Digital Twin in manufacturing: A categorical literature review and classification
Open accessAbstract
The Digital Twin (DT) is commonly known as a key enabler for the digital transformation, however, in literature is no common understanding concerning this term. It is used slightly different over the disparate disciplines. The aim of this paper is to provide a categorical literature review of the DT in manufacturing and to classify existing publication according to their level of integration of the DT. Therefore, it is distinct between Digital Model (DM), Digital Shadow (DS) and Digital Twin. The results are showing, that literature concerning the highest development stage, the DT, is scarce, whilst there is more literature about DM and DS.
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Digital twins monitor a single process.
“a single process [34,36,44,45]”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [36]
Dealing with a constant flux of data makes it also possible to apply Artificial Intelligence (AI) and Machine Learning (ML) techniques to IoT systems based on Digital Twin.
“Dealing with a constant flux of data makes it also possible to apply Artificial Intelligence (AI) and Machine Learning (ML) techniques to IoT systems based on Digital Twin [51][52][53] [54].”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [53]
Cites
The NIST Definition of Cloud Computing
Mell, P., & Grance, T. (2011) · doi:10.6028/nist.sp.800-145 · Cited by 15,338 · see citing works
A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems
Lee, J., Bagheri, B., & Kao, H.-A. (2015) · Manufacturing Letters · doi:10.1016/j.mfglet.2014.12.001 · Cited by 5,113 · see citing works
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-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 · cited 4× · see citing works
“(Tao et al. 2017; Lee et al. 2013a; Rosen et al. 2015) To get a more common understanding of the Digital Twin, the level of integration are discussed in the following section.”
BackgroundInfluentialThe 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
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 · cited 7× · see citing works
“(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…”
BackgroundInfluentialShaping 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 · cited 3× · see citing works
“While some researchers, especially coming from the class Digital Shadow, see a further research need in developing the optimization and simulation methods, others see the data connectivity as main problem.(Yang et al. 2016; Um et al. 2017b; Vachálek et al. 2017; Schleich et al. 2017; Frazzon et al. 2016; Kuhn 2017; St…”
BackgroundMethodDigital 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
Recent advances and trends in predictive manufacturing systems in big data environment
Lee, J., Lapira, E., Bagheri, B., & Kao, H.-A. (2013) · Manufacturing Letters · doi:10.1016/j.mfglet.2013.09.005 · Cited by 1,090 · cited 7× · see citing works
“…stages of machine life cycle to handle data/information more efficiently and further achieve better transparency of a machine’s health condition (Lee et al. 2013b) Layout planning (Uhlemann et al. 2017a) o continuous production system evaluation and planning o Automatic and application…”
BackgroundInfluentialThe Digital Twin: Realizing the Cyber-Physical Production System for Industry 4.0
Uhlemann, T. H.-J., Lehmann, C., & Steinhilper, R. (2017) · Procedia CIRP · doi:10.1016/j.procir.2016.11.152 · Cited by 994 · see citing works
From the Internet of Computers to the Internet of Things
Mattern, F., & Floerkemeier, C. (2010) · From Active Data Management to Event-Based Systems and More · doi:10.1007/978-3-642-17226-7_15 · Cited by 772 · see citing works
Machine Learning for Predictive Maintenance: A Multiple Classifier Approach
Susto, G. A., Schirru, A., Pampuri, S., McLoone, S., & Beghi, A. (2015) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2349359 · Cited by 763 · 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 · cited 2× · see citing works
“Categorical literature review Reference Type Level of integration Focused area Technology Boschert, Rosen (2016) review DT product lifecycle simulation Bottani et al. (2017) case-study DT PPC simulation Brenner, Hummel (2017) definition DT PPC sensors Cai et al. (2017) concept DM maintenance simulation Frazzon et al.…”
BackgroundThe Digital Twin: Demonstrating the Potential of Real Time Data Acquisition in Production Systems ☆
Uhlemann, T., Schock, C., Lehmann, C., Freiberger, S., & Steinhilper, R. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.04.043 · Cited by 426 · 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
Schluse, M., & Rossmann, J. (2016) · 2016 IEEE International Symposium on Systems Engineering (ISSE) · doi:10.1109/syseng.2016.7753162 · Cited by 292 · see citing works
Cai, Y., Starly, B., Cohen, P., & Lee, Y.-S. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.07.094 · Cited by 289 · cited 3× · see citing works
“While some researchers, especially coming from the class Digital Shadow, see a further research need in developing the optimization and simulation methods, others see the data connectivity as main problem.(Yang et al. 2016; Um et al. 2017b; Vachálek et al. 2017; Schleich et al. 2017; Frazzon et al. 2016; Kuhn 2017; St…”
BackgroundBrenner, B., & Hummel, V. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.04.039 · Cited by 212 · see citing works
Future 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 · cited 2× · see citing works
“…al. (2017b) concept undefined PPC AutomationML, XML, CPS, PLC, OPC-UA, MQTT, MTConnect Vachálek et al. (2017) case-study DS PPC Plant Simulation, OPC-UA Weyer et al. (2016) concept DS PPC simulation, CPS, SOA Yang et al. (2016) concept DS PPC simulation, optimization Zhang et al. (2017) concept…”
BackgroundInnovations 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 · cited 3× · see citing works
“While some researchers, especially coming from the class Digital Shadow, see a further research need in developing the optimization and simulation methods, others see the data connectivity as main problem.(Yang et al. 2016; Um et al. 2017b; Vachálek et al. 2017; Schleich et al. 2017; Frazzon et al. 2016; Kuhn 2017; St…”
BackgroundLife 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 · cited 2× · see citing works
“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 the synchronization between the virtual and real system, thanks to sense…”
BackgroundTool-wear prediction and pattern-recognition using artificial neural network and DNA-based computing
D'Addona, D., Ullah, A. S. S., & Matarazzo, D. (2015) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-015-1155-0 · Cited by 142 · cited 5×
“…o Improved decision support by means of detailed diagnosis o Automatic planning and execution from orders by the production units Maintenance (D’Addona et al. 2017; Susto et al. 2015) o Identify the impact of state changes on upstream and downstream processes of a production system o…”
BackgroundMethodInfluentialPredictive Manufacturing System - Trends of Next-Generation Production Systems
Lee, J., Lapira, E., Yang, S., & Kao, A. (2013) · IFAC Proceedings Volumes · doi:10.3182/20130522-3-br-4036.00107 · Cited by 140 · cited 6× · see citing works
“…stages of machine life cycle to handle data/information more efficiently and further achieve better transparency of a machine’s health condition (Lee et al. 2013b) Layout planning (Uhlemann et al. 2017a) o continuous production system evaluation and planning o Automatic and application…”
BackgroundInfluentialVirtual factory: an integrated approach to manufacturing systems modeling
Jain, S., Choong, N. F., Aye, K. M., & Luo, M. (2001) · International Journal of Operations & Production Management · doi:10.1108/01443570110390354 · Cited by 112 · see citing works
New Perspectives for Generating Smart PSS Solutions – Life Cycle, Methodologies and Transformation
Kuhlenkötter, B., Wilkens, U., Bender, B., Abramovici, M., Süße, T., Göbel, J., Herzog, M., Hypki, A., & Lenkenhoff, K. (2017) · Procedia CIRP · doi:10.1016/j.procir.2017.03.036 · Cited by 105 · cited 3× · see citing works
“…TCP/IP, optimization Jain et al. (2001) concept DS layout planning simulation Kaylani, Atieh (2016) case-study DM PPC discrete event simulation Kuhlenkötter et al. (2017) concept DM product lifecycle - Kuhn (2017) review DT maintenance simulation Kumar et al. (2015) case-study DM PPC…”
BackgroundA virtual factory approach for in situ simulation to support production and maintenance planning
Terkaj, W., Tolio, T., & Urgo, M. (2015) · CIRP Annals · doi:10.1016/j.cirp.2015.04.121 · Cited by 100 · cited 1× · see citing works
“…al. (2017) review DS product lifecycle simulation Tao et al. (2017) concept DM PPC Semantic Web Terkaj, Urgo (2015) concept undefined PPC simulation, CPS Terkaj et al. (2015) concept DM process design simulation, Semantic Web, UML Theuer, Lass (2016) concept undefined PPC simulation, CPS, System…”
BackgroundPlug-and-Simulate within Modular Assembly Line enabled by Digital Twins and the use of AutomationML
Um, J., Weyer, S., & Quint, F. (2017) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2017.08.2360 · Cited by 88 · cited 6× · see citing works
“(Weyer et al. 2016; Um et al. 2017b; Uhlemann et al. 2017a; Lindström et al. 2017; Kuhn 2017) 4.”
BackgroundInfluentialSimons, S., Abé, P., & Neser, S. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.04.023 · Cited by 78 · see citing works
Kuhn, T. (2017) · Informatik-Spektrum · doi:10.1007/s00287-017-1061-2 · Cited by 76 · see citing works
Lindström, J., Larsson, H., Jonsson, M., & Lejon, E. (2017) · doi:10.1016/j.procir.2017.03.099 · Cited by 57
Bowyer, A., Bayliss, G., Taylor, R., & Willis, P. (1996) · International journal of shape modeling · doi:10.1142/s0218654396000117 · Cited by 43 · cited 1×
“…study DM product lifecycle discrete event simulation, sensors Gyulai et al. (2016) concept DM layout planning Plant Simulation, TCP/IP, optimization Jain et al. (2001) concept DS layout planning simulation Kaylani, Atieh (2016) case-study DM PPC discrete event simulation Kuhlenkötter et al.…”
MethodSimulation-based optimization for the integrated scheduling of production and logistic systems
Frazzon, E., Albrecht, A., & Hurtado, P. (2016) · doi:10.1016/j.ifacol.2016.07.581 · Cited by 35 · cited 3×
“While some researchers, especially coming from the class Digital Shadow, see a further research need in developing the optimization and simulation methods, others see the data connectivity as main problem.(Yang et al. 2016; Um et al. 2017b; Vachálek et al. 2017; Schleich et al. 2017; Frazzon et al. 2016; Kuhn 2017; St…”
BackgroundMüller, R., Vette, M., Hörauf, L., Speicher, C., & Burkhard, D. (2017) · doi:10.1016/j.promfg.2017.07.215 · Cited by 30 · cited 1×
“…DS maintenance PHM, TCM, sensors Lindström et al. (2017) case-study DS maintenance PHM, sensors Mell, Grance (2011) case-study DS PPC visualization Müller et al. (2017) review DT manufacturing in general - Pawlaszczyk (2006) review DT manufacturing in general optimization Prager, David (2016)…”
BackgroundA Flexible Simulation Support for Production Planning and Control in Small and Medium Enterprises
Yang, S., Arndt, T., & Lanza, G. (2016) · doi:10.1016/j.procir.2016.10.062 · Cited by 22 · cited 3×
“Categorical literature review Reference Type Level of integration Focused area Technology Boschert, Rosen (2016) review DT product lifecycle simulation Bottani et al. (2017) case-study DT PPC simulation Brenner, Hummel (2017) definition DT PPC sensors Cai et al. (2017) concept DM maintenance simulation Frazzon et al.…”
BackgroundSimulation-based Production Planning and Execution Control for Reconfigurable Assembly Cells
Gyulai, D., Pfeiffer, A., Kádár, B., & Monostori, L. (2016) · doi:10.1016/j.procir.2016.11.077 · Cited by 20 · cited 1×
“…RFID Friedrich et al. (2014) concept DS maintenance - GE Power Digital Solutions (2016) study DM product lifecycle discrete event simulation, sensors Gyulai et al. (2016) concept DM layout planning Plant Simulation, TCP/IP, optimization Jain et al. (2001) concept DS layout planning…”
BackgroundAutonomous Systems for Maintenance Tasks – Requirements and Design of a Control Architecture☆
Friedrich, C., Lechler, A., & Verl, A. (2014) · doi:10.1016/j.protcy.2014.09.020 · Cited by 19 · cited 2×
“Categorical literature review Reference Type Level of integration Focused area Technology Boschert, Rosen (2016) review DT product lifecycle simulation Bottani et al. (2017) case-study DT PPC simulation Brenner, Hummel (2017) definition DT PPC sensors Cai et al. (2017) concept DM maintenance simulation Frazzon et al.…”
Kaylani, H., & Atieh, A. (2016) · doi:10.1016/j.procir.2015.12.072 · Cited by 16
Streaming Machine Generated Data to Enable a Third-Party Ecosystem of Digital Manufacturing Apps☆
Singh, S., Angrish, A., Barkley, J., Starly, B., Lee, Y.-S., & Cohen, P. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.07.093 · Cited by 15 · cited 4× · see citing works
“Categorical literature review Reference Type Level of integration Focused area Technology Boschert, Rosen (2016) review DT product lifecycle simulation Bottani et al. (2017) case-study DT PPC simulation Brenner, Hummel (2017) definition DT PPC sensors Cai et al. (2017) concept DM maintenance simulation Frazzon et al.…”
BackgroundMethodInfluentialA Virtual Factory Data Model as a Support Tool for the Simulation of Manufacturing Systems
Terkaj, W., & Urgo, M. (2015) · doi:10.1016/j.procir.2015.04.023 · Cited by 15
Salleh, N., Kasolang, S., Mustakim, M. A., & Kuzaiman, N. A. (2017) · doi:10.1016/j.procs.2017.01.206 · Cited by 11 · cited 4×
“(Zhang et al. 2017; Salleh et al. 2017) There is a tremendous benefit of the Digital Twin for applications in industry, but there is still a lack of case-studies which apply the concepts in practice.”
BackgroundInfluentialDevelopment a Modular Factory with Modular Software Components
Um, J., Fischer, K., Spieldenner, T., & Kolberg, D. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.07.196 · Cited by 11 · cited 5× · see citing works
“(Weyer et al. 2016; Um et al. 2017b; Uhlemann et al. 2017a; Lindström et al. 2017; Kuhn 2017) 4.”
BackgroundInfluentialMastering Complexity with Autonomous Production Processes
Theuer, H., & Lass, S. (2016) · Procedia CIRP · doi:10.1016/j.procir.2016.07.058 · Cited by 7 · see citing works
Inclusion of Long-term Production Planning/Scheduling into Real-time Optimization
Kumar, D., Ye, C., & Esmaili, A. (2015) · doi:10.1016/j.ifacol.2015.08.186 · Cited by 5 · cited 1×
“…case-study DM PPC discrete event simulation Kuhlenkötter et al. (2017) concept DM product lifecycle - Kuhn (2017) review DT maintenance simulation Kumar et al. (2015) case-study DM PPC optimization Lee et al. (2013b) concept DS maintenance PHM, CPS Lee et al. (2013c) concept DS maintenance…”
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Flagged first, then by citations
6 of the 49 references couldn’t be matched to a known paper.
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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
“[11] to produce a categorical review table of selected publications.”
BackgroundCharacterising 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
“5 Fidelity [33] [80] [108] [24] [85] [8] [56] [88] [68] [112] [99] [78] [32] [111] [36] [7] [71] [63] [61] [73] [20] [67] [6] [4] [48] [55] [95] [16] [92] [98] [87] [9] [66] [110] [18] [89] [12]”
BackgroundInfluentialReview 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
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
A 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 · see citing works
“, from 2001 to 2006 [41], from 2014 [37], from 2005 to 2016 [38]).”
BackgroundKusiak, A. (2018) · International Journal of Production Research · doi:10.1080/00207543.2017.1351644 · Cited by 1,330 · 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: 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 · see citing works
Review 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 · see citing works
Digital twin paradigm: A systematic literature review
Semeraro, C., Lezoche, M., Panetto, H., & Dassisti, M. (2021) · Computers in industry (Print) · doi:10.1016/j.compind.2021.103469 · Cited by 852 · see citing works
“(Stark et al., 2017) characterizes the DT as (1) an unique instance of the universal Digital Master model of an asset, (2) its individual Digital Shadow and (3) an intelligent linkage (algorithm, simulation model, correlation, etc.) of the two elements above (Kritzinger et al., 2018).”
BackgroundDigital 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 · see citing works
“This effort covers different stages in the production and also different applications cases [27].”
BackgroundDigital Twin: Generalization, characterization and implementation
VanDerHorn, E., & Mahadevan, S. (2021) · Decision Support Systems · doi:10.1016/j.dss.2021.113524 · Cited by 808 · see citing works
Digital 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 · see citing works
Digital twin: benefits, use cases, challenges, and opportunities
Attaran, M., & Celik, B. G. (2023) · Decision Analytics Journal · doi:10.1016/j.dajour.2023.100165 · Cited by 704 · see citing works
Digital twins in smart farming
Verdouw, C., Tekinerdoğan, B., Beulens, A., & Wolfert, S. (2021) · Agricultural Systems · doi:10.1016/j.agsy.2020.103046 · Cited by 634 · see citing works
“Basically, this implies that they must have a feedback loop in which a norm, sensor, discriminator, decision maker, and effector are present (de Leeuw, 1997; Int Veld, 2002).”
BackgroundConstruction 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 · see citing works
“Although there is no commonly agreed conceptualization or definition of the term (Kritzinger et al., 2018; Gerber et al., 2019), numerous organizations have defined digital twins in terms of their functions and characteristics.”
BackgroundDigital 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 · see citing works
Digital Twins: State of the art theory and practice, challenges, and open research questions
Sharma, A., Kosasih, E., Zhang, J., Brintrup, A., & Calinescu, A. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2022.100383 · Cited by 587 · see citing works
“Some works focus on specific domains, such as manufacturing [54], aerospace [60] and production science [39], others are general [20, 73].”
BackgroundInfluentialIntroducing digital twins to agriculture
Pylianidis, C., Osinga, S., & Athanasiadis, I. N. (2021) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2020.105942 · Cited by 720 · see citing works
“…will be some confusion in the coming years about what a DT is and when a technology can be considered a DT. Research has been done to classify technologies based on how close they are to becoming DT (Kritzinger et al., 2018), but it is still difficult to identify when a system can be called a DT.”
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Aheleroff, S., Xu, X. W., Zhong, R. Y., & Lu, Y. (2020) · Advanced Engineering Informatics · doi:10.1016/j.aei.2020.101225 · Cited by 680 · see citing works
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“Meanwhile, the authors in [6] reviewed digital twins for Industry 4.”
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 · see citing works
Deng, M., Menassa, C., & Kamat, V. (2021) · Journal of Information Technology in Construction · doi:10.36680/j.itcon.2021.005 · Cited by 448 · see citing works
“…of the Digital Twin originated from the aerospace field (Shafto et al. 2010), and then expanded to industrial manufacturing (Negri et al. 2017, Kritzinger et al. 2018, Zhuang et al. 2018, Tchana et al. 2019, Zhang et al. 2019), has attracted increasing attention in the built environment…”
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Thelen, A., Zhang, X., Fink, O., Lu, Y., Ghosh, S., Youn, B. D., Todd, M. D., Mahadevan, S., Hu, C. K., & Hu, Z. Y. (2022) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-022-03425-4 · Cited by 471 · see citing works
City Digital Twin Potentials: A Review and Research Agenda
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Javaid, M., Haleem, A., & Suman, R. (2023) · Cognitive Robotics · doi:10.1016/j.cogr.2023.04.003 · Cited by 466 · see citing works
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 · see citing works
Sepasgozar, S. M. E. (2021) · Buildings · doi:10.3390/buildings11040151 · Cited by 381 · see citing works
“, BIM) and DT as similar concepts or used them interchangeably [33,66,67].”
MethodWoschank, M., Rauch, E., & Zsifkovits, H. (2020) · Sustainability · doi:10.3390/su12093760 · Cited by 338 · see citing works
“…there are many research activities for realizing CPS and mono-directional information flow from the physical object to the digital model (digital shadow), and in a further step a bidirectional information flow between both models to control the physical system through a so-called digital twin [66].”
BackgroundKamble, 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 · see citing works
Deep learning in drug discovery: an integrative review and future challenges
Askr, H., Elgeldawi, E., Aboul-Ella, H., Elshaier, Y., Gomaa, M. M., & Hassanien, A. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10306-1 · Cited by 328 · see citing works
“In an ideal world, the digital component would have all the system’s information that could be acquired from its physical counterpart (Kritzinger et al. 2018).”
BackgroundLiu, X., Jiang, D., Tao, B., Xiang, F., Jiang, G., Sun, Y., Kong, J., & Li, G. (2023) · Advanced Engineering Informatics · doi:10.1016/j.aei.2023.101876 · Cited by 369 · see citing works
From Corrective to Predictive Maintenance—A Review of Maintenance Approaches for the Power Industry
Moleda, M., Małysiak-Mrozek, B., Ding, W.-P., Sunderam, V., & Mrozek, D. (2023) · Italian National Conference on Sensors · doi:10.3390/s23135970 · Cited by 317 · see citing works
Xia, K., Sacco, C., Kirkpatrick, M. B., Saidy, C., Nguyen, L., Kircaliali, A., & Harik, R. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.012 · Cited by 426 · see citing works
A Survey on Digital Twin for Industrial Internet of Things: Applications, Technologies and Tools
Xu, H., Wu, J., Pan, Q., Guan, X., & Guizani, M. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3297395 · Cited by 304 · see citing works
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 · see citing works
“A DT can help in (i) production planning and control by planning and executing the orders automatically and improving decision 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 anticipa…”
Digital Twins in Agriculture: A State-of-the-art review
Purcell, W., & Neubauer, T. (2022) · Smart Agricultural Technology · doi:10.1016/j.atech.2022.100094 · Cited by 303 · see citing works
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 · see citing works
“In [9] several definitions ofDigital Twins are compared and evaluated.”
BackgroundMethodHosamo, H., Svennevig, P. R., Svidt, K., Han, D., & Nielsen, H. (2022) · Energy and Buildings · doi:10.1016/j.enbuild.2022.111988 · Cited by 297 · see citing works
Framework for a digital twin in manufacturing: Scope and requirements
Shao, G., & Helu, M. (2020) · Manufacturing Letters · doi:10.1016/j.mfglet.2020.04.004 · Cited by 292 · see citing works
Digital Twin for the Oil and Gas Industry: Overview, Research Trends, Opportunities, and Challenges
Wanasinghe, T. R., Wroblewski, L., Petersen, B. K., Gosine, R. G., James, L. A., Silva, O. D., Mann, G. K. I., & Warrian, P. J. (2020) · IEEE Access · doi:10.1109/access.2020.2998723 · Cited by 411 · see citing works
“of the literature review presented in this article, however, is limited to the O&G industry and follows a similar approach to that presented in [11], [38]–[42].”
ResultDigital Twin: A Comprehensive Survey of Security Threats
Alcaraz, C., & López, J. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3171465 · Cited by 364 · see citing works
“To further clarify such differences and highlight the characteristics of a DT, Kritsinger et al. identify in [2] three variants of mirroring systems, classifying them as: digital model , an isolated system without automatic connection to the real world; digital shadow , a system with an automated…”
BackgroundShahzad, M., Shafiq, M. T., Douglas, D., & Kassem, M. (2022) · Buildings · doi:10.3390/buildings12020120 · Cited by 356 · see citing works
“The interview participants viewed digital twins as a twoway interaction between a virtual model and physical asset, which has been highlighted by several authors [12,30].”
BackgroundWan, J., Li, X.-M., Dai, H., Kusiak, A., Martinez-García, M. A., & Li, D. (2020) · Proceedings of the IEEE · doi:10.1109/jproc.2020.3034808 · Cited by 272 · see citing works
“Moreover, digital twin technologies may be the driving technologies to improve resource reconfigura-tion [172]–[174].”
BackgroundSmart city based on digital twins
Li, D.-R., Yu, W.-B., & Shao, Z.-F. (2021) · Computational Urban Science · doi:10.1007/s43762-021-00005-y · Cited by 264 · see citing works
Perno, M., Hvam, L., & Haug, A. (2021) · Computers in Industry · doi:10.1016/j.compind.2021.103558 · Cited by 328 · see citing works
“…limited to construction (Opoku et al., 2021), healthcare (Semeraro et al., 2021), industrial production (Negri et al., 2017; Rasheed et al., 2020; Kritzinger et al., 2018), aviation (Mandolla et al., 2019) and automotive (Alcácer and Cruz-Machado, 2019) industries, meteorology, education and…”
BackgroundMethodResultInfluentialA six-layer architecture for the digital twin: a manufacturing case study implementation
Redelinghuys, A., Basson, A., & Kruger, K. (2019) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01516-6 · Cited by 247 · see citing works
“Kritzinger et al. (2018) distinguishes between the various digital forms and categorized them as digital model, digital shadow and digital twin.”
BackgroundMethodDigital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review
Chen, Y., Yang, O., Sampat, C., Bhalode, P., Ramachnadran, R., & Ierapetritou, M. (2020) · Processes · doi:10.3390/pr8091088 · Cited by 295 · see citing works
“…ones in industry currently, including the employment of a digital model where the digital representation of a physical system exists without automated data communications in both ways, and a digital shadow where model exists with one-way data transfer from physical to virtual component [2].”
BackgroundInfluentialDigital Twin in Aerospace Industry: A Gentle Introduction
Li, L., Aslam, S., Wileman, A., & Perinpanayagam, S. (2021) · IEEE Access · doi:10.1109/access.2021.3136458 · Cited by 316 · see citing works
“flow, from physical entity to the virtual side, whilstnot realising the close-loop of data which involvesusing virtual data to affect the physical entity [29].”
BackgroundMicrogrid 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 · see citing works
“physical product can be obtained from its DT [24]–[26].”
BackgroundDelgado, J. M. D., & Oyedele, L. O. (2021) · Advanced Engineering Informatics · doi:10.1016/j.aei.2021.101332 · Cited by 272 · see citing works
Web-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 · see citing works
Digital Twins for Multiple Sclerosis
Voigt, I., Inojosa, H., Dillenseger, A., Haase, R., Akgün, K., & Ziemssen, T. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.669811 · Cited by 279 · see citing works
The 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 · see citing works
Digital twin: Data exploration, architecture, implementation and future
Dihan, M. S., Akash, A. I., Tasneem, Z., Das, P., Das, S. K., Islam, M. R., Islam, M. M., Badal, F. R., Ali, M. F., Ahamed, M. H., et al. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e26503 · Cited by 250 · see citing works
“…Extensible Markup Language (XML), Kepware, ZigBee, Message Queuing Telemetry Trans-port (MQTT), MySQL, Application Programming Interface (API), UML/SD, MTComm, Standard Internet Protocol, Industrial Internet of Things (IIoT) Protocol, Wireless Communication, TCP/IP Connection [111,112].”
BackgroundAivaliotis, P., Georgoulias, K., Arkouli, Z., & Makris, S. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.03.072 · Cited by 204 · see citing works
A framework for data-driven digital twins of smart manufacturing systems
Friederich, J., Francis, D. P., Lazarova‐Molnar, S., & Mohamed, N. (2021) · Computers in Industry · doi:10.1016/j.compind.2021.103586 · Cited by 348 · see citing works
“This enables the digitally extracted simulation model to be a high-fidelity replica of the real entity that it is modeling in real-time (Kritzinger et al., 2018), (Tao et al., 2019).”
BackgroundInfluentialDigital 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 · see citing works
“…years, more authors are inclined to the notion that the vision refers to a comprehensive virtual representation with connectivity to the physical and functional description of the product/system throughout the lifecycle phases (Yun, Park, and Kim 2017; Cheng et al. 2018; Kritzinger et al. 2018).”
BackgroundInfluentialSchalk, N., Tkadletz, M., & Mitterer, C. (2021) · Surface & Coatings Technology · doi:10.1016/j.surfcoat.2021.127949 · Cited by 197 · see citing works
Digital Ecosystems for Developing Digital Twins of the Earth: The Destination Earth Case
Nativi, S., Mazzetti, P., & Craglia, M. (2021) · Remote Sensing · doi:10.3390/rs13112119 · Cited by 196 · see citing works
“The three concepts implement different levels of integration between the physical and digital entities [17]: a digital model does not implement any form of automated data exchange between the physical and the digital entities (i.e., in Figure 2, the “Data stream” and “Actions” connections are…”
BackgroundDigital twins: An analysis framework and open issues
Boyes, H. A., & Watson, T. (2022) · Computers in Industry · doi:10.1016/j.compind.2022.103763 · Cited by 241 · see citing works
“The other two axes are the “ Value Life-cycle ” , a proposed agile iterative/incremental approach to development lifecycle (Aheleroff et al., 2019), and data flow based on a digital twin integration hierarchy (Kritzinger et al., 2018).”
BackgroundVillalonga, 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 · see citing works
Real-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 · see citing works
Digital Twins: Review and Challenges
Juarez, M. G., Botti, V. J., & Giret, A. S. (2021) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4050244 · Cited by 187 · see citing works
Digital twins in infrastructure: definitions, current practices, challenges and strategies
Broo, D. G., & Schooling, J. (2023) · International Journal of Construction Management · doi:10.1080/15623599.2021.1966980 · Cited by 184 · see citing works
“For instance, Barricelli et al. (2019) argue that a digital twin is more than a simple model and simulation and refers to the works of Grieves (2014), Kritzinger et al. (2018), Negri et al. (2017) and Boschert and Rosen (2016).”
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 · see citing works
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 · see citing works
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 · see citing works
“Digital twins are understood as one of the key enablers of digital transformation in the manufacturing industry [23,31,33,34].”
BackgroundDigital Twin Models in Industrial Operations: A Systematic Literature Review
Melesse, T. Y., Pasquale, V., & Riemma, S. (2020) · Procedia Manufacturing · doi:10.1016/j.promfg.2020.02.084 · Cited by 180 · see citing works
“However, some applied case studies already exist in the literature [17].”
BackgroundMethodA review of building digital twins to improve energy efficiency in the building operational stage
Cespedes-Cubides, A. S., & Jradi, M. (2024) · Energy Informatics · doi:10.1186/s42162-024-00313-7 · Cited by 177
“Utilizing the levels of data integration of Kritzinger et al. (2018) for digital twins in manufacturing, as shown in Fig.”
MethodArowoiya, V., Moehler, R., & Fang, Y.-H. (2023) · Energy and Built Environment · doi:10.1016/j.enbenv.2023.05.004 · Cited by 173 · see citing works
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 · see citing works
Digital Twin Research in the AECO-FM Industry
Ozturk, G. B. (2021) · Journal of Building Engineering · doi:10.1016/j.jobe.2021.102730 · Cited by 172 · see citing works
Digital Twin Hospital Buildings: An Exemplary Case Study through Continuous Lifecycle Integration
Peng, Y., Zhang, M., Yu, F.-Q., Xu, J., & Gao, S. (2020) · Advances in Civil Engineering · doi:10.1155/2020/8846667 · Cited by 172 · see citing works
“A survey shows more than half of declared DT research papers about manufacture only reached the digital shadow level of integration [13].”
BackgroundAsatiani, A., Malo, P., Nagbøl, P. R., Penttinen, E., Rinta-Kahila, T., & Salovaara, A. (2021) · Journal of the AIS · doi:10.17705/1jais.00664 · Cited by 172 · see citing works
“approach that simplifies envelopment is to strive for “gray-box models,” as exemplified by the creation of “digital twins” that can simulate real, physical processes (see El Saddik, 2018; Kritzinger et al., 2018).”
BackgroundTowards electric digital twin grid: Technology and framework review
Sifat, M. M. H., Choudhury, S. M., Das, S. K., Ahamed, M. H., Muyeen, S. M., Hasan, M. M., Ali, M. F., Tasneem, Z., Islam, M. M., Islam, M. R., et al. (2022) · Energy and AI · doi:10.1016/j.egyai.2022.100213 · Cited by 189 · see citing works
“Due to the real-time interconnectivity, each decision made by the twin grid flows into the physical layer with the help of incident response strategies [91].”
BackgroundMicrosimulation 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 · see citing works
Qian, C., Liu, X., Ripley, C., Qian, M., Liang, F., & Yu, W. (2022) · Future Internet · doi:10.3390/fi14020064 · Cited by 235 · see citing works
Digital Twins in greenhouse horticulture: A review
Ariesen-Verschuur, N., Verdouw, C. N., & Teki̇nerdoğan, B. (2022) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2022.107183 · Cited by 187 · see citing works
Intelligent manufacturing execution systems: A systematic review
Shojaeinasab, A., Charter, T., Jalayer, M., Khadivi, M., Ogunfowora, O., Raiyani, N., Yaghoubi, M., & Najjaran, H. (2022) · Journal of manufacturing systems · doi:10.1016/j.jmsy.2022.01.004 · Cited by 167 · see citing works
A review on the characteristics of cyber-physical systems for the future smart factories
Napoleone, A., Macchi, M., & Pozzetti, A. (2020) · Journal of manufacturing systems · doi:10.1016/j.jmsy.2020.01.007 · Cited by 167 · see citing works
“[85] Kritzinger W, Karner M, Traar G, Henjes J, Sihn W, Kritzinger W, et al.”
BackgroundDevelopment of a Digital Twin for smart farming: Irrigation management system for water saving
Alves, R. G., Maia, R., & Lima, F. (2023) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2023.135920 · Cited by 165 · see citing works
Trends in Smart Manufacturing: Role of Humans and Industrial Robots in Smart Factories
Evjemo, L., Gjerstad, T., Grøtli, E., & Sziebig, G. (2020) · Current Robotics Reports · doi:10.1007/s43154-020-00006-5 · Cited by 164 · see citing works
Enhancing wisdom manufacturing as industrial metaverse for industry and society 5.0
Yao, X., Ma, N., Zhang, J., Wang, K., Yang, E., & Faccio, M. (2022) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-022-02027-7 · Cited by 211 · see citing works
Coupry, C., Noblecourt, S., Richard, P., Baudry, D., & Bigaud, D. (2021) · Applied Sciences · doi:10.3390/app11156810 · Cited by 160 · see citing works
“Digital Model (left), igital Shado ( i dl ), i it l in (right) [21].”
BackgroundMethodInfluentialA New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future
Bécue, A., Maia, E., Feeken, L., Borchers, P., & Praça, I. (2020) · Applied Sciences · doi:10.3390/app10134482 · Cited by 188 · see citing works
“As the authors of [37,52,69] provided more extensive surveys on recent developments in the area of digital twins for manufacturing, we proceed with highlighting key enabling technologies for modeling digital twins, as presented recently by Rasheed et al.”
MethodDigital twin enhanced BIM to shape full life cycle digital transformation for bridge engineering
Song, H.-H., Yang, G., Li, H.-J., Zhang, T., & Jiang, A.-N. (2023) · Automation in Construction · doi:10.1016/j.autcon.2022.104736 · Cited by 159 · see citing works
Digital twin design for real-time monitoring – a case study of die cutting machine
Wang, K., Lee, Y.-H., & Angelica, S. (2020) · International Journal of Production Research · doi:10.1080/00207543.2020.1817999 · Cited by 182 · see citing works
“According to Kritzinger et al. (2018), DT has experienced three evolutions in its development (Figure 1): the digital model does not have an automated data exchange between physical and digital objects; the digital shadow has an automated unidirectional data flow between physical and digital…”
MethodTowards next generation cyber-physical systems and digital twins for construction
Akanmu, A., Anumba, C., & Ogunseiju, O. O. (2021) · Journal of Information Technology in Construction · doi:10.36680/j.itcon.2021.027 · Cited by 159 · see citing works
“Providing a less complex definition, Lee and Seshia (2011) described CPS as a tight integration of computational resources with physical processes.”
BackgroundMethodDigital Twins for Cyber-Physical Systems Security: State of the Art and Outlook
Eckhart, M., & Ekelhart, A. (2019) · Security and Quality in Cyber-Physical Systems Engineering · doi:10.1007/978-3-030-25312-7_14 · Cited by 158 · see citing works
“Consequently, Kritzinger et al. (2018) proposed a classification of the digital-twin concept based on how the data exchange between the virtual replica and its physical counterpart is realized.”
BackgroundMethodInfluentialConceptualisation of a 7-element digital twin framework in supply chain and operations management
Ivanov, D. (2023) · International Journal of Production Research · doi:10.1080/00207543.2023.2217291 · Cited by 157 · see citing works
“Kritzinger et al. (2018), Negri, Fumagalli, and Macchi (2017), Melesse, Di Pasquale, and Riemma (2020), Psarommatis and May (2022) and Singh et al. (2020) focus on manufacturing-oriented digital twins.”
BackgroundDigital Twin in Industry 4.0: Technologies, Applications and Challenges
Pires, F., Cachada, A., Barbosa, J., Moreira, A., & Leitão, P. (2019) · International Conference on Industrial Informatics · doi:10.1109/indin41052.2019.8972134 · Cited by 157 · see citing works
“According to the literature review performed by [15] one of the most common technologies found in the literature for model construction is discrete event modelling.”
BackgroundMethodInfluentialMES-integrated digital twin frameworks
Negri, E., Berardi, S., Fumagalli, L., & Macchi, M. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.05.007 · Cited by 213 · see citing works
The use of digital twins in healthcare: socio-ethical benefits and socio-ethical risks
Popa, E., van Hilten, M., Oosterkamp, E., & Bogaardt, M. (2021) · Life Sciences, Society and Policy · doi:10.1186/s40504-021-00113-x · Cited by 152 · see citing works
Adoption paths of digital transformation in manufacturing SME
Battistoni, E., Gitto, S., Murgia, G., & Campisi, D. (2022) · International Journal of Production Economics · doi:10.1016/j.ijpe.2022.108675 · Cited by 150 · see citing works
Field-synchronized Digital Twin framework for production scheduling with uncertainty
Negri, E., Pandhare, V., Cattaneo, L., Singh, J., Macchi, M., & Lee, J. (2020) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-020-01685-9 · Cited by 150 · see citing works
Digital Twins Driven Supply Chain Visibility within Logistics: A New Paradigm for Future Logistics
Moshood, T. D., Nawanir, G., Sorooshian, S., & Okfalisa, O. (2021) · Applied System Innovation · doi:10.3390/asi4020029 · Cited by 195 · see citing works
“The following list of problems that are likely to be faced while attempting to introduce a Digital Twins has been established based on the concerns posed by [17,96,97].”
BackgroundImpactful Digital Twin in the Healthcare Revolution
Hassani, H., Huang, X., & MacFeely, S. (2022) · Big Data and Cognitive Computing · doi:10.3390/bdcc6030083 · Cited by 200 · see citing works
“There are bi-directional data connections between the physical product and its virtual twin; however, the data is exchanged manually [27,28], meaning the virtual twin represents a certain status of the physical product with the manually controlled process of synthesis.”
BackgroundA knowledge-based Digital Shadow for machining industry in a Digital Twin perspective
Ladj, A., Wang, Z., Meski, O., Belkadi, F., Ritou, M., & Cunha, C. M. D. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.07.018 · Cited by 173 · see citing works
“Furthermore, the data flows are fully integrated for both directions, one may refer to Digital Twin where the digital objects generate feedback for the control of the physical object (Kritzinger et al. 2018).”
BackgroundA review of digital twin applications in construction
Madubuike, O. C., Anumba, C. J., & Khallaf, R. (2022) · Journal of Information Technology in Construction · doi:10.36680/j.itcon.2022.008 · Cited by 147 · see citing works
“Kritzinger et al. (2018) explained more on PLM, which referred to an industry presentation describing DT as a digital informational construct of a physical system created as an entity on its own but linked to the physical system.”
Background
- Authors
- Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W.
- Affiliations
- Fraunhofer Austria (AT)
- Corresponding author
- Kritzinger, Werner
- Venue
- IFAC-PapersOnLine
- Publisher
- Elsevier BV
- Published
- 2018
- Volume
- 51
- Issue
- 11
- Pages
- 1016-1022
- ISSN
- 2405-8963 (ISSN-L)
- OpenAlex
- W2890904471
- Cited by
- 3,612
- References
- 49
- Citations by year
- 2026: 761 · 2025: 639 · 2024: 576 · 2023: 577 · 2022: 437 · 2021: 356 · 2020: 194 · 2019: 71 · 2018: 1
- FWCI
- 128.89
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IFAC-PapersOnLine (publishedVersion)
- Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) (submittedVersion)
- Fraunhofer-Publica (Fraunhofer-Gesellschaft) (submittedVersion)
- Funders
- European Commission
- Horizon 2020 Framework Programme
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
- Keywords
- digital twin, manufacturing industry, digital models, digital shadow, digital transformation, terminology, levels of integration
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