Cimino, A., Longo, F., & Nicoletti, L. (2023) · Computers & Industrial Engineering · doi:10.1016/j.cie.2023.109764 · Cited by 130 · see citing works

Digital twins: Recent advances and future directions in engineering fields

Iranshahi, K., Brun, J., Arnold, T., Sergi, T., & Müller, U. C. (2025) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2025.200516 · Cited by 132 · see citing works

Digital twins in Industry 5.0

Lv, Z. (2023) · Research · doi:10.34133/research.0071 · Cited by 108 · see citing works

A hybrid teaching factory model towards personalized education 4.0

Mourtzis, D., Panopoulos, N., & Angelopoulos, J. (2022) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2022.2145025 · Cited by 66 · see citing works

Digital Twin Implementation in Additive Manufacturing: A Comprehensive Review

Amor, S. B., Elloumi, N., Eltaief, A., Louhichi, B., Alrasheedi, N., & Seibi, A. (2024) · Processes · doi:10.3390/pr12061062 · Cited by 62 · see citing works

Digital twin inception in the Era of industrial metaverse

Mourtzis, D. (2023) · Frontiers in Manufacturing Technology · doi:10.3389/fmtec.2023.1155735 · Cited by 56 · see citing works

Digital Thread-Driven Proactive and Reactive Service Composition for Cloud Manufacturing

Yang, B. Y., Wang, S., Li, S., & Bi, F. (2022) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2022.3171338 · Cited by 45 · see citing works

Credibility consideration for digital twins in manufacturing

Shao, G., Hightower, J., & Schindel, W. D. (2022) · Manufacturing Letters · doi:10.1016/j.mfglet.2022.11.009 · Cited by 51 · see citing works

Experimental investigations and modeling for multi-pass laser micro-milling by soft computing-physics informed machine learning on PMMA sheet using CO2 laser

Anjum, A., Shaikh, A. A., & Tiwari, N. (2022) · Optics & Laser Technology · doi:10.1016/j.optlastec.2022.108922 · Cited by 43 · see citing works

An adaptive, artificial intelligence-based chatter detection method for milling operations

Stavropoulos, P. G., Souflas, T., Papaioannou, C., Bikas, H., & Mourtzis, D. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-09920-8 · Cited by 42 · see citing works

The Use of Digital Twins to Address Smart Tourist Destinations’ Future Challenges

Florido‐Benítez, L. (2024) · Platforms · doi:10.3390/platforms2040016 · Cited by 46 · see citing works

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Leng, J., Gardoni, P., Wang, M., Li, Z., Królczyk, G., Feng, S., İncecik, A., & Li, W. (2023) · Structural Health Monitoring · doi:10.1177/14759217221148688 · Cited by 39 · see citing works

Beyond Industry 4.0: Tracing the Path to Industry 5.0 through Bibliometric Analysis

Durnoi, A.-N. C., Delcea, C., Stănescu, A., Teodorescu, C. A., & Vargas, V. (2024) · Sustainability · doi:10.3390/su16125251 · Cited by 38 · see citing works

Digitization of Manufacturing Processes: From Sensing to Twining

Stavropoulos, P. (2022) · Technologies · doi:10.3390/technologies10050098 · Cited by 37 · see citing works

Digital Twin Cognition: AI-Biomarker Integration in Biomimetic Neuropsychology

Gkintoni, E., & Halkiopoulos, C. (2025) · Biomimetics · doi:10.3390/biomimetics10100640 · Cited by 41 · see citing works

Integration of SCADA and Industrial IoT: Opportunities and Challenges

Nechibvute, A., & Mafukidze, H. D. (2023) · IETE Technical Review · doi:10.1080/02564602.2023.2246426 · Cited by 37 · see citing works

Digital twin of buildings and occupants for emergency evacuation: Framework, technologies, applications and trends

Lin, J., Chen, K.-Y., Song, S.-Y., Cai, Y., Pan, P., & Deng, Y. (2025) · Advanced Engineering Informatics · doi:10.1016/j.aei.2025.103419 · Cited by 28 · see citing works

Synthetic data generation for digital twins: enabling production systems analysis in the absence of data

Lopes, P. V., Silveira, L., Aquino, R. D. G., Ribeiro, C. H., Skoogh, A., & Verri, F. (2024) · International journal of computer integrated manufacturing (Print) · doi:10.1080/0951192x.2024.2322981 · Cited by 21 · see citing works

Personalized PSS Design Optimization based on Digital Twin and Extended Reality

Mourtzis, D., Angelopoulos, J., & Panopoulos, N. (2022) · Procedia CIRP · doi:10.1016/j.procir.2022.05.267 · Cited by 26 · see citing works

Barriers to the adoption of the Metaverse in digital supply chains

Butt, A. S., Alghababsheh, M., & Awan, U. (2025) · Journal of Enterprise Information Management · doi:10.1108/jeim-09-2024-0500 · Cited by 24 · see citing works

A data-driven digital twin framework for key performance indicators in CNC machining processes

Vishnu, V. S., Varghese, K. G., & Gurumoorthy, B. (2023) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2023.2177741 · Cited by 23 · see citing works

Architectural framework of digital twin-based cyber-physical production system for resilient rechargeable battery production

Park, K. T., Park, Y. H., Park, M.-W., & Noh, S. D. (2023) · Journal of Computational Design and Engineering · doi:10.1093/jcde/qwad024 · Cited by 27 · see citing works

Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0

Mon, B. F., Hayajneh, M., Ali, N. A., Ullah, F., Ullah, H., & Alkobaisi, S. (2025) · Computers, Materials & Continua · doi:10.32604/cmc.2025.061411 · Cited by 26 · see citing works

Leveraging Digital Twins as a Common Operating Picture for Disaster Management: Case of Seismic Hazards

Korkmaz, M., Zülfikar, A. C., & Demirkesen, S. (2024) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi13120430 · Cited by 22 · see citing works

On the Optimization of Robot Machining: A Simulation-Based Process Planning Approach

Souflas, T., Gerontas, C., Bikas, H., & Stavropoulos, P. G. (2024) · Machines · doi:10.3390/machines12080521 · Cited by 22 · see citing works

The architecture evolution of intelligent factory logistics digital twin from planning, implement to operation

Qiu, F., Chen, M., Wang, L., Yu, Y., & Tang, T. (2023) · Advances in Mechanical Engineering · doi:10.1177/16878132231198339 · Cited by 18 · see citing works

Integration of game theory optimization in financial markets: a systematic literature review based on TCCM framework

Ganti, A., & Singhania, S. (2024) · Journal of Modelling in Management · doi:10.1108/jm2-04-2024-0114 · Cited by 18 · see citing works

Advances in Adaptive Scheduling in Industry 4.0

Mourtzis, D. (2022) · Frontiers in Manufacturing Technology · doi:10.3389/fmtec.2022.937889 · Cited by 17 · see citing works

Digital Twin Technology in Wireless Communication: A Comprehensive Engineering Survey

Bhatia, M., & Kumar, R. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3565843 · Cited by 15 · see citing works

Challenges and opportunities of the transition from Industry 4.0 to Industry 5.0

Mourtzis, D. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13924-6.00004-1 · Cited by 15 · see citing works

RMPFQ: A Quality-Oriented Knowledge Modelling Method for Manufacturing Systems Towards Cognitive Digital Twins

Zheng, X., Petrali, P., Lu, J., Turrin, C., & Kiritsis, D. (2022) · Frontiers in Manufacturing Technology · doi:10.3389/fmtec.2022.901364 · Cited by 14 · see citing works

Plant disease epidemiology in the age of artificial intelligence and machine learning

Neik, T. X., Dolatabadian, A., Danilevicz, M. F., Upadhyaya, S. R., Zhang, F., Batley, J., & Edwards, D. (2025) · Agriculture Communications · doi:10.1016/j.agrcom.2025.100089 · Cited by 14 · see citing works

Use of Digital Twin Technology in the Teaching-Learning Process, in the field of University Education: A Bibliometric Review

Chamorro-Atalaya, O., Flores-Velásquez, C. H., Flores-Cáceres, R., Arévalo-Tuesta, J. A., Castañeda, M. E. Z., Quispe, G. E. T., Aranda-Dextre, C. C., Cruz-Telada, Y., Caller-Luna, J., & Anco, R. J. A. (2024) · International Journal of Learning Teaching and Educational Research · doi:10.26803/ijlter.23.2.15 · Cited by 13 · see citing works

A roadmap for selection of metal welding process: a review and proposals

Soltan, H., & Omar, M. (2022) · Welding in the World · doi:10.1007/s40194-022-01379-1 · Cited by 13 · see citing works

Using constrained-disorder principle-based systems to improve the performance of digital twins in biological systems (Preprint)Preprint

Sigawi, T., & Ilan, Y. (2023) · doi:10.2196/preprints.46304 · Cited by 12 · see citing works

Using Cloning-GAN Architecture to Unlock the Secrets of Smart Manufacturing: Replication of Cognitive Models

Terziyan, V. Y., & Tiihonen, T. (2024) · Procedia Computer Science · doi:10.1016/j.procs.2024.01.089 · Cited by 11 · see citing works

Sustainable Smart Cities - A Vision for Tomorrow

Almusaed, A., & Almssad, A. (2022) · IntechOpen eBooks · doi:10.5772/intechopen.100727 · Cited by 11 · see citing works

A Method for Dynamic Insertion Order Scheduling in Flexible Job Shops Based on Digital Twins

Wang, Y., Leng, J., Liu, X., Wang, J., & Meng, Q. (2022) · Applied Sciences · doi:10.3390/app122312430 · Cited by 10 · see citing works

Artificial Intelligence for Production Management and Control Towards Mass Personalization of Global Networks

Mourtzis, D., Panopoulos, N., Stavropoulos, P. G., & Papakostas, N. (2024) · Lecture notes in mechanical engineering · doi:10.1007/978-3-031-54034-9_8 · Cited by 9 · see citing works

Scientometric Analysis of Digital Twin in Industry 4.0

Kaur, H., & Bhatia, M. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3459965 · Cited by 17 · see citing works

An approach to improve asset maintenance and management priorities using machine learning techniques

Nithin, A. H., Hobbs, M., Sriramula, S., & Sripada, S. G. (2022) · Safety and Reliability · doi:10.1080/09617353.2022.2142011 · Cited by 8 · see citing works

A Literature Review of Digital Twins and Their Applications in the Internet of Things Based on Artificial Intelligence

Hnaien, I. B., Gascard, E., Simeu-Abazi, Z., & Dhouibi, H. (2024) · International Conference on Control, Automation and Diagnosis (ICCAD) · doi:10.1109/iccad60883.2024.10553718 · Cited by 7 · see citing works

IoT and Digital Twins for Ssmart Food Supply Chains

Rashed, M. S., Fakhry, S., Satour, R., Abdelkarim, E. A., Sobhy, M., & Pathania, S. (2025) · Sustainable development goals series · doi:10.1007/978-3-031-76758-6_16 · Cited by 8 · see citing works

Blending Human Ware with Software and Hardware in the Design of Smart Cities

Almusaed, A., & Almssad, A. (2022) · IntechOpen eBooks · doi:10.5772/intechopen.109053 · Cited by 7 · see citing works

AI-driven predictive modeling of homogeneous bead geometry for WAAM processes

Fernández-Zabalza, A., Rodríguez-Díaz, Á., Veiga, F., Suárez, A., Uralde, V., Ballesteros, T., & Alfaro-Lopez, J. R. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-16061-1 · Cited by 6 · see citing works

Real-Time Digital Twin Architecture for Immersive Industrial Automation Training

Ortiz, J. S., Andaluz, V. H., & Carvajal, C. P. (2026) · Sensors · doi:10.3390/s26072023 · Cited by 6 · see citing works

Digital process twins: a modular approach for surface conditioning and process optimization

Clark, B., Schoop, J., & Poonawala, H. A. (2024) · Production Engineering · doi:10.1007/s11740-023-01250-2 · Cited by 6 · see citing works

Digital Twin for Field Data Management: Design of a platform to promote FAIR principles and ensure data reusability

Hamlaoui, R., Orimi, A. G., Donia, R., Backe, C., Briken, V., & Lachmayer, R. (2025) · Procedia CIRP · doi:10.1016/j.procir.2025.08.030 · Cited by 5 · see citing works

Digital Twins and Cyber–Physical Systems Toward the Digitalization of Power and Energy Systems

Pham, L. N. H., Shrestha, A., Sharma, C., & Gonzalez-longatt, F. M. (2025) · IEEE Transactions on Technology and Society · doi:10.1109/tts.2025.3615624 · Cited by 6 · see citing works

Towards Declarative Deployment and Lifecycle Orchestration of Digital Twin Ecosystems

Andruccioli, M., Girau, R., Mirri, S., & Salomoni, P. (2026) · IEEE Consumer Communications and Networking Conference · doi:10.1109/ccnc65079.2026.11366397 · Cited by 4 · see citing works

A framework for process states structural interpretation of zero-defect manufacturing

Xu, Z., Guo, Z., Zhang, G., Zhou, X., & Zhang, Y. (2024) · Advanced Engineering Informatics · doi:10.1016/j.aei.2024.102442 · Cited by 4 · see citing works

Developing a Digital Twin for Human Performance Assessment in Human–Machine Interaction

Novak, E., Javernik, A., Palčić, I., & Ojsteršek, R. (2026) · Machines · doi:10.3390/machines14030346 · Cited by 4 · see citing works

Enhancing the Wireless Network's Energy Efficiency to Reduce Security Challenges in 5G Systems: A Review

Maiwada, U. D., Danyaro, K. U., Sarlan, A. B., Liew, M. S., & Audi, U. I. (2023) · WSEAS TRANSACTIONS on COMMUNICATIONS archive · doi:10.37394/23204.2023.22.16 · Cited by 3 · see citing works

Influence of Solvers and their Characteristics on Simulation Time and Accuracy Exemplified for a Vacuum Gripping System

Stegmaier, V., Dittler, D., Jazdi, N., & Weyrich, M. (2023) · Procedia CIRP · doi:10.1016/j.procir.2023.09.064 · Cited by 3 · see citing works

A Digital Twin Approach and Challenges for Real-Time Automated Surface-Drip Irrigation Monitoring: A Case of Arusha Tanzania

Wangere, J., Sinde, R., Ally, M., & Mbwambo, O. (2024) · Progress in IS · doi:10.1007/978-3-031-56603-5_5 · Cited by 3 · see citing works

Data-Driven Logistics Optimization

Kanyepe, J. (2024) · Advances in logistics, operations, and management science book series · doi:10.4018/979-8-3693-6205-1.ch003 · Cited by 5 · see citing works

Integrating 3D object detection with ontologies for accurate digital twin creation in manufacturing systems

Boroukhian, T., Supyen, K., Samson, J. B., Bashyal, A., & Wicaksono, H. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-16548-x · Cited by 5 · see citing works

Sustainability through digital transformation: EU practices

Karadayi‐Usta, S. (2024) · Sustainable Social Development · doi:10.54517/ssd.v2i1.2434 · Cited by 3 · see citing works

Research on the development and application of digital twin for the full life cycle of bridge engineering

Tao, H. (2024) · Theoretical and Natural Science · doi:10.54254/2753-8818/31/20241153 · Cited by 2 · see citing works

Achieving Customer Satisfaction Drive-Thru Services through Digital Twins in America

Lanawaang, Y. M., Suryawijaya, T. W. E., Mahmud, M., & Zhou, B. (2024) · International Journal of Digital Entrepreneurship and Business · doi:10.52238/ideb.v5i1.148 · Cited by 2 · see citing works

A Digital Twin Framework for Industry 4.0/5.0 Technologies

Asranov, M., Aliev, K., Chiabert, P., & Inoyatkhodjaev, J. (2024) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-62578-7_2 · Cited by 2 · see citing works

Optimization Machining Processes in Multi-User Cyber-Physical Cells: A Comparative

Martins, G. S. M., Martins, T. C., Soares, T. R., Zafalão, I. H. L., Fernandes, A. D. C., Graziani, Á. P., Camillo, B. Z., Simoni, R., & Trabasso, L. G. (2024) · International Conference on Automation, Robotics and Computer Engineering (ICARCE) · doi:10.1109/icarce63054.2024.00017 · Cited by 2 · see citing works

Problems of Using Digital Twins in Ensuring Information Security of Critical Information Infrastructure Facilities

Mityakov, E. (2023) · Telecom IT · doi:10.31854/2307-1303-2023-11-4-36-47 · Cited by 3 · see citing works

Geometric Coherence of a Digital Twin: A Discussion

Lammini, A., Pinquié, R., & Foucault, G. (2023) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-25182-5_23 · Cited by 1 · see citing works

Digital Twins and Green Paths

Khan, A., Jhanjhi, N. Z., & Ray, S. K. (2024) · Advances in logistics, operations, and management science book series · doi:10.4018/979-8-3693-5375-2.ch002 · Cited by 1 · see citing works

Leveraging Recurrent Neural Networks in Virtual Reality-based Digital Twin Models for Enhanced Predictive Maintenance of Industrial Machines

Razzaq, H. A., Mehmood, M., & Khan, F. (2024) · International Multi-Topic Conference · doi:10.1109/inmic64792.2024.11004403 · Cited by 1 · see citing works

A Cyber-Physical Production Systems Framework with Scheduling-Based Optimization Modules

Krenczyk, D., Kalinowski, K., Skołud, B., & Jagodziński, M. (2025) · Lecture notes in mechanical engineering · doi:10.1007/978-3-032-01517-4_38 · Cited by 1 · see citing works

Introduction

Stavropoulos, P. G. (2023) · SpringerBriefs in applied sciences and technology · doi:10.1007/978-3-031-33793-2_1 · Cited by 1 · see citing works

DRIVE-THRU REVOLUTION: ENHANCING CUSTOMER SATISFACTION THROUGH DIGITAL TWINS

Lanawaang, Y. M., & Suryawijaya, T. W. E. (2024) · Business Management Analysis Journal (BMAJ) · doi:10.24176/bmaj.v7i1.12130 · Cited by 1 · see citing works

Digital twin technology for energy flexibility and saving

Avendano, I. A. C., Javan, F. D., Najafi, B., Aghaei, M., Moazami, A., & Rinaldi, F. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-14070-9.00011-1 · Cited by 1 · see citing works

Automated Configuration of Behavior Models in Digital Twins based on a Knowledge-Graph

Dittler, D., Bodenstein, F., Hildebrandt, G., Jazdi, N., & Weyrich, M. (2024) · Procedia CIRP · doi:10.1016/j.procir.2024.10.148 · Cited by 1 · see citing works

Fun and E-learning (A Hybrid Teaching Factory Model)

Nurmalasari, D., Yulia, A., & Rusni, I. M. (2024) · Proceeding of International Student Conference on Business, Education, Economics, Accounting, and Management. · doi:10.21009/isc-beam.011.52

Logistics of Bulk Material Handling - Challenges for a Holistic Simulation Approach

Katterfeld, A., & Otto, H. (2024) · Lecture notes in logistics · doi:10.1007/978-3-031-70977-7_14

Enhancing Mass Customization Using a Digital Twin: Review and Model Development

Bezuneh, M. K., Tsegaw, A. A., Woldegiorgis, B. H., Bogale, T. M., Brossog, M., & Franke, J. E. (2025) · Green energy and technology · doi:10.1007/978-3-031-77339-6_8

Industrial Metaverse Towards Human-Centric Smart Manufacturing

Mourtzis, D. (2025) · Springer eBooks · doi:10.1007/978-3-031-82170-7_1

Hybrid evolutionary algorithm for maximizing medical equipment supply during pandemic✰

James, C. D., & Mondal, S. (2025) · Systems and Soft Computing · doi:10.1016/j.sasc.2025.200275

Digital twin for early-stage fault detection in a hybrid manufacturing cell

Tsakalos, D., Krimpas, G. A., & Mourtzis, D. (2026) · Digital Twin · doi:10.1080/27525783.2026.2622705

Digital twin for energy efficient integrated building management systems: a review towards sustainable development

Nasser, S. G. A., Zahab, E. A., & Essa, M. E.-S. M. (2026) · Digital Twin · doi:10.1080/27525783.2026.2700904

Digital twin–enabled Industry 4.0 transformation: empirical insights into lean manufacturing practices and circular economy practices in SMEs

Al-Hashimy, H. N. H., Yao, J., Pitchay, A. A., & Hussein, W. N. (2026) · Journal of Manufacturing Technology Management · doi:10.1108/jmtm-12-2025-1251

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

Digital Twin Past, Present, and Future

Sermakani, A. M., Radhika, R., & Sujatha, V. (2024) · Auerbach Publications eBooks · doi:10.1201/9781003469612-1

Digital Twin for the Industry 4.0: Overview, Challenges, and OpportunitiesPreprint

Caiza, G. J., & Sanz, R. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4038241 · Cited by 2 · see citing works

Artificial Intelligence and Internet of Things (IoT) Facilitated Digital Twin for Industry 4.0 Application Domains

Rana, R., & Bhambri, P. (2024) · CRC Press eBooks · doi:10.1201/9781003395416-11 · Cited by 7 · see citing works

A Survey of Digital Twin for Industry 4.0: Benefits, Challenges and Opportunities

Murgod, T. R., Sundaram, S. M., Mahanthesha, U., & Murugesan, P. (2023) · SN Computer Science · doi:10.1007/s42979-023-02363-2 · Cited by 13 · see citing works