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About The Importance of Autonomy and Digital Twins for the Future of Manufacturing
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Industrie 4.0 - the “brand” name of the German initiative driving the future of manufacturing - is one of several initiatives around the globe emphasizing the importance of industrial manufacturing for economy and society. Besides the socio-economical if not political question which has to be answered - including the question about the future of labor - there are a couple of substantial technical and technological questions that have to be taken care of as well.
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“In Table 1 seven articles developed ' ad-hoc ' systems to build DT: for the management of a didactic production line [26], to construct a MES in Android systems [43], to build user guides for safety reason [60,62], and to evaluate the performances of a cloud-based DT [74,75];”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [62]
In the citing paper
“For this aspect, the articles considered can be divided into two different categories: (i) those that effectively use a cloud and build a cloud-based DT application, marked in the table as [27,34,37,43,47,48,54,56,62,67,74-76], (ii) those that construct the DT application in a virtual space with the use of a software highlighting the possibility to build it also in a cloud”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [62]
In the citing paper
“Also, there are papers that mainly belong to the first group but also offer services of the second group ([39,40,50,70]), and vice versa ([56,61,62]).”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [62]
In the citing paper
“It can also be implemented for its capability to represent and deal with a continuous flow of data [48] [49].”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [48]
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Research works printed but not linked: 2
- Siemens 2014. A worldwide production language, Siemens Industry Journal, 01 | 2014 | siemens.com/industry
- Tenorth, 2013, KnowRob – A Knowledge Processing Infrastructure for Cognition-enabled Robots, International Journal of Robotics Research (IJRR), 32
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Digital Twin for Human–Robot Collaboration in Manufacturing: Review and Outlook
Ramasubramanian, A. K., Mathew, R., Kelly, M., Hargaden, V., & Papakostas, N. (2022) · Applied Sciences · doi:10.3390/app12104811 · Cited by 108
Sánchez-Vaquerizo, J. A. (2021) · ISPRS Int. J. Geo Inf. · doi:10.3390/ijgi11010024 · Cited by 81
“In fact, it matches the early definitions of digital twins [4,106,107] and it is closer to the concept of digital shadow [108].”
BackgroundStavropoulos, P., & Mourtzis, D. (2022) · Design and Operation of Production Networks for Mass Personalization in the Era of Cloud Technology · doi:10.1016/b978-0-12-823657-4.00010-5 · Cited by 80
Hananto, A., Tirta, A., Herawan, S., Idris, M., Soudagar, M. E. M., Djamari, D. W., & Veza, I. (2024) · De Computis · doi:10.3390/computers13040100 · Cited by 79
A review of unit level digital twin applications in the manufacturing industry
Böttjer, T., Tola, D., Kakavandi, F., Wewer, C. R., Ramanujan, D., Gomes, C. Â. G., Larsen, P. G., & Iosifidis, A. (2023) · CIRP journal of manufacturing science and technology · doi:10.1016/j.cirpj.2023.06.011 · Cited by 92
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
A Deep-Reinforcement-Learning-Based Digital Twin for Manufacturing Process Optimization
Khdoudi, A., Masrour, T., Hassani, I. E., & Mazgualdi, C. E. (2024) · Systems · doi:10.3390/systems12020038 · Cited by 102
Digital Twin and Data-Driven Quality Prediction of Complex Die-Casting Manufacturing
Liu, D., Du, Y., Chai, W., Lu, C., & Cong, M. (2022) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2022.3168309 · Cited by 78
Göppert, A., Grahn, L., Rachner, J., Grunert, D., Hort, S., & Schmitt, R. (2021) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-021-01860-6 · Cited by 78
“3 JSON Schema defining required properties for parameter of earlies starting date of a digital twin, embedding it within the framework of cyber-physical systems (CPS) is often applied (Rosen et al., 2015; Stark & Damerau, 2019; Uhlemann et al., 2017; Weyer et al., 2016).”
MethodSteering Representations—Towards a Critical Understanding of Digital Twins
Korenhof, P., Blok, V., & Kloppenburg, S. (2021) · Philosophy & Technology · doi:10.1007/s13347-021-00484-1 · Cited by 86
“…technical discourse Digital Twins are said to be employed for the purposes of “optimisation”, “efficiency”, “better management and control”, “diagnostics”, “health management”, to “increase lifespan and success”, etcetera (see, e.g. Rosen et al., 2015; Schleich et al., 2017; Verdouw et al., 2021).”
Digital Twin-based manufacturing system: a survey based on a novel reference model
Liu, S., Zheng, P., & Bao, J. (2023) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-023-02172-7 · Cited by 84
“In order to cope with the growth of market demand for product personalization and small-batch, the current manufactur-ingindustryischangingtothesmartmanufacturingparadigm (Rosen et al., 2015), which has the characteristics of “high quality, high efficiency and low consumption”.”
Suuronen, S., Ukko, J., Eskola, R., Semken, R. S., & Rantanen, H. (2022) · CIRP - Journal of Manufacturing Science and Technology · doi:10.1016/j.cirpj.2022.02.016 · Cited by 76
Zhang, X., & Zhu, W. (2019) · International Journal of Advanced Robotic Systems · doi:10.1177/1729881419880663 · Cited by 90
Shahriar, M. R., Sunny, S. M. N. A., Liu, X., Leu, M. C., Hu, L., & Nguyen, N.-T. (2018) · 2018 5th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2018 4th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom) · doi:10.1109/cscloud/edgecom.2018.00018 · Cited by 75
Ontology-based modeling of part digital twin oriented to assembly
Bao, Q.-W., Zhao, G.-H., Yu, Y., Dai, S., & Wang, W. (2020) · Proceedings of the Institution of mechanical engineers. Part B, journal of engineering manufacture · doi:10.1177/0954405420941160 · Cited by 75
“Meanwhile, the connectivity, modularity and autonomy of digital twin also challenge the modeling approach in the lifecycle of a product.(3) Particularly, the assembly phase of a product is full of uncertainties and real-time requirements, which demand the digital twin of assembly workflow to be more structured and con…”
BackgroundSupporting the lean journey with simulation and optimization in the context of Industry 4.0
Uriarte, A. G., Ng, A., & Moris, M. (2018) · doi:10.1016/j.promfg.2018.06.097 · Cited by 74
Machining process-oriented monitoring method based on digital twin via augmented reality
Liu, S., Lu, S., Li, J., Sun, X., Lu, Y., & Bao, J. (2021) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-06838-5 · Cited by 80
Digital Twins for Precision Healthcare
Ahmadi-Assalemi, G., Al-Khateeb, H. M., Maple, C., Epiphaniou, G., Alhaboby, Z. A., Alkaabi, S., & Alhaboby, D. (2020) · Advanced sciences and technologies for security applications · doi:10.1007/978-3-030-35746-7_8 · Cited by 73
Digital Twins: A Systematic Literature Review Based on Data Analysis and Topic Modeling
Kukushkin, K., Ryabov, Y., & Borovkov, A. I. (2022) · Data · doi:10.3390/data7120173 · Cited by 94
“This cluster clearly The red cluster co-citation leaders are F. Tao, H. Zhang and M. Grieves. twin [1,3,4,25,29–32].”
BackgroundGeneric development methodology for flexible robotic pick-and-place workcells based on Digital Twin
Tipary, B., & Erdös, G. (2021) · Robotics Comput. Integr. Manuf. · doi:10.1016/j.rcim.2021.102140 · Cited by 72
“Meanwhile, enabled by the industrial digitalization, the concept of Digital Twin (DT) receives significant attention [6,7].”
BackgroundA virtual commissioning based methodology to integrate digital twins into manufacturing systems
Barbieri, G., Bertuzzi, A., Capriotti, A., Ragazzini, L., Gutierrez, D., Negri, E., & Fumagalli, L. (2021) · Production Engineering · doi:10.1007/s11740-021-01037-3 · Cited by 72
A multi-layered view of chemical and biochemical engineering
Gani, R., Bałdyga, J., Biscans, B., Brunazzi, E., Charpentier, J., Drioli, E., Feise, H. J., Furlong, A., Geem, K. M. V., de Hemptinne, J.-C., et al. (2020) · Process Safety and Environmental Protection · doi:10.1016/j.cherd.2020.01.008 · Cited by 84
“To this end concepts such as digital twins, hybrid-297 modeling techniques, novel sensors that are currently under development should receive more 298 attention (Rosen et al., 2015).”
Hidden Markov model-based digital twin construction for futuristic manufacturing systems
Ghosh, A. K., Ullah, A., & Kubo, A. (2019) · Artificial intelligence for engineering design, analysis and manufacturing · doi:10.1017/s089006041900012x · Cited by 72
“Rosen et al .”
Sun, Z., Jayasinghe, S., Sidiq, A., Shahrivar, F., Mahmoodian, M., & Setunge, S. (2024) · Sensors · doi:10.3390/s25010059 · Cited by 76
Digital twin-driven dynamic scheduling of a hybrid flow shop
Tliba, K., Diallo, T. M. L., Penas, O., Khalifa, R. B., Yahia, N. B., & Choley, J. (2022) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-022-01922-3 · Cited by 69
“DT has been recently introduced and extensively adopted in the production systems sector, particularly for assembly lines, prognostics, shop floor management, in order to provide a realistic virtual modeling of the physical systems based on its real behavior (Negri et al., 2017; Rosen et al., 2015).”
BackgroundBuilding digital twins of existing highways using map data based on engineering expertise
Jiang, F., Ma, L., Broyd, T., Chen, W.-Y., & Luo, H.-B. (2022) · Automation in Construction · doi:10.1016/j.autcon.2021.104081 · Cited by 69
Chen, B.-Q., Liu, K., Yu, T., & Li, R. (2024) · Energies · doi:10.3390/en17081964 · Cited by 61
“…to allow mirroring of the conditions of the The idea of using a twin model can be dated back to NASA’s Apollo program in the 1970s, where two identical space vehicles were built to allow mirroring of the conditions of the space vehicle during the mission [63]. space vehicle during the mission [63].”
MethodA Framework for Prefabricated Component Hoisting Management Systems Based on Digital Twin Technology
Zhao, Y., Cao, C., & Liu, Z.-S. (2022) · Buildings · doi:10.3390/buildings12030276 · Cited by 68
“The concept of “twin” originated from National Aeronautics and Space Administration (NASA), which predicted the flight status of the air vehicle through the accurate simulation test of the “twin” aircraft on the ground [24].”
BackgroundDigital Twin Modeling Enabled Machine Tool Intelligence: A Review
Zhang, L., Liu, J., & Zhuang, C. (2024) · Chinese Journal of Mechanical Engineering · doi:10.1186/s10033-024-01036-2 · Cited by 82
“The concept of twins first appeared in the National Aeronautics and Space Administration (NASA) [13].”
BackgroundWang, T., Li, J., Kong, Z., Liu, X., Snoussi, H., & Lv, H. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.07.011 · Cited by 73
Enhancing Digital Twins through Reinforcement Learning
Cronrath, C., Aderiani, A. R., & Lennartson, B. (2019) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/coase.2019.8842888 · Cited by 77
“The Digital Twin is seen as a core enabler for smart and autonomous manufacturing systems [1].”
BackgroundNext Generation Digital Twin: an Ecosystem for Mechatronic Systems?
Rosen, R., Fischer, J.-G., & Boschert, S. (2019) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2019.11.685 · Cited by 66
Self-citationShop Floor Digital Twin in Smart Manufacturing: A Systematic Literature Review
Corallo, A., Vecchio, V. D., Lezzi, M., & Morciano, P. (2021) · Sustainability · doi:10.3390/su132312987 · Cited by 78
Digital twin for personalized medicine development
Saratkar, S., Langote, M., Kumar, P., Gote, P. M., Weerarathna, I. N., & Mishra, G. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1583466 · Cited by 88
“Because it provides previously unheard-of insights into intricate systems and processes, digital twin technology is transforming industries worldwide (69).”
Digital Twins for Construction Assets Using BIM Standard Specifications
El-Din, M. N., Pereira, P. F., Martins, J. P., & Ramos, N. (2022) · Buildings · doi:10.3390/buildings12122155 · Cited by 97
Dai, S. L., Zhao, G. L., Yu, Y., Zheng, P., Bao, Q., & Wang, W. (2021) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2021.102173 · Cited by 77
A Digital Twin-based scheduling framework including Equipment Health Index and Genetic Algorithms
Negri, E., Ardakani, H. D., Cattaneo, L., Singh, J., Macchi, M., & Lee, J. (2019) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2019.10.024 · Cited by 63
“When it moved to the industrial engineering, it took a role of overall lifecycle monitoring of products (Abramovici, Göbel, and Neges 2015) or production systems (Rosen et al. 2015), of which the prediction of failures and in general the equipment health monitoring are a part of (Liu et al. 2015).”
BackgroundInfluentialGeometrical Variations Management 4.0: towards next Generation Geometry Assurance
Schleich, B., Wärmefjord, K., Söderberg, R., & Wartzack, S. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.04.078 · Cited by 63
“In this context, the digital twin often refers to a comprehensive physical and functional description of a component, product or system, which includes more or less all information which could be useful in the current and subsequent lifecycle phases [27, 28].”
BackgroundA comprehensive survey of digital twins: Applications, technologies and security challenges
Jeremiah, S. R., Azzaoui, A. E., Xiong, N. N., & Park, J. H. (2024) · Journal of Systems Architecture · doi:10.1016/j.sysarc.2024.103120 · Cited by 77
He, X., Ai, Q., Wang, J.-B., Tao, F., Pan, B., Qiu, R., & Yang, B. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3203823 · Cited by 62
Digital twins for cutting processes
Bergs, T., Biermann, D., Erkorkmaz, K., & M'saoubi, R. (2023) · CIRP annals · doi:10.1016/j.cirp.2023.05.006 · Cited by 62
A unified framework for digital twin development in manufacturing
Latsou, C., Ariansyah, D., Salome, L., Erkoyuncu, J. A., Sibson, J., & Dunville, J. (2024) · Advanced Engineering Informatics · doi:10.1016/j.aei.2024.102567 · Cited by 70
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
Synchronizing physical and digital factory: benefits and technical challenges
Modoni, G. E., Caldarola, E. G., Sacco, M., & Terkaj, W. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.02.125 · Cited by 62
Digital Twins for Clinical and Operational Decision-Making: Scoping Review
Riahi, V., Diouf, I., Khanna, S., Boyle, J., & Hassanzadeh, H. (2024) · Journal of Medical Internet Research · doi:10.2196/55015 · Cited by 63
“DTs have their roots in the field of engineering [3-6] but are quickly expanding to a wide range of applications, such as city planning [7-9], energy [10,11], retail [12,13], and health care [14,15].”
Digital twin monitoring and simulation integrated platform for reconfigurable manufacturing systems
Leng, B., Gao, S., Xia, T., Pan, E., Seidelmann, J., Wang, H., & Xi, L. (2023) · Advanced Engineering Informatics · doi:10.1016/j.aei.2023.102141 · Cited by 64
Wang, J., Li, X., Wang, P., & Liu, Q. (2022) · Technology Analysis and Strategic Management · doi:10.1080/09537325.2022.2026320 · Cited by 77
“Rosen et al. (2015) discussed that the importance of autonomy and digital twins for the future of manufacturing.”
BackgroundAlimam, H., Mazzuto, G., Tozzi, N., Ciarapica, F. E., & Bevilacqua, M. (2023) · Journal of King Saud University: Computer and Information Sciences · doi:10.1016/j.jksuci.2023.101846 · Cited by 60
When is a simulation a digital twin? A systematic literature review
Wooley, A., Silva, D. F., & Bitencourt, J. (2023) · Manufacturing Letters · doi:10.1016/j.mfglet.2023.08.014 · Cited by 67
Bi-level dynamic scheduling architecture based on service unit digital twin agents
Zhang, J., Deng, T., Jiang, H., Chen, H., Qin, S., & Ding, G. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.05.007 · Cited by 71
Marine energy digitalization digital twin's approaches
Nezhad, M. M., Neshat, M., Sylaios, G., & Garcia, D. A. (2024) · Renewable & Sustainable Energy Reviews · doi:10.1016/j.rser.2023.114065 · Cited by 60
A Five-Step Approach to Planning Data-Driven Digital Twins for Discrete Manufacturing Systems
Resman, M., Protner, J., Šimic, M., & Herakovič, N. (2021) · Applied Sciences · doi:10.3390/app11083639 · Cited by 59
“It defines the digital twin as an ultra-realistic, high-scaling simulation model that uses the best-available physical models, with data being collected throughout the whole lifecycle of the system [13,14].”
MethodDigital Twins: Properties, Software Frameworks, and Application Scenarios
Minerva, R., & Crespi, N. (2021) · IT Professional · doi:10.1109/mitp.2020.2982896 · Cited by 59
Internet of Things Ontology for Digital Twin in Cyber Physical Systems
Steinmetz, C., Rettberg, A., Ribeiro, F., Schroeder, G. N., & Pereira, C. (2018) · Brazilian Symposium on Computing System Engineering · doi:10.1109/sbesc.2018.00030 · Cited by 59
“With the Cyber Physical System concept, the Digital Twin can be understood as a virtual representation of the physical product, a digital shadow that contains all information and knowledge of it [16].”
MethodApplication Status and Prospect of Digital Twin for On-Orbit Spacecraft
Yang, W., Zheng, Y., & Li, S. (2021) · IEEE Access · doi:10.1109/access.2021.3100683 · Cited by 58
Towards adaptive digital twins architecture
Ogunsakin, R., Mehandjiev, N., & Marín, C. A. (2023) · Computers in Industry · doi:10.1016/j.compind.2023.103920 · Cited by 73
Greenhouse industry 4.0 – digital twin technology for commercial greenhouses
Howard, D. A., Ma, Z., Veje, C., Clausen, A., Aaslyng, J. M., & Jørgensen, B. N. (2021) · Energy Informatics · doi:10.1186/s42162-021-00161-9 · Cited by 58
“The three main disciplines of production systems simulated in a DT are production planning and control (Rosen et al. 2015), maintenance (D ’ Addona et al. 2017), and lay-out planning (Uhlemann et al. 2017).”
BackgroundDemonstration and evaluation of a digital twin-based virtual factory
Yildiz, E., Møller, C., & Bilberg, A. (2021) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-06825-w · Cited by 78
Application and Development Prospect of Digital Twin Technology in Aerospace
Z, H., & Wang, L. (2020) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2021.04.165 · Cited by 58
Stakeholders collaborations, challenges and emerging concepts in digital twin ecosystems
Tripathi, N., Hietala, H., Xu, Y.-Q., & Liyanage, R. (2024) · Information and Software Technology · doi:10.1016/j.infsof.2024.107424 · Cited by 57
Kannapinn, M., Pham, M. K., & Schäfer, M. (2022) · Innovative Food Science & Emerging Technologies · doi:10.1016/j.ifset.2022.103143 · Cited by 57
“Autonomous processes with artificial intelligence are among the next disruptive technological trends, and Digital Twins might act as enablers (Rosen et al., 2015).”
BackgroundA twin data and knowledge-driven intelligent process planning framework of aviation parts
Li, J., Zhou, G., & Zhang, C. (2021) · International Journal of Production Research · doi:10.1080/00207543.2021.1951869 · Cited by 65
Li, X., Wang, L., Chuanjun, Z., & Liu, Z. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.08.003 · Cited by 68
Krupitzer, C., Noack, T., & Borsum, C. (2022) · Processes · doi:10.3390/pr10091781 · Cited by 78
Opportunities and Challenges to Develop Digital Twins for Subsea Pipelines
Chen, B.-Q., Videiro, P. M., & Soares, C. G. (2022) · Journal of Marine Science and Engineering · doi:10.3390/jmse10060739 · Cited by 66
“The idea to use a twin model can be dated back to the 1970s when two identical space vehicles were built in NASA’s Apollo program to allow for mirroring of the conditions of the space vehicle [6].”
MethodMaintenance optimization for a multi-unit system with digital twin simulation
Savolainen, J., & Urbani, M. (2021) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-021-01740-z · Cited by 56
RECLAIM: Toward a New Era of Refurbishment and Remanufacturing of Industrial Equipment
Zacharaki, A., Vafeiadis, T., Kolokas, N., Vaxevani, A., Xu, Y.-C., Peschl, M., Ioannidis, D., & Tzovaras, D. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2020.570562 · Cited by 56
Zhang, M., Zuo, Y. N., & Tao, F. (2018) · IEEE International Conference on Networking, Sensing and Control (ICNSC) · doi:10.1109/icnsc.2018.8361272 · Cited by 89
“propose that the DT makes all models and data available in a consistent environment in the future manufacturing [19].”
BackgroundShifting value stream patterns along the product lifecycle with digital twins
Schleich, B., Dittrich, M., Clausmeyer, T., Damgrave, R., Erkoyuncu, J., Haefner, B., Lange, J. D., Plakhotnik, D., Scheidel, W., & Wuest, T. (2019) · Procedia CIRP · doi:10.1016/j.procir.2020.01.049 · Cited by 56
5-Dimensional Definition for a Manufacturing Digital Twin
Bazaz, S. M., Lohtander, M., & Varis, J. (2019) · Procedia Manufacturing · doi:10.1016/j.promfg.2020.01.107 · Cited by 56
Talkhestani, B. A., Jazdi, N., Schlögl, W., & Weyrich, M. (2018) · Procedia CIRP · doi:10.1016/j.procir.2017.12.168 · Cited by 56
Santana, A., Afonso, P., Zanin, A., & Wernke, R. (2017) · doi:10.1016/j.promfg.2017.09.193 · Cited by 56
Towards the Development of Digital Twins for the Bio-manufacturing Industry.
Gargalo, C. L., Heras, S. C. D. L., Jones, M., Udugama, I. A., Mansouri, S., Krühne, U., & Gernaey, K. (2020) · Advances in Biochemical Engineering/Biotechnology · doi:10.1007/10_2020_142 · Cited by 55
Readiness of Enterprises in Czech Republic to Implement Industry 4.0: Index of Industry 4.0
Vrchota, J., & Pech, M. (2019) · Applied Sciences · doi:10.3390/app9245405 · Cited by 68
“The concept of using “twins” comes from the Apollo NASA (National Aeronautics and Space Administration) program; later, it was used also in aviation, such as the “Iron Bird” [96].”
MethodTransfer Learning as an Enabler of the Intelligent Digital Twin
Maschler, B., Braun, D., Jazdi, N., & Weyrich, M. (2020) · Procedia CIRP · doi:10.1016/j.procir.2021.05.020 · Cited by 54
“The DT can be used for support during the hole lifecycle of a plant starting from its design over engineering, operation up to optimization as long as the Digital Twin is continuously adapted to the real asset [13].”
MethodCao, X. Z., Zhao, G. L., & Xiao, W. (2020) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1177/0954405420937869 · Cited by 66
Digital Twins as the Next Phase of Cyber-Physical Systems in Construction
Kan, C., & Anumba, C. (2019) · Computing in Civil Engineering · doi:10.1061/9780784482438.033 · Cited by 54
The digital twin in neuroscience: from theory to tailored therapy
Fekonja, L. S., Schenk, R., Schröder, E., Tomasello, R., Tomšič, S., & Picht, T. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1454856 · Cited by 66
“Such systems are already successfully deployed in manufacturing (Rosen et al., 2015), design (Helbing and Sánchez-Vaquerizo, 2023), architecture (Al-Sehrawy and Kumar, 2021) or city planning (Ravid et al., 2022) among others.”
BackgroundA Wasserstein generative digital twin model in health monitoring of rotating machines
Hu, W., Wang, T., & Chu, F. (2022) · Computers in Industry · doi:10.1016/j.compind.2022.103807 · Cited by 55
Design and research of digital twin machine tool simulation and monitoring system
Guo, M., Fang, X., Hu, Z., & Li, Q. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-09613-2 · Cited by 57
“During the running process, the twin model is always highly consistent with the entity, so that the twin has the ability to accurately reflect the running state of the physical entity, thus realizing the effective monitoring of the physical entity[8].”
MethodContext awareness in process monitoring of additive manufacturing using a digital twin
Reisch, R. T., Hauser, T., Lutz, B., Tsakpinis, A., Winter, D., Kamps, T., & Knoll, A. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-08636-5 · Cited by 60
“For the latter, continuous and dynamic changes in the physical space by means of DTs could be a suitable solution by enabling prescriptive analytic methods [35].”
BackgroundDigital Twin for Cybersecurity Incident Prediction
Pokhrel, A., Katta, V., & Colomo‐Palacios, R. (2020) · International Conference on Software Engineering · doi:10.1145/3387940.3392199 · Cited by 44
“…such as CPS, IoT and cloud computing which are not only helpful in the development and design stages but also in the production stages to check that production is running smoothly, detect wear and tear without needing to halt production or predict component failure and other disruptions [2] [35].”
BackgroundInfluentialVirtual Factory: Digital Twin Based Integrated Factory Simulations
Yildiz, E., Møller, C., & Bilberg, A. (2020) · Procedia CIRP · doi:10.1016/j.procir.2020.04.043 · Cited by 74
Frazzon, E., Agostino, Í., Broda, E., & Freitag, M. (2020) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2020.04.008 · Cited by 53
A Primer on the Factories of the Future
Anumbe, N. C., Saidy, C., & Harik, R. (2022) · Sensors · doi:10.3390/s22155834 · Cited by 68
Atikokan Digital Twin: Machine learning in a biomass energy system
Spinti, J., Smith, P., & Smith, S. T. (2022) · Applied Energy · doi:10.1016/j.apenergy.2021.118436 · Cited by 52
“Nevertheless, there is general consensus that a digital twin is a method to improve the efficiency of physical assets or processes [4,5,7,8,9].”
Industrial Robot Control by Means of Gestures and Voice Commands in Off-Line and On-Line Mode
Kaczmarek, W., Panasiuk, J., Borys, S., & Banach, P. (2020) · Italian National Conference on Sensors · doi:10.3390/s20216358 · Cited by 52
Towards Semantically Enhanced Digital Twins
Kharlamov, E., Martin-Recuerda, F., Perry, B., Cameron, D., Fjellheim, R., & Waaler, A. (2018) · 2018 IEEE International Conference on Big Data (Big Data) · doi:10.1109/bigdata.2018.8622503 · Cited by 52
Abanda, F. H., Jian, N., Adukpo, S. E., Tuhaise, V. V., & Manjia, M. B. (2024) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-023-02301-2 · Cited by 52
Cui, Z., Yang, X., Yue, J., Liu, X., Tao, W., Xia, Q., & Wu, C. (2023) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2023.07.016 · Cited by 54
Digital Twins for High-Tech Machining Applications—A Model-Based Analytics-Ready Approach
Hänel, A., Seidel, A., Frieß, U., Teicher, U., Wiemer, H., Wang, D.-Q., Wenkler, E., Penter, L., Hellmich, A., & Ihlenfeldt, S. (2021) · Journal of Manufacturing and Materials Processing · doi:10.3390/jmmp5030080 · Cited by 51
“0 principles in the near future and the advancement of globalization, production processes will have to change fundamentally [3].”
BackgroundDigital twin-enabled smart industrial systems: a bibliometric review
Ciano, M. P., Pozzi, R., Rossi, T., & Strozzi, F. (2020) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2020.1852600 · Cited by 63
“Besides, industry 4.0 and digital twin can be linked in reference to the flexibility demand of the newest automation systems (Rosen et al. 2015).”
BackgroundMethodInfluentialDigital Twin Applications : A first systemization of their dimensions
Uhlenkamp, J.-F., Hribernik, K., Wellsandt, S., & Thoben, K. (2019) · IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) · doi:10.1109/ice.2019.8792579 · Cited by 81
“Subsequent papers widened the area of applications by applying the concept to products in general and to other life cycle processes, especially the design and production [6].”
BackgroundMethodThe 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
Working mode in aircraft manufacturing based on digital coordination model
Guo, F., Zou, F., Liu, J., & Wang, Z. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-018-2048-0 · Cited by 51
“Lockheed Martin Company [31] has created a digital thread working pattern that collects heterogeneous dynamic data from physical assembly space.”
BackgroundAgent-based manufacturing — review and expert evaluation
Pulikottil, T., Estrada-Jimenez, L. A., Rehman, H. U., Mo, F., Nikghadam-Hojjati, S., & Barata, J. (2023) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-023-11517-8 · Cited by 50
Abrazeh, S., Mohseni, S., Zeitouni, M. J., Parvaresh, A., Fathollahi, A., Gheisarnejad, M., & Khooban, M. (2023) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2022.3168507 · Cited by 50
“To overcome the issue of control procedure, among numerous others, digitization of the physical domain can be one of the keys [40], [41].”
BackgroundDigital Technologies in Offsite and Prefabricated Construction: Theories and Applications
Cheng, Z., Tang, S.-X., Liu, H.-X., & Lei, Z. (2023) · Buildings · doi:10.3390/buildings13010163 · Cited by 50
Alibrandi, U. (2022) · ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A Civil Engineering · doi:10.1061/ajrua6.0001238 · Cited by 73
Evolutionary digital twin: A new approach for intelligent industrial product development
Lin, T. Y., Jia, Z., Yang, C., Xiao, Y., Lan, S., Shi, G., Zeng, B., & Li, H. (2020) · Advanced Engineering Informatics · doi:10.1016/j.aei.2020.101209 · Cited by 56
Metadata
- Authors
- Rosen, R., von Wichert, G., Lo, G., & Bettenhausen, K. D.
- Affiliations
- Siemens (Germany) (DE)
- Siemens (United States) (US)
- Corresponding author
- Rosen, Roland
- Lo, George
- Bettenhausen, Kurt D.
- Venue
- IFAC-PapersOnLine
- Publisher
- Elsevier BV
- Published
- 2015
- Volume
- 48
- Issue
- 3
- Pages
- 567-572
- ISSN
- 2405-8963 (ISSN-L)
- OpenAlex
- W2346505350
- Cited by
- 1,474
- References
- 2
- Citations by year
- 2026: 113 · 2025: 163 · 2024: 202 · 2023: 226 · 2022: 200 · 2021: 183 · 2020: 138 · 2019: 142 · 2018: 73 · 2017: 22 · 2016: 11
- FWCI
- 61.97
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IFAC-PapersOnLine (publishedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- Industry 4.0, digital twin, future of manufacturing, future of work, industrial automation
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