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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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“a single process [34,36,44,45]”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [36]
In the citing paper
“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]
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Liu, Y., Feng, J., Lu, J., & Zhou, S. (2024) · Advanced Engineering Informatics · doi:10.1016/j.aei.2024.102592 · Cited by 123
Autonomous, context-aware, adaptive Digital Twins—State of the art and roadmap
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Albalkhy, W., Karmaoui, D., Ducoulombier, L., Lafhaj, Z., & Linner, T. (2024) · Automation in Construction · doi:10.1016/j.autcon.2024.105368 · Cited by 136
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Xiong, M., & Wang, H. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-09717-9 · Cited by 187
“The development of DT benefits from the support of the abovementioned advanced technologies; meanwhile, it is listed as one of the top ten emerging technologies by Gartner [7], and it shows significant potential value in many fields [8, 9].”
BackgroundIliuţă, M.-E., Moisescu, M.-A., Pop, E., Ionita, A.-D., Caramihai, S.-I., & Mitulescu, T.-C. (2024) · Applied Sciences · doi:10.3390/app14135454 · Cited by 134
“Singh et al. [13] classified Digital Twins according to several parameters, including creation time, integration level, role within the application, focused application parameters, hierarchical structure, and maturity level.”
BackgroundMethodBadakhshan, E., & Ball, P. (2022) · International Journal of Production Research · doi:10.1080/00207543.2022.2093682 · Cited by 133
“Much of the literature developed conceptual frameworks and there is limited research on the application of the SC digital twins in practice (Badakhshan and Ball 2021; Kritzinger et al. 2018).”
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Smart manufacturing scheduling: A literature review
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Digital Twins in Civil Infrastructure Systems
Callcut, M., Cerceau Agliozzo, J.-P., Varga, L., & McMillan, L. (2021) · Sustainability · doi:10.3390/su132011549 · Cited by 132
“It is also pertinent to note that the ability to create what [76] defines as a DT, “automated control of the physical twin”, is currently quite rare, if possible at all, in the vast majority of applications.”
BackgroundThe Internet of Things in the Oil and Gas Industry: A Systematic Review
Wanasinghe, T. R., Gosine, R. G., James, L. A., Mann, G. K. I., Silva, O. D., & Warrian, P. J. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.2995617 · Cited by 203
“This systematic review follows a similar approach presented in [47] and [48], and Table I summarizes this article selection criteria for this review.”
MethodA Comprehensive Review of Digital Twins Technology in Agriculture
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“According to the prevailing taxonomy in digital twin research [12,13], integration levels have advanced sequentially from digital models (static) through digital shadows (dynamic) to full digital twins (interactive), with each stage defined by data coupling intensity and control capabilities.”
InfluentialReinforcement learning for facilitating human-robot-interaction in manufacturing
Oliff, H., Liu, Y., Kumar, M., Williams, M. D., & Ryan, M. J. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.018 · Cited by 142
Towards next generation digital twin in robotics: Trends, scopes, challenges, and future
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“In other studies “Digital Twin” (DT) has been used erratically to describe various connections between the physical and digital components in the growing volume of literature [5].”
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Industrial digitalization. A systematic literature review and research agenda
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Koulouris, A., Misailidis, N., & Petrides, D. (2021) · doi:10.1016/j.fbp.2021.01.016 · Cited by 128
The role of digital twins in lean supply chain management: review and research directions
Guo, D., & Mantravadi, S. (2024) · International Journal of Production Research · doi:10.1080/00207543.2024.2372655 · Cited by 157
“With a higher level of data integration between the physical and digital counterparts, interaction and optimisation can be achieved by combining digital twins with big data, operations research and artificial intelligence techniques (Kritzinger et al. 2018; Qi et al.2021; Rathore et al. 2021).”
The Role of Digital Twins in Connected and Automated Vehicles
Schwarz, C., & Wang, Z. (2022) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2021.3129524 · Cited by 133
“In contrast, the digital twin exchanges data in both directions [2], [24], [25].”
BackgroundComprehensive analysis of digital twins in smart cities: a 4200-paper bibliometric study
El-Agamy, R., Sayed, H. A., al Akhatatneh, A. M., Aljohani, M. K. A., & Elhosseini, M. A. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10781-8 · Cited by 125
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Glatt, M. F., Sinnwell, C., Yi, L., Donohoe, S. P., Ravani, B., & Aurich, J. C. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.04.015 · Cited by 166
Digital twins and industrial internet of things: uncovering operational intelligence in Industry 4.0
Attaran, S., Attaran, M., & Celik, B. G. (2024) · Decision Analytics Journal · doi:10.1016/j.dajour.2024.100398 · Cited by 122
Digital twin-driven deep reinforcement learning for adaptive task allocation in robotic construction
Lee, D., Lee, S. H., Masoud, N., Krishnan, M. S., & Li, V. C. (2022) · Advanced Engineering Informatics · doi:10.1016/j.aei.2022.101710 · Cited by 143
Digital Twin Framework for Built Environment: A Review of Key Enablers
Piras, G., Agostinelli, S., & Muzi, F. (2024) · Energies · doi:10.3390/en17020436 · Cited by 118
A digital twin hierarchy for metal additive manufacturing
Phua, A., Davies, C. H. J., & Delaney, G. W. (2022) · Computers in Industry · doi:10.1016/j.compind.2022.103667 · Cited by 145
Destro, F., & Barolo, M. (2022) · International journal of pharmaceutics · doi:10.1016/j.ijpharm.2022.121715 · Cited by 118
Falekas, G., & Karlis, A. D. (2021) · Energies · doi:10.3390/en14185933 · Cited by 141
“Digital construct categorization as established by [16] and adopted by broader literature.”
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Industry application of digital twin: from concept to implementation
Fang, X., Wang, H., Liu, G., Tian, X., Ding, G., & Zhang, H. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-09632-z · Cited by 135
“Based on the degree of data transfer between them, Kritzinger et al. [9] proposed that there are three categories of current DT models: (1) digital model (DM), no data flow; (2) digital shadow (DS), there is a one-way data flow; and (3) digital twin (DT), there is a two-way data flow, so the whole…”
BackgroundEramo, R., Bordeleau, F., Combemale, B., van den Brand, M., Wimmer, M., & Wortmann, A. (2022) · IEEE Software · doi:10.1109/ms.2021.3130755 · Cited by 116
“Research and industry have produced various definitions [9], [11], ranging from underspecified (digital replica or virtual counterpart), over narrow (virtual representation based on augmented reality technology), to utopian (complete digital representation) approaches.”
BackgroundInfluentialJeddoub, I., Nys, G., Hajji, R., & Billen, R. (2023) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2023.103440 · Cited by 101
The Role of BIM in Integrating Digital Twin in Building Construction: A Literature Review
Nguyen, T. D., & Adhikari, S. (2023) · Sustainability · doi:10.3390/su151310462 · Cited by 113
“…result, the framework proposed by the researchers aims to assist the construction industry in comprehending the degree of digital transformation maturity in construction by classifying the present literature based on the classification of DT implementation in manufacturing by Kritzinger et al. [52].”
MethodDigital twin application in energy storage: Trends and challenges
Semeraro, C., Olabi, A., Aljaghoub, H., Alami, A., Radi, M. A., Dassisti, M., & Abdelkareem, M. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2022.106347 · Cited by 113
State-of-the-art survey on digital twin implementations
Liu, Y. K., Ong, S. K., & Nee, A. Y. C. (2022) · Advances in Manufacturing · doi:10.1007/s40436-021-00375-w · Cited by 126
“Many of these reviews categorize DT based on the level of direct control between the virtual models and the physical systems, namely, no interaction, unidirectional and bidirectional, or digital models, digital shadows and digital twins respectively [9, 24, 25].”
Backgroundvan der Valk, H., Haße, H., Möller, F., & Otto, B. (2021) · Business & Information Systems Engineering · doi:10.1007/s12599-021-00727-7 · Cited by 113
“Evidently, using the Digital Twin concept in healthcare use cases (e.g., see Rivera et al. (2019) for the use case digital patients ) requires a different set of specialized characteristics than a Digital Twin in manufacturing (e.g., see Kritzinger et al. (2018)).”
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Aheleroff, S., Mostashiri, N., Xu, X., & Zhong, R. (2021) · Advanced Engineering Informatics · doi:10.1016/j.aei.2021.101438 · Cited by 113
A digital twin for smart farming
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“Digital Twin concept [16]”
BackgroundDigital twin for intelligent tunnel construction
Li, T., Li, X.-J., Rui, Y., Ling, J.-X., Zhao, S., & Zhu, H.-H. (2024) · Automation in Construction · doi:10.1016/j.autcon.2023.105210 · Cited by 112
Digital-twin-based testing for cyber–physical systems: A systematic literature review
Somers, R. J., Douthwaite, J. A., Wagg, D., Walkinshaw, N., & Hierons, R. M. (2022) · Information and Software Technology · doi:10.1016/j.infsof.2022.107145 · Cited by 132
Urban development with dynamic digital twins in Helsinki city
Hämäläinen, M. (2021) · IET Smart Cities · doi:10.1049/smc2.12015 · Cited by 151
A digital twin-based flexible cellular manufacturing for optimization of air conditioner line
Guo, H., Chen, M., Khalgui, M., Qu, T., Wang, S., & Li, J. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.07.012 · Cited by 123
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“In the presented definition, in line with the findings of Kritzinger et al. (2018), an automatic data exchange is required.”
BackgroundResultInfluentialWu, D. X., Zheng, A., Yu, W., Cao, H., Ling, Q., Liu, J., & Zhou, D. (2025) · Applied Sciences · doi:10.3390/app15041911 · Cited by 133
Yu, D., & He, Z. (2022) · Natural Hazards · doi:10.1007/s11069-021-05190-x · Cited by 170
Psarommatis, F. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2021.03.021 · Cited by 123
“Under this categorization, only 18 % of papers claiming to present DTs are presenting true DTs [35].”
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Digital Twins for the Circular Economy
Preut, A., Kopka, J., & Clausen, U. (2021) · Sustainability · doi:10.3390/su131810467 · Cited by 110
“Based on descriptions and definitions of the scientists Michael Grieves and John Vickers [15], who are widely regarded as the originators of the idea for the digital twin [15,21,22] the following working definition was set.”
BackgroundDevelopment of Digital Twin for Intelligent Maintenance of Civil Infrastructure
Mahmoodian, M., Shahrivar, F., Setunge, S., & Mazaheri, S. (2022) · Sustainability · doi:10.3390/su14148664 · Cited by 110
Digital twin for ship life-cycle: A critical systematic review
Mauro, F., & Kana, A. A. (2022) · Ocean Engineering · doi:10.1016/j.oceaneng.2022.113479 · Cited by 141
“Therefore, Kritzinger et al. (2018) propose the following classification for reported use cases: – Digital Model : no automatic communication between virtual and physical states.”
BackgroundDigital Twins in the Construction Industry: A Perspective of Practitioners and Building Authority
Ammar, A., Nassereddine, H., AbdulBaky, N., AbouKansour, A., Tannoury, J., Urban, H., & Schranz, C. (2022) · Frontiers in Built Environment · doi:10.3389/fbuil.2022.834671 · Cited by 148
“The increased focus on data and the opportunities created by digitization promoted the potential of the emerging phenomenon of Digital Twins in the manufacturing industry with the wave of Industry 4.0 to ful fi ll the requirements of Smart Factory (Negri et al., 2017; Kritzinger et al., 2018; Tao et al., 2019).”
BackgroundInfluentialZeb, S., Mahmood, A., Hassan, S. A., Piran, M., Gidlund, M., & Guizani, M. (2021) · Journal of Network and Computer Applications · doi:10.48550/arxiv.2108.04465 · Cited by 107
“A DT model is often confused with digital shadow or digital model ; however, in the latter approaches, there are no automated exchange of control data between the image created in the virtual space and the physical objects to alter the industrial processes [51], [52].”
MethodSoft Materials and Devices Enabling Sensorimotor Functions in Soft Robots
Su, J., He, K., Li, Y., Tu, J., & Chen, X. (2025) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00906 · Cited by 121
Hosamo, H., Hosamo, M., Nielsen, H., Svennevig, P. R., & Svidt, K. (2022) · Advances in Building Energy Research · doi:10.1080/17512549.2022.2136240 · Cited by 106
“For example, Kritzinger et al. (2018), Autiosalo et al. (2020), J. Lee et al. (2013), H. H. Hosamo and Hosamo (2022), and H. H. Hosamo, Imran, et al. (2022); nevertheless, Grieves fi rst articulated the concept of Digital Twin in 2012.”
BackgroundSimulation-based decision support tool for in-house logistics: the basis for a digital twin
Coelho, F., Relvas, S., & Barbosa‐Póvoa, A. P. (2020) · Computers & Industrial Engineering · doi:10.1016/j.cie.2020.107094 · Cited by 120
Methods for enabling real-time analysis in digital twins: A literature review
Eshaghi, M. S., Anitescu, C., & Rabczuk, T. (2024) · Computers & Structures · doi:10.1016/j.compstruc.2024.107342 · Cited by 120
Digital Twin: Where do humans fit in?
Agrawal, A., Thiel, R., Jain, P., Singh, V., & Fischer, M. (2023) · Automation in Construction · doi:10.48550/arxiv.2301.03040 · Cited by 105
“[37] describes three types of DT based on the level of data integration: (1) Digital Model, which is a digital representation of the physical object without any data exchange, (2) Digital Shadow, which includes one-way data flows from the physical object to the digital object, and (3) Digital Twin, which has bidirecti…”
BackgroundMethodResultA Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture
Chaux, J. D., Sanchez-Londoño, D., & Barbieri, G. (2021) · Applied Sciences · doi:10.3390/app11198875 · Cited by 122
“According to Kritzinger et al. [17] and Negri et al. [18], DT “exploits sensed data, mathematical models and real-time data elaboration to forecast and optimise the behaviour of the physical asset at each life cycle phase, in real-time”.”
BackgroundMethodDigital twins in healthcare: a comprehensive review and future directions
Rudsari, H. K., Tseng, B., Zhu, H., Song, L., Gu, C., Roy, A., Irajizad, E., Butner, J. D., Long, J. P., & Do, K.-A. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1633539 · Cited by 105
Wu, H., Ji, P., Ma, H., & Xing, L. (2023) · Sensors · doi:10.3390/s23198306 · Cited by 119
“A digital twin, according to Kritzinger et al. [3], is a digital representation of a physical entity with a fully integrated and automated bi-directional data flow to the physical entity.”
MethodDigital Twin models in industrial operations: State‐of‐the‐art and future research directions
Melesse, T. Y., Pasquale, V., & Riemma, S. (2021) · IET Collaborative Intelligent Manufacturing · doi:10.1049/cim2.12010 · Cited by 103
Systems Architecture Design Pattern Catalog for Developing Digital Twins
Tekinerdoğan, B., & Verdouw, C. (2020) · Italian National Conference on Sensors · doi:10.3390/s20185103 · Cited by 103
“A model for a control system is shown in Figure 5 (based on [1,24,25]).”
MethodTowards Model-Driven Digital Twin Engineering: Current Opportunities and Future Challenges
Bordeleau, F., Combemale, B., Eramo, R., van den Brand, M., & Wimmer, M. (2020) · International Conferences on Systems Modelling and Management · doi:10.1007/978-3-030-58167-1_4 · Cited by 103
“Each digital twin is defined in terms of one or more models of the system, or part of it [26].”
BackgroundA scoping review of human digital twins in healthcare applications and usage patterns
Tudor, B. H., Shargo, R., Gray, G., Fierstein, J., Kuo, F. H., Burton, R. A., Johnson, J. T., Scully, B., Asante-Korang, A., Rehman, M. A., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01910-w · Cited by 102
Digital Twin Technology in Built Environment: A Review of Applications, Capabilities and Challenges
Mousavi, Y., Gharineiat, Z., Karimi, A. A., McDougall, K., Rossi, A., & Barsanti, S. G. (2024) · Smart Cities · doi:10.3390/smartcities7050101 · Cited by 117
“…level, the system exhibits a high degree of autonomy and can analyse detailed performance [21]. to the physical object, influencing its behaviour [22] and facilitating real-time planning and decision-making It can perform automatic prediction and operation under various unknown situations to…”
Digital Twins: A Maturity Model for Their Classification and Evaluation
Uhlenkamp, J.-F., Hauge, J. B., Broda, E., Lütjen, M., Freitag, M., & Thoben, K. (2022) · IEEE Access · doi:10.1109/access.2022.3186353 · Cited by 134
“However, we would like to use this criterion to further distinguish DTs and therefore adopt Kritzinger’s characteristics for our MM.”
BackgroundInfluentialRiaz, K., Mcafee, M., & Gharbia, S. S. (2023) · Italian National Conference on Sensors · doi:10.3390/s23052659 · Cited by 99
Literature review of digital twin technologies for civil infrastructure
Liu, C., Zhang, P., & Xu, X. (2023) · Journal of Infrastructure Intelligence and Resilience · doi:10.1016/j.iintel.2023.100050 · Cited by 98
Digital Twin Applications in the Water Sector: A Review
Bam, P. G., Rezaei, N., Roubanis, A., Austin, D. M., Austin, E. S., Tarroja, B., Takacs, I., Villez, K., & Rosso, D. (2025) · Water · doi:10.3390/w17202957 · Cited by 98
Digital Twin in the Maritime Domain: A Review and Emerging Trends
Madusanka, N. S., Fan, Y., Yang, S., & Xiang, X. (2023) · Journal of Marine Science and Engineering · doi:10.3390/jmse11051021 · Cited by 142
Digital Twin in biomanufacturing: challenges and opportunities towards its implementation
Udugama, I. A., Lopez, P. C., Gargalo, C. L., Li, X., Bayer, C., & Gernaey, K. (2021) · Systems Microbiology and Biomanufacturing · doi:10.1007/s43393-021-00024-0 · Cited by 97
Analysis of Digital Twin Applications in Energy Efficiency: A Systematic Review
Ba, L., Tangour, F., El Abbassi, I., & Absi, R. (2025) · Sustainability · doi:10.3390/su17083560 · Cited by 96
Automated vision-based construction progress monitoring in built environment through digital twin
Pal, A., Lin, J. J., Hsieh, S., & Golparvar‐Fard, M. (2023) · Developments in the Built Environment · doi:10.1016/j.dibe.2023.100247 · Cited by 119
Multimedia knowledge‐based bridge health monitoring using digital twin
Kang, J., Chung, K., & Hong, E. J. (2021) · Multimedia Tools and Applications · doi:10.1007/s11042-021-10649-x · Cited by 108
Naderi, H., & Shojaei, A. (2023) · Automation in Construction · doi:10.1016/j.autcon.2023.104785 · Cited by 115
Actionable cognitive twins for decision making in manufacturing
Rožanec, J. M., Lu, J., Rupnik, J., Škrjanc, M., Mladenić, D., Fortuna, B., Zheng, X., & Kiritsis, D. (2021) · International Journal of Production Research · doi:10.1080/00207543.2021.2002967 · Cited by 114
Enabling battery digital twins at the industrial scale
Dubarry, M., Howey, D., & Wu, B. (2023) · Joule · doi:10.1016/j.joule.2023.05.005 · Cited by 93
Digital Twins in Agriculture and Forestry: A Review
Tagarakis, A., Benos, L., Kyriakarakos, G., Pearson, S., Sørensen, C. G., & Bochtis, D. (2024) · Italian National Conference on Sensors · doi:10.3390/s24103117 · Cited by 92
“In the present study, the proposed classification of Kritzinger et al. [64] is used, which was developed on the basis of the achievable level of data integration between the physical asset and its virtual counterpart.”
BackgroundMethodGrosse, E. (2023) · International Journal of Production Research · doi:10.1080/00207543.2023.2169383 · Cited by 92
“…digitally the essential characteristics of a physical system with real-time bidirectional interaction between the digital and physical systems’ (Kritzinger et al. 2018; Zhang et al. 2022), has increased considerably in supply chain management (e.g. Ivanov and Dolgui 2021; Badakhshan and Ball…”
BackgroundThe impact of digital twins on the evolution of intelligent manufacturing and Industry 4.0
Attaran, M., Attaran, S., & Çelik, B. G. (2023) · Advances in Computational Intelligence · doi:10.1007/s43674-023-00058-y · Cited by 129
“Since then, many scholars have provided varied definitions of this technology and discussed various stages of digital twin development (Fuller et al. 2020; Stark and Damerau 2019; Kritzinger et al. 2018; Tao et al. 2018a).”
BackgroundDigital Twin and Industry 4.0 Enablers in Building and Construction: A Survey
Wei, H., Lim, K. Y. H., & Cai, Y. (2022) · Buildings · doi:10.3390/buildings12112004 · Cited by 136
Abdelrahman, M., Macatulad, E., Lei, B., Quintana, M., Miller, C., & Biljecki, F. (2025) · Building and Environment · doi:10.1016/j.buildenv.2025.112748 · Cited by 120
Options for and Challenges of Employing Digital Twins in Construction Management
Salem, T., & Dragomir, M. (2022) · Applied Sciences · doi:10.3390/app12062928 · Cited by 90
The Digital Twin Concept in Industry – A Review and Systematization
Sjarov, M., Lechler, T., Fuchs, J., Brossog, M., Selmaier, A., Faltus, F., Donhauser, T., & Franke, J. E. (2020) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa46521.2020.9212089 · Cited by 132
“In 2018, Kritzinger et al. [10] provided a review on existing literature in which the use of a Digital Twin would be mentioned.”
BackgroundComputation Offloading and Service Caching for Intelligent Transportation Systems With Digital Twin
Xu, X., Liu, Z., Bilal, M., Vimal, S., & Song, H. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3190669 · Cited by 95
“Recently, DT has been researched and applied to many industries [7].”
BackgroundDigital Twins in Human-Computer Interaction: A Systematic Review
Barricelli, B. R., & Fogli, D. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2118189 · Cited by 98
“Another literature review is (Kritzinger et al., 2018), also focused on DT in manufacturing.”
BackgroundDynamic Routings in Satellite Networks: An Overview
Cao, X., Li, Y., Xiong, X., & Wang, J. (2022) · Italian National Conference on Sensors · doi:10.3390/s22124552 · Cited by 89
Smart Production Planning and Control: Concept, Use-Cases and Sustainability Implications
Oluyisola, O., Sgarbossa, F., & Strandhagen, J. (2020) · Sustainability · doi:10.3390/su12093791 · Cited by 89
“Meanwhile, a digital twin goes a step further and, in addition to accepting data, can send action instructions to the production system [57].”
BackgroundFrom Simulation to Autonomy: Reviews of the Integration of Artificial Intelligence and Digital Twins
Sajadieh, S. M. M., & Noh, S. D. (2025) · International Journal of Precision Engineering and Manufacturing-Green Technology · doi:10.1007/s40684-025-00750-z · Cited by 114
“This is particularly useful in environments where continuous monitoring is essential, such as predictive maintenance or condition monitoring [4, 71–73].”
Digital Twin applications in the food industry: a review
Abdurrahman, E., & Ferrari, G. (2025) · Frontiers in Sustainable Food Systems · doi:10.3389/fsufs.2025.1538375 · Cited by 88
Digital twins for performance management in the built environment
Petri, I., Rezgui, Y., Ghoroghi, A., & Alzahrani, A. (2023) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2023.100445 · Cited by 88
“Digital twin models are proposed in the field of smart maintenance systems [27] alongside functional architectures with applicability for industrial case studies [28].”
BackgroundDigital Twins in Agriculture: A Review of Recent Progress and Open Issues
Wang, L. (2024) · Electronics · doi:10.3390/electronics13112209 · Cited by 87
Digital Twin: From Concept to Practice
Agrawal, A., Fischer, M., & Singh, V. (2022) · Journal of Management in Engineering · doi:10.48550/arxiv.2201.06912 · Cited by 87
“Love and Matthews (2019) noted that to realize the purported benefits of technology, asking a series of “how” questions is essential.”
BackgroundMa, S.-Z., Flanigan, K. A., & Bergés, M. (2023) · Advanced Engineering Informatics · doi:10.1016/j.aei.2024.102800 · Cited by 86
“The study must define DT-related terms similar to the aforementioned selected surveys and reviews [46, 53, 54, 55, 56, 57] C-CR2 The study must state its intention (e.g., framework, implementation, both) C-CR3 The study must propose and address its own research question(s) C-CR4 The study should…”
BackgroundMethodResultKineber, A. F., Singh, A. K., Fazeli, A., Mohandes, S. R., Cheung, C. M., Arashpour, M., EJOHWOMU, O. A., & Zayed, T. M. (2023) · Sustainable Cities and Society · doi:10.1016/j.scs.2023.104930 · Cited by 91
Wu, Z. Y., Chew, A., Meng, X., Cai, J., Pok, J., Kalfarisi, R., Lai, K. C., Hew, S. F., & Wong, J. (2023) · Sustainable cities and society · doi:10.1016/j.scs.2023.104446 · Cited by 86
Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry
Henrichs, E., Noack, T., Pinzón, A. M., Salem, M. A., Stolz, J., & Krupitzer, C. (2021) · Sensors · doi:10.3390/s22010115 · Cited by 99
Digital Twin for Smart Manufacturing: The Simulation Aspect
Shao, G., Jain, S., Laroque, C., Lee, L., Lendermann, P., & Rose, O. (2019) · Online World Conference on Soft Computing in Industrial Applications · doi:10.1109/wsc40007.2019.9004659 · Cited by 86
“Kritzinger et al. (2018) propose a classification of digital models into three subcategories based on their level of data integration between the physical and digital counterparts: (1) Digital model: a digital representation of an existing or planned physical object without any form of automated…”
Metadata
- 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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