The DOI matches its Crossref record; 43 of the 49 references it cites were found in a registry or an index.
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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In the citing paper
“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]
Citations
Cites
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“(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×
“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
Recent advances and trends in predictive manufacturing systems in big data environment
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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
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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×
“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
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
Schluse, M., & Rossmann, J. (2016) · 2016 IEEE International Symposium on Systems Engineering (ISSE) · doi:10.1109/syseng.2016.7753162 · Cited by 292
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×
“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
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×
“…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×
“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…”
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Garetti, M., Rosa, P., & Terzi, S. (2012) · Computers in Industry · doi:10.1016/j.compind.2012.02.007 · Cited by 156 · cited 2×
“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×
“…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
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×
“…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×
“…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×
“(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
Kuhn, T. (2017) · Informatik-Spektrum · doi:10.1007/s00287-017-1061-2 · Cited by 76
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×
“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×
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BackgroundInfluentialMastering Complexity with Autonomous Production Processes
Theuer, H., & Lass, S. (2016) · Procedia CIRP · doi:10.1016/j.procir.2016.07.058 · Cited by 7
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…”
Background
Flagged first, then by citations
6 of the 49 references couldn’t be matched to a known paper.
Research works printed but not linked: 4
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Cited by
Sorted by citations
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
“[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
“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 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
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
“, from 2001 to 2006 [41], from 2014 [37], from 2005 to 2016 [38]).”
Background
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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