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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 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
“respond to state changes even during an ongoing operation [27].”
BackgroundMethodDigital 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
“(Kuhn 2017; Boschert, Rosen 2016; Rosen et al. 2015) In terms of manufacturing, (Garetti et al. 2012) has the following definition for a Digital Twin: “The DT consists of a virtual representation of a production system that is able to run on different simulation disciplines that is characterized by…”
BackgroundInfluentialCharacterising 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
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InfluentialDigital 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
“The increasing digitalization of manufacturing is opening up opportunities for smart manufacturing [6].”
BackgroundMethodInfluentialReview 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 2,075
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
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
“Digital Twin has gained significant impetus as a breakthrough technological development that has the potential to transform the landscape of manufacturing today and tomorrow [1].”
BackgroundA survey on digital twin: definitions, characteristics, applications, and design implications
Barricelli, B. R., Casiraghi, E., & Fogli, D. (2019) · IEEE Access · doi:10.1109/access.2019.2953499 · Cited by 1,480
“[53] seems referring to the DT as a realistic model or simulation with the ability of continuously communicating with its physical twin, which is a too simplistic way for describing it.”
BackgroundMethodResultInfluentialShaping 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
Tao, F., Qi, Q., Wang, L., & Nee, A. Y. C. (2019) · Engineering · doi:10.1016/j.eng.2019.01.014 · Cited by 1,589
“The virtual models and physical processes of a DT co-evolve over the life-cycle of the product or system [40].”
BackgroundDigital Twin—The Simulation Aspect
Boschert, S., & Rosen, R. (2016) · Mechatronic Futures · doi:10.1007/978-3-319-32156-1_5 · Cited by 1,158
Self-citationDigital twin-driven product design framework
Tao, F., Sui, F., Liu, A., Qi, Q., Zhang, M., Song, B., Guo, Z., Lu, S. C.-Y., & Nee, A. Y. C. (2018) · International Journal of Production Research · doi:10.1080/00207543.2018.1443229 · Cited by 1,290
Digital twin: origin to future
Singh, M., Fuenmayor, E., Hinchy, E., Qiao, Y., Murray, N., & Devine, D. (2021) · Applied System Innovation · doi:10.3390/asi4020036 · Cited by 1,038
“This level of detail allows DT simulation and prediction tools to be more reliable when presented with a set of alternative actions or scenarios [21].”
BackgroundMethodInfluentialReview of digital twin applications in manufacturing
Cimino, C., Negri, E., & Fumagalli, L. (2019) · Computers in Industry · doi:10.1016/j.compind.2019.103130 · Cited by 874
Digital twin paradigm: A systematic literature review
Semeraro, C., Lezoche, M., Panetto, H., & Dassisti, M. (2021) · Computers in Industry · doi:10.1016/j.compind.2021.103469 · Cited by 1,129
“From the simulation point of view, the digital twin represents a new wave in modelling and simulation (Rosen et al., 2015).”
BackgroundMethodInfluentialDigital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models
Minerva, R., Lee, G. M., & Crespi, N. (2020) · Proceedings of the IEEE · doi:10.1109/jproc.2020.2998530 · Cited by 812
“It also provides the ability to manage the DTs and to simulate their future behavior.”
BackgroundInfluentialDigital twin application in the construction industry: A literature review
Opoku, D.-G. J., Perera, S., Osei-Kyei, R., & Rashidi, M. (2021) · Journal of Building Engineering · doi:10.1016/j.jobe.2021.102726 · Cited by 753
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
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
Rathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., & Bakiras, S. (2021) · IEEE Access · doi:10.1109/access.2021.3060863 · Cited by 616
“In this way, Rosen et al. [33] emphasizes the use of digital twinning in manufacturing.”
Construction with digital twin information systems
Sacks, R., Brilakis, I., Pikas, E., Xie, H. S., & Girolami, M. (2020) · Data-Centric Engineering · doi:10.1017/dce.2020.16 · Cited by 609
“…and virtual counterparts, enabled by the development of advanced sensing (e.g., computer vision), internet of things (e.g., interconnected assets), high-speed networking (e.g., 5G internet), and advanced analytics (e.g., machine learning) technologies (Rosen et al., 2015; Gerber et al., 2019).”
BackgroundInfluentialDigital Twin for maintenance: A literature review
Errandonea, I., Beltrán, S., & Arrizabalaga, S. (2020) · Computers in Industry · doi:10.1016/j.compind.2020.103316 · Cited by 819
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
“• The analysis of the debate initiated in 2013 [40] and further explored in [54], whether DT covers the entire product lifecycle [62, 23] or just the product [66, 1].”
BackgroundInfluentialZhuang, C., Liu, J., & Xiong, H. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-018-1617-6 · Cited by 700
“From this point of view, the twin was referred to as a prototype that mirrored the real operating condition for the simulation of real-time behavior [19].”
BackgroundHaag, S., & Anderl, R. (2018) · Manufacturing Letters · doi:10.1016/j.mfglet.2018.02.006 · Cited by 559
Digital Twin as a Service (DTaaS) in Industry 4.0: An Architecture Reference Model
Aheleroff, S., Xu, X. W., Zhong, R. Y., & Lu, Y. (2020) · Advanced Engineering Informatics · doi:10.1016/j.aei.2020.101225 · Cited by 680
Digital Twin for rotating machinery fault diagnosis in smart manufacturing
Wang, J., Ye, L., Gao, R. X., Li, C., & Zhang, L. (2019) · International Journal of Production Research · doi:10.1080/00207543.2018.1552032 · Cited by 552
“The concept of “twin” is originally derived from NASA’s Apollo Project when the aircraft’s twin body is a real physical system (Rosen et al. 2015).”
BackgroundMethodA 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
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
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
“It is also a possible direction for future manufacturing workshops, and it will raise the next wave of simulation, modeling and optimization (Rosen et al. 2015).”
BackgroundZhang, H., Liu, Q., Chen, X., Zhang, D., & Leng, J. (2017) · IEEE Access · doi:10.1109/access.2017.2766453 · Cited by 471
“Two typical understandings/areas of the digital twin can be observed in industrial practice [31].”
BackgroundDigital twin and its implementations in the civil engineering sector
Jiang, F., Ma, L., Broyd, T., & Chen, K. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103838 · Cited by 531
Ding, K., Chan, F. T. S., Zhang, X., Zhou, G., & Zhang, F. (2019) · International Journal of Production Research · doi:10.1080/00207543.2019.1566661 · Cited by 456
“As to autonomous manufacturing, machines and other resources should be smart, they need to know their capabilities and states both historically and currently (Rosen et al. 2015).”
BackgroundA Digital-Twin-Assisted Fault Diagnosis Using Deep Transfer Learning
Xu, Y., Sun, Y., Liu, X., & Zheng, Y. (2019) · IEEE Access · doi:10.1109/access.2018.2890566 · Cited by 533
“It simulates and maps the entire product life cycle through ultra-realistic and dynamically optimized simulation models [4], thus reducing the cost of design and maintenance, while enhancing the efficiency and quality of manufacturing.”
A survey on AI-driven digital twins in Industry 4.0: smart manufacturing and advanced robotics
Huang, Z., Shen, Y., Li, J., Fey, M., & Brecher, C. (2021) · Sensors · doi:10.3390/s21196340 · Cited by 418
“The widespread application of simulation models and ubiquitous connectivity provide a solid foundation for building digital production twin throughout the product lifecycle, which is considered a key enabler for future manufacturing transformation and upgrading in the era of big data [1,31,32].”
BackgroundDigital 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
Human–Cyber–Physical Systems (HCPSs) in the Context of New-Generation Intelligent Manufacturing
Zhou, J., Zhou, Y., Wang, B., & Zang, J. (2019) · Engineering · doi:10.1016/j.eng.2019.07.015 · Cited by 518
Yu, W., Patros, P., Young, B., Klinac, E., & Walmsley, T. (2022) · Renewable & Sustainable Energy Reviews · doi:10.1016/j.rser.2022.112407 · Cited by 361
Kamble, S., Gunasekaran, A., Parekh, H., Mani, V., Belhadi, A., & Sharma, R. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121448 · Cited by 414
Digital twin-based WEEE recycling, recovery and remanufacturing in the background of Industry 4.0
Wang, X. V., & Wang, L. (2019) · International Journal of Production Research · doi:10.1080/00207543.2018.1497819 · Cited by 330
“New Industry 4.0 services were also suggested based on the digital twin, to generate insights that can be utilised for the future car design and optimisation (Rüßmann et al. 2015).”
BackgroundInfluentialDeep learning in drug discovery: an integrative review and future challenges
Askr, H., Elgeldawi, E., Ella, H. A., Elshaier, Y. A. M. M., Gomaa, M. M., & Hassanien, A. E. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10306-1 · Cited by 428
“The idea of making a "twin" of a process or a product returned to NASA’s Apollo project in the late 1960s (Rosen et al. 2015; Mayani et al. 2018; Schleich et al. 2017), when it assembled two identical space spacecraft.”
BackgroundWagg, D., Worden, K., Barthorpe, R. J., & Gardner, P. A. (2020) · ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering · doi:10.1115/1.4046739 · Cited by 382
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
“…can more accurately reflect the real state and behavior of physical devices in the physical space, so that they can detect the function and performance of physical devices in the virtual space, achieve intelligent perception and interconnection, and efficient data transmission and integration [32].”
Applications of Digital Twin across Industries: A Review
Singh, M., Srivastava, R., Fuenmayor, E. A., Kuts, V., Qiao, Y., Murray, N., & Devine, D. M. (2022) · Applied Sciences · doi:10.3390/app12115727 · Cited by 376
“…support by means of a detailed diagnosis, (ii) maintenance by evaluating and analyzing machine conditions, identifying any changes in the production system and its effects, and taking anticipatory maintenance, and (iii) layout planning by evaluating the production system continuously [11,65].”
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
An architecture of an intelligent digital twin in a cyber-physical production system
Ashtari Talkhestani, B., Jung, T., Lindemann, B., Sahlab, N., Jazdi, N., Schloegl, W., & Weyrich, M. (2019) · at - Automatisierungstechnik · doi:10.1515/auto-2019-0039 · Cited by 300
“During the mission, theground-basedmodelwasused to simulate alternatives, where the available flight datawas used to reflect the flight conditions as accurately as possible and to assist astronauts in orbit in critical situations [6, 7].”
MethodA Digital Twin Based Industrial Automation and Control System Security Architecture
Gehrmann, C., & Gunnarsson, M. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2938885 · Cited by 377
“) in a production system allowing advanced simulations of a complete manufacturing system and the units involved in an autonomous system [15].”
BackgroundMobility Digital Twin: Concept, Architecture, Case Study, and Future Challenges
Wang, Z.-R., Gupta, R., Han, K., Wang, H., Ganlath, A., Ammar, N., & Tiwari, P. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3156028 · Cited by 285
“Along with its rapid development in different domains during the past decade, including aeronautics and space [4], [7], robotics [8], [9], manufacturing [10], [11], and informatics [12], the Digital Twin also has a huge potential in the transportation domain.”
BackgroundUrbina 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
“…to implement Digital Twins is one of the benefits of data collection: large amounts of data enable the construction of simulations of different scenarios, which can be useful to make predictions about behaviors or failures, according to the latest data obtained from the physical twin [5,28].”
BackgroundMethodPerno, M., Hvam, L., & Haug, A. (2021) · Computers in Industry · doi:10.1016/j.compind.2021.103558 · Cited by 328
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
Santhi, A. R., & Muthuswamy, P. (2023) · International Journal on Interactive Design and Manufacturing (IJIDeM) · doi:10.1007/s12008-023-01217-8 · Cited by 438
Industry 4.0 and the New Simulation Modelling Paradigm
Rodič, B. (2017) · Organizacija · doi:10.1515/orga-2017-0017 · Cited by 255
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
“The concept of creating a “twin” of a process or a product can be traced back to the late 1960s when NASA ensembled two identical space vehicles for its Apollo project [20–22].”
BackgroundVisualisation of the Digital Twin data in manufacturing by using Augmented Reality
Zhu, Z.-X., Liu, C., & Xu, X. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.03.223 · Cited by 241
Microgrid Digital Twins: Concepts, Applications, and Future Trends
Bazmohammadi, N., Madary, A., Vasquez, J. C., Mohammadi, H. B., Khan, B., Wu, Y., & Guerrero, J. M. (2022) · IEEE Access · doi:10.1109/access.2021.3138990 · Cited by 233
Is Human Digital Twin possible?
Shengli, W. (2021) · Computer Methods and Programs in Biomedicine Update · doi:10.1016/j.cmpbup.2021.100014 · Cited by 233
Agostinelli, S., Cumo, F., Guidi, G., & Tomazzoli, C. (2021) · Energies · doi:10.3390/en14082338 · Cited by 314
“…suitable deployment data-model based on urban intelligence systems, pervasive computing, communication, big data management technologies, and artificial intelligence (AI), leading to a strong evolution in the management of urban environments as well as in the quality of life in smart cities [7,8].”
BackgroundSmart contracts on the blockchain - A bibliometric analysis and reviewPreprint
Ante, L. (2020) · Telematics and informatics · doi:10.2139/ssrn.3576393 · Cited by 227
Scaling digital twins from the artisanal to the industrial
Niederer, S., Sacks, M. S., Girolami, M., & Willcox, K. E. (2021) · Nature Computational Science · doi:10.1038/s43588-021-00072-5 · Cited by 231
“Digital twins originated in aerospace engineering, with many people pointing to the Apollo program as the first place where the idea was put in practice, where simulators on the ground mirrored the systems being put into space 10 .”
BackgroundWeb-based digital twin modeling and remote control of cyber-physical production systems
Liu, C., Jiang, P., & Jiang, W. (2020) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2020.101956 · Cited by 223
Modeling of Cloud-Based Digital Twins for Smart Manufacturing with MT Connect
Hu, L., Nguyen, N.-T., Tao, W., Leu, M. C., Liu, X. F., Shahriar, M. R., & Al Sunny, S. M. N. (2018) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.07.155 · Cited by 219
Choi, S., Park, K.-B., Roh, D., Lee, J. Y., Mohammed, M., Ghasemi, Y., & Jeong, H. (2022) · Robotics Comput. Integr. Manuf. · doi:10.1016/j.rcim.2021.102258 · Cited by 218
Alexopoulos, K., Nikolakis, N., & Chryssolouris, G. (2020) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2020.1747642 · Cited by 324
“Rosen et al. (2015) argue how DT implementations could increase the autonomy of manufacturing systems by combining the real data with simulation models from design, thus allowing the DT to predict future states based on the realistic data.”
MethodExploring the role of digital twin for asset lifecycle management
Macchi, M., Roda, I., Negri, E., & Fumagalli, L. (2018) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2018.08.415 · Cited by 216
“When adopted in manufacturing, the DT has taken a new objective: to simulate the complex behaviour of production systems, also including external factors, as human presence and technical constraints (Rosen et al. 2015; Gabor et al. 2016; Arisoy et al. 2017).”
BackgroundMethodDigital-Twin-Based Job Shop Scheduling Toward Smart Manufacturing
Fang, Y., Peng, C., Lou, P., Zhou, Z., Hu, J., & Yan, J. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2938572 · Cited by 281
“[27]–[29] bring a chance to reduce the gap.”
BackgroundA Methodology for Digital Twin Modeling and Deployment for Industry 4.0
Schroeder, G. N., Steinmetz, C., Rodrigues, R. N., Henriques, R. V. B., Rettberg, A., & Pereira, C. E. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2020.3032444 · Cited by 213
“However, with the advent of CPSs, the DT appears as a virtual representation of the physical product, a digital shadow that contains all its information and knowledge [15].”
BackgroundThe concept of digital twin and digital shadow in manufacturing
Bergs, T., Gierlings, S., Auerbach, T., Klink, A., Schraknepper, D., & Augspurger, T. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.02.010 · Cited by 212
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
“” Roland Rosen [20] 2015 A “ new wave in modeling, simulation, and optimization technology, which provides a big set of all digital artifacts.”
BackgroundFuture Modeling and Simulation of CPS-based Factories: an Example from the Automotive Industry
Weyer, S., Meyer, T. J., Ohmer, M., Gorecky, D., & Zühlke, D. (2016) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2016.12.168 · Cited by 210
Control Co‐Design: An engineering game changer
Garcia-Sanz, M. (2019) · Advanced Control for Applications: Engineering and Industrial Systems · doi:10.1002/adc2.18 · Cited by 209
A Cyber-Physical Machine Tools Platform using OPC UA and MTConnect
Liu, C., Vengayil, H., Lu, Y.-Q., & Xu, X. (2019) · Journal of manufacturing systems · doi:10.1016/j.jmsy.2019.04.006 · Cited by 209
“Nowadays, digital twin is considered as a key enabler for Product Lifecycle Management (PLM), CPPS and Smart Factory in the era of Industry 4.0 [19–21].”
InfluentialThe Convergence of Digital Twin, IoT, and Machine Learning: Transforming Data into Action
Kaur, M., Mishra, V., & Maheshwari, P. (2019) · Internet of Things · doi:10.1007/978-3-030-18732-3_1 · Cited by 209
Jia, W., Wang, W., & Zhang, Z. (2022) · Advanced Engineering Informatics · doi:10.1016/j.aei.2022.101706 · Cited by 256
Innovations in digital modelling for next generation manufacturing system design
Stark, R., Kind, S., & Neumeyer, S. (2017) · CIRP Annals · doi:10.1016/j.cirp.2017.04.045 · Cited by 208
Systematic review of digital twin technology and applications
Yao, J.-F., Yang, Y., Wang, X.-C., & Zhang, X.-P. (2023) · Visual Computing for Industry, Biomedicine, and Art · doi:10.1186/s42492-023-00137-4 · Cited by 201
“DT was defined from a linkage-focused perspective by Rosen et al. [11] who argued that a DT not only comprises a large collection of digital products but also should possess a good architecture so that all components are linked.”
BackgroundMethodDigital twin in manufacturing: conceptual framework and case studies
Onaji, I., Tiwari, D., Soulatiantork, P., Song, B., & Tiwari, A. (2022) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2022.2027014 · Cited by 298
“As shown in Figure 9, the proposed digital twin framework enables the inclusion of both operational and environmental data for analytics (Rosen et al. 2015; Catapult 2018).”
BackgroundInfluentialVillalonga, A., Negri, E., Biscardo, G., Castaño, F., Haber, R., Fumagalli, L., & Macchi, M. (2021) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2021.04.008 · Cited by 195
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
“0 implies their importance for modern factories [53,54].”
BackgroundModular 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
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
“The digital twin also aims to ensure the e ffi ciency of a manufacturing site based on interconnection and interaction via the real-world IIoT network (Silveira, Borenstein, and Fogliatto 2001; Rosen et al. 2015; Kühn 2006; Gabor et al. 2016).”
MethodReal-time machining data application and service based on IMT digital twin
Tong, X., Liu, Q., Pi, S., & Xiao, Y. (2019) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01500-0 · Cited by 192
Developing design principles for the digitalisation of purchasing and supply management
Srai, J. S., & Lorentz, H. (2018) · Journal of Purchasing and Supply Management · doi:10.1016/j.pursup.2018.07.001 · Cited by 300
Potential and limitations of digital twins to achieve the Sustainable Development Goals
Tzachor, A., Sabri, S., Richards, C. E., Rajabifard, A., & Acuto, M. (2022) · Nature Sustainability · doi:10.1038/s41893-022-00923-7 · Cited by 224
“…only limited applications of virtual replicas exist to support better planning decisions in the urban and peri-urban areas of developing countries, further marginalizing some one billion people who reside in slums and informal settlements (undermining targets spanning SDGs 6, 7, 9, 11 and 13) 42 .”
BackgroundDigital 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
Havard, V., Jeanne, B., Lacomblez, M., & Baudry, D. (2019) · Production & Manufacturing Research · doi:10.1080/21693277.2019.1660283 · Cited by 183
“Rosen, von Wichert, Lo, and Bettenhausen (2015) deal with the challenges of smart industry by focusing on digital twin to ensure modularity, connectivity, and autonomy of industrial systems.”
BackgroundA Requirements Driven Digital Twin Framework: Specification and Opportunities
Moyne, J. R., Qamsane, Y., Balta, E. C., Kovalenko, I., Faris, J., Barton, K. L., & Tilbury, D. M. (2020) · IEEE Access · doi:10.1109/access.2020.3000437 · Cited by 230
“One common aspect of the SM vision in which DTs play an important role is the movement from reactive to predictive to prescriptive operations in manufacturing application environments [4], [58], [59].”
BackgroundDigital 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
A digital-twin visualized architecture for Flexible Manufacturing System
Fan, Y., Yang, J.-Z., Chen, J.-H., Hu, P., Wang, X., Xu, J.-C., & Zhou, B. (2021) · Journal of manufacturing systems · doi:10.1016/j.jmsy.2021.05.010 · Cited by 181
Zhuang, C., Miao, T., Liu, J., & Xiong, H. (2020) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2020.102075 · Cited by 202
Digital Building Twins and Blockchain for Performance-Based (Smart) Contracts
Hunhevicz, J. J., Motie, M., & Hall, D. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103981 · Cited by 180
“Digital twins are understood as one of the key enablers of digital transformation in the manufacturing industry [23,31,33,34].”
BackgroundRosen, R., Boschert, S., & Sohr, A. (2018) · atp magazin · doi:10.17560/atp.v60i10.2371 · Cited by 179
Self-citationWagner, C., Grothoff, J., Epple, U., Drath, R., Malakuti, S., Grüner, S., Hoffmeister, M., & Zimermann, P. (2017) · IEEE International Conference on Emerging Technologies and Factory Automation · doi:10.1109/etfa.2017.8247583 · Cited by 178
“In this context, the DT is not only a huge collection of information, but it utilizes connections between the information and meta information to explicitly add semantics [10].”
BackgroundData-driven digital twin technology for optimized control in process systems.
He, R., Chen, G.-M., Dong, C., Sun, S., & Shen, X.-Y. (2019) · ISA transactions · doi:10.1016/j.isatra.2019.05.011 · Cited by 176
Arowoiya, V. A., Moehler, R., & Fang, Y. (2023) · Energy and Built Environment · doi:10.1016/j.enbenv.2023.05.004 · Cited by 219
Implementing Industry 4.0 principles
Cañas, H., Mula, J., Díaz-Madroñero, M., & Campuzano-Bolarín, F. (2021) · Computers & industrial engineering · doi:10.1016/j.cie.2021.107379 · Cited by 173
Digital twin driven human–robot collaborative assembly
Bilberg, A., & Malik, A. A. (2019) · CIRP Annals · doi:10.1016/j.cirp.2019.04.011 · Cited by 401
Microsimulation of electric vehicle energy consumption and driving range
Xie, Y., Li, Y.-Y., Zhao, Z., Dong, H., Wang, S.-Q., Liu, J.-P., Guan, J.-H., & Duan, X.-B. (2020) · Applied Energy · doi:10.1016/j.apenergy.2020.115081 · Cited by 171
Rocca, R., Rosa, P., Sassanelli, C., Fumagalli, L., & Terzi, S. (2020) · Sustainability · doi:10.3390/su12062286 · Cited by 171
“CPS being at base of the pyra id (field level) leads to a convergence of physical and digital worlds within the Digital Twin [15] by allowing a real-ti e si ulation of processes, aterial flows, and energy consu ptions [60].”
BackgroundTowards Security-Aware Virtual Environments for Digital Twins
Eckhart, M., & Ekelhart, A. (2018) · CPSS@AsiaCCS · doi:10.1145/3198458.3198464 · Cited by 169
“The term "Digital Twin" was coined by Shafto et al. [29] and describes the use of holistic simulations to virtually mirror a physical system [26].”
Background
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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