About The Importance of Autonomy and Digital Twins for the Future of Manufacturing
Open accessAbstract
Industrie 4.0 - the “brand” name of the German initiative driving the future of manufacturing - is one of several initiatives around the globe emphasizing the importance of industrial manufacturing for economy and society. Besides the socio-economical if not political question which has to be answered - including the question about the future of labor - there are a couple of substantial technical and technological questions that have to be taken care of as well.
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Seven articles in Table 1 developed ad-hoc systems to build DT.
“In Table 1 seven articles developed ' ad-hoc ' systems to build DT: for the management of a didactic production line [26], to construct a MES in Android systems [43], to build user guides for safety reason [60,62], and to evaluate the performances of a cloud-based DT [74,75];”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [62]
The reviewed articles can be divided into two categories by cloud usage: those that effectively use a cloud and build a cloud-based DT application, and those that construct the DT application in a virtual space with software highlighting the possibility to build it also in a cloud-based environment.
“For this aspect, the articles considered can be divided into two different categories: (i) those that effectively use a cloud and build a cloud-based DT application, marked in the table as [27,34,37,43,47,48,54,56,62,67,74-76], (ii) those that construct the DT application in a virtual space with the use of a software highlighting the possibility to build it also in a cloud”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [62]
Some reviewed papers mainly belong to the first service group but also offer services of the second group, and vice versa.
“Also, there are papers that mainly belong to the first group but also offer services of the second group ([39,40,50,70]), and vice versa ([56,61,62]).”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [62]
It can also be implemented for its capability to represent and deal with a continuous flow of data.
“It can also be implemented for its capability to represent and deal with a continuous flow of data [48] [49].”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [48]
Cited by
Sorted by citations
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“respond to state changes even during an ongoing operation [27].”
BackgroundMethodDigital Twin in manufacturing: A categorical literature review and classification
Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W. (2018) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2018.08.474 · Cited by 3,612 · 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…”
BackgroundInfluentialCharacterising the Digital Twin: A systematic literature review
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“The increasing digitalization of manufacturing is opening up opportunities for smart manufacturing [6].”
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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
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“Digital Twin has gained significant impetus as a breakthrough technological development that has the potential to transform the landscape of manufacturing today and tomorrow [1].”
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“[53] seems referring to the DT as a realistic model or simulation with the ability of continuously communicating with its physical twin, which is a too simplistic way for describing it.”
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“The virtual models and physical processes of a DT co-evolve over the life-cycle of the product or system [40].”
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Self-citationDigital twin-driven product design framework
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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
“This level of detail allows DT simulation and prediction tools to be more reliable when presented with a set of alternative actions or scenarios [21].”
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“From the simulation point of view, the digital twin represents a new wave in modelling and simulation (Rosen et al., 2015).”
BackgroundMethodInfluentialDigital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models
Minerva, R., Lee, G. M., & Crespi, N. (2020) · Proceedings of the IEEE · doi:10.1109/jproc.2020.2998530 · Cited by 812 · see citing works
“It also provides the ability to manage the DTs and to simulate their future behavior.”
BackgroundInfluentialDigital twin application in the construction industry: A literature review
Opoku, D.-G. J., Perera, S., Osei-Kyei, R., & Rashidi, M. (2021) · Journal of Building Engineering · doi:10.1016/j.jobe.2021.102726 · Cited by 753 · see citing works
Digital twin: benefits, use cases, challenges, and opportunities
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“In this way, Rosen et al. [33] emphasizes the use of digital twinning in manufacturing.”
Construction with digital twin information systems
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“…and virtual counterparts, enabled by the development of advanced sensing (e.g., computer vision), internet of things (e.g., interconnected assets), high-speed networking (e.g., 5G internet), and advanced analytics (e.g., machine learning) technologies (Rosen et al., 2015; Gerber et al., 2019).”
BackgroundInfluentialDigital Twin for maintenance: A literature review
Errandonea, I., Beltrán, S., & Arrizabalaga, S. (2020) · Computers in Industry · doi:10.1016/j.compind.2020.103316 · Cited by 819 · see citing works
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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
“• The analysis of the debate initiated in 2013 [40] and further explored in [54], whether DT covers the entire product lifecycle [62, 23] or just the product [66, 1].”
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“From this point of view, the twin was referred to as a prototype that mirrored the real operating condition for the simulation of real-time behavior [19].”
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Digital Twin as a Service (DTaaS) in Industry 4.0: An Architecture Reference Model
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Digital Twin for rotating machinery fault diagnosis in smart manufacturing
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“The concept of “twin” is originally derived from NASA’s Apollo Project when the aircraft’s twin body is a real physical system (Rosen et al. 2015).”
BackgroundMethodA digital twin smart city for citizen feedback
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Toward a Digital Twin for real-time geometry assurance in individualized production
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“It is also a possible direction for future manufacturing workshops, and it will raise the next wave of simulation, modeling and optimization (Rosen et al. 2015).”
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“Two typical understandings/areas of the digital twin can be observed in industrial practice [31].”
BackgroundDigital twin and its implementations in the civil engineering sector
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“As to autonomous manufacturing, machines and other resources should be smart, they need to know their capabilities and states both historically and currently (Rosen et al. 2015).”
BackgroundA Digital-Twin-Assisted Fault Diagnosis Using Deep Transfer Learning
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“It simulates and maps the entire product life cycle through ultra-realistic and dynamically optimized simulation models [4], thus reducing the cost of design and maintenance, while enhancing the efficiency and quality of manufacturing.”
A survey on AI-driven digital twins in Industry 4.0: smart manufacturing and advanced robotics
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“The widespread application of simulation models and ubiquitous connectivity provide a solid foundation for building digital production twin throughout the product lifecycle, which is considered a key enabler for future manufacturing transformation and upgrading in the era of big data [1,31,32].”
BackgroundDigital Twin Service towards Smart Manufacturing
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Human–Cyber–Physical Systems (HCPSs) in the Context of New-Generation Intelligent Manufacturing
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“New Industry 4.0 services were also suggested based on the digital twin, to generate insights that can be utilised for the future car design and optimisation (Rüßmann et al. 2015).”
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“The idea of making a "twin" of a process or a product returned to NASA’s Apollo project in the late 1960s (Rosen et al. 2015; Mayani et al. 2018; Schleich et al. 2017), when it assembled two identical space spacecraft.”
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Overview of predictive maintenance based on digital twin technology
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“…can more accurately reflect the real state and behavior of physical devices in the physical space, so that they can detect the function and performance of physical devices in the virtual space, achieve intelligent perception and interconnection, and efficient data transmission and integration [32].”
Applications of Digital Twin across Industries: A Review
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“…support by means of a detailed diagnosis, (ii) maintenance by evaluating and analyzing machine conditions, identifying any changes in the production system and its effects, and taking anticipatory maintenance, and (iii) layout planning by evaluating the production system continuously [11,65].”
Technologies for digital twin applications in construction
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An architecture of an intelligent digital twin in a cyber-physical production system
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“During the mission, theground-basedmodelwasused to simulate alternatives, where the available flight datawas used to reflect the flight conditions as accurately as possible and to assist astronauts in orbit in critical situations [6, 7].”
MethodA Digital Twin Based Industrial Automation and Control System Security Architecture
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“) in a production system allowing advanced simulations of a complete manufacturing system and the units involved in an autonomous system [15].”
BackgroundMobility Digital Twin: Concept, Architecture, Case Study, and Future Challenges
Wang, Z.-R., Gupta, R., Han, K., Wang, H., Ganlath, A., Ammar, N., & Tiwari, P. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3156028 · Cited by 285 · see citing works
“Along with its rapid development in different domains during the past decade, including aeronautics and space [4], [7], robotics [8], [9], manufacturing [10], [11], and informatics [12], the Digital Twin also has a huge potential in the transportation domain.”
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“…to implement Digital Twins is one of the benefits of data collection: large amounts of data enable the construction of simulations of different scenarios, which can be useful to make predictions about behaviors or failures, according to the latest data obtained from the physical twin [5,28].”
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Digital Twins From Smart Manufacturing to Smart Cities: A Survey
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Industry 4.0 and the New Simulation Modelling Paradigm
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“The concept of creating a “twin” of a process or a product can be traced back to the late 1960s when NASA ensembled two identical space vehicles for its Apollo project [20–22].”
BackgroundVisualisation of the Digital Twin data in manufacturing by using Augmented Reality
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Microgrid Digital Twins: Concepts, Applications, and Future Trends
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Is Human Digital Twin possible?
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“…suitable deployment data-model based on urban intelligence systems, pervasive computing, communication, big data management technologies, and artificial intelligence (AI), leading to a strong evolution in the management of urban environments as well as in the quality of life in smart cities [7,8].”
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Scaling digital twins from the artisanal to the industrial
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“Digital twins originated in aerospace engineering, with many people pointing to the Apollo program as the first place where the idea was put in practice, where simulators on the ground mirrored the systems being put into space 10 .”
BackgroundWeb-based digital twin modeling and remote control of cyber-physical production systems
Liu, C., Jiang, P., & Jiang, W. (2020) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2020.101956 · Cited by 223 · see citing works
Modeling of Cloud-Based Digital Twins for Smart Manufacturing with MT Connect
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“Rosen et al. (2015) argue how DT implementations could increase the autonomy of manufacturing systems by combining the real data with simulation models from design, thus allowing the DT to predict future states based on the realistic data.”
MethodExploring the role of digital twin for asset lifecycle management
Macchi, M., Roda, I., Negri, E., & Fumagalli, L. (2018) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2018.08.415 · Cited by 216 · see citing works
“When adopted in manufacturing, the DT has taken a new objective: to simulate the complex behaviour of production systems, also including external factors, as human presence and technical constraints (Rosen et al. 2015; Gabor et al. 2016; Arisoy et al. 2017).”
BackgroundMethodDigital-Twin-Based Job Shop Scheduling Toward Smart Manufacturing
Fang, Y., Peng, C., Lou, P., Zhou, Z., Hu, J., & Yan, J. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2938572 · Cited by 276 · see citing works
“[27]–[29] bring a chance to reduce the gap.”
BackgroundA Methodology for Digital Twin Modeling and Deployment for Industry 4.0
Schroeder, G. N., Steinmetz, C., Rodrigues, R. N., Henriques, R. V. B., Rettberg, A., & Pereira, C. E. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2020.3032444 · Cited by 213 · see citing works
“However, with the advent of CPSs, the DT appears as a virtual representation of the physical product, a digital shadow that contains all its information and knowledge [15].”
BackgroundThe concept of digital twin and digital shadow in manufacturing
Bergs, T., Gierlings, S., Auerbach, T., Klink, A., Schraknepper, D., & Augspurger, T. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.02.010 · Cited by 212 · see citing works
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“” Roland Rosen [20] 2015 A “ new wave in modeling, simulation, and optimization technology, which provides a big set of all digital artifacts.”
BackgroundFuture Modeling and Simulation of CPS-based Factories: an Example from the Automotive Industry
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Control Co‐Design: An engineering game changer
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A Cyber-Physical Machine Tools Platform using OPC UA and MTConnect
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“Nowadays, digital twin is considered as a key enabler for Product Lifecycle Management (PLM), CPPS and Smart Factory in the era of Industry 4.0 [19–21].”
InfluentialThe Convergence of Digital Twin, IoT, and Machine Learning: Transforming Data into Action
Kaur, M., Mishra, V., & Maheshwari, P. (2019) · Internet of Things · doi:10.1007/978-3-030-18732-3_1 · Cited by 209 · see citing works
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Innovations in digital modelling for next generation manufacturing system design
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Systematic review of digital twin technology and applications
Yao, J.-F., Yang, Y., Wang, X.-C., & Zhang, X.-P. (2023) · Visual Computing for Industry, Biomedicine, and Art · doi:10.1186/s42492-023-00137-4 · Cited by 201 · see citing works
“DT was defined from a linkage-focused perspective by Rosen et al. [11] who argued that a DT not only comprises a large collection of digital products but also should possess a good architecture so that all components are linked.”
BackgroundMethodDigital twin in manufacturing: conceptual framework and case studies
Onaji, I., Tiwari, D., Soulatiantork, P., Song, B., & Tiwari, A. (2022) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2022.2027014 · Cited by 298 · see citing works
“As shown in Figure 9, the proposed digital twin framework enables the inclusion of both operational and environmental data for analytics (Rosen et al. 2015; Catapult 2018).”
BackgroundInfluentialVillalonga, A., Negri, E., Biscardo, G., Castaño, F., Haber, R., Fumagalli, L., & Macchi, M. (2021) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2021.04.008 · Cited by 195 · see citing works
Digital Twin Reference Model Development to Prevent Operators’ Risk in Process Plants
Bevilacqua, M., Bottani, E., Ciarapica, F. E., Costantino, F., Donato, L. D., Ferraro, A., Mazzuto, G., Monteriù, A., Nardini, G., Ortenzi, M., et al. (2020) · Sustainability · doi:10.3390/su12031088 · Cited by 223 · see citing works
“0 implies their importance for modern factories [53,54].”
BackgroundModular based flexible digital twin for factory design
Guo, J., Zhao, N., Sun, L., & Zhang, S. (2018) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0953-6 · Cited by 205 · see citing works
Design and implementation of a digital twin application for a connected micro smart factory
Park, K. T., Nam, Y. W., Lee, H. S., Im, S. J., Noh, S. D., Son, J. Y., & Kim, H. (2019) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2019.1599439 · Cited by 194 · see citing works
“The digital twin also aims to ensure the e ffi ciency of a manufacturing site based on interconnection and interaction via the real-world IIoT network (Silveira, Borenstein, and Fogliatto 2001; Rosen et al. 2015; Kühn 2006; Gabor et al. 2016).”
MethodReal-time machining data application and service based on IMT digital twin
Tong, X., Liu, Q., Pi, S., & Xiao, Y. (2019) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01500-0 · Cited by 192 · see citing works
Developing design principles for the digitalisation of purchasing and supply management
Srai, J. S., & Lorentz, H. (2018) · Journal of Purchasing and Supply Management · doi:10.1016/j.pursup.2018.07.001 · Cited by 268 · see citing works
Potential and limitations of digital twins to achieve the Sustainable Development Goals
Tzachor, A., Sabri, S., Richards, C. E., Rajabifard, A., & Acuto, M. (2022) · Nature Sustainability · doi:10.1038/s41893-022-00923-7 · Cited by 224 · see citing works
“…only limited applications of virtual replicas exist to support better planning decisions in the urban and peri-urban areas of developing countries, further marginalizing some one billion people who reside in slums and informal settlements (undermining targets spanning SDGs 6, 7, 9, 11 and 13) 42 .”
BackgroundDigital twin: a state-of-the-art review of its enabling technologies, applications and challenges
Hu, W., Zhang, T., Deng, X., Liu, Z., & Tan, J. (2021) · Journal of Intelligent Manufacturing and Special Equipment · doi:10.1108/jimse-12-2020-010 · Cited by 228 · see citing works
Havard, V., Jeanne, B., Lacomblez, M., & Baudry, D. (2019) · Production & Manufacturing Research · doi:10.1080/21693277.2019.1660283 · Cited by 183 · see citing works
“Rosen, von Wichert, Lo, and Bettenhausen (2015) deal with the challenges of smart industry by focusing on digital twin to ensure modularity, connectivity, and autonomy of industrial systems.”
BackgroundA Requirements Driven Digital Twin Framework: Specification and Opportunities
Moyne, J. R., Qamsane, Y., Balta, E. C., Kovalenko, I., Faris, J., Barton, K. L., & Tilbury, D. M. (2020) · IEEE Access · doi:10.1109/access.2020.3000437 · Cited by 230 · see citing works
“One common aspect of the SM vision in which DTs play an important role is the movement from reactive to predictive to prescriptive operations in manufacturing application environments [4], [58], [59].”
BackgroundDigital Twin of a Cutting Tool
Botkina, D., Hedlind, M., Olsson, B., Henser, J., & Lundholm, T. (2018) · Procedia CIRP · doi:10.1016/j.procir.2018.03.178 · Cited by 183 · 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
Zhuang, C., Miao, T., Liu, J., & Xiong, H. (2020) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2020.102075 · Cited by 202 · 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].”
BackgroundRosen, R., Boschert, S., & Sohr, A. (2018) · atp magazin · doi:10.17560/atp.v60i10.2371 · Cited by 179 · see citing works
Self-citationWagner, C., Grothoff, J., Epple, U., Drath, R., Malakuti, S., Grüner, S., Hoffmeister, M., & Zimermann, P. (2017) · IEEE International Conference on Emerging Technologies and Factory Automation · doi:10.1109/etfa.2017.8247583 · Cited by 178 · see citing works
“In this context, the DT is not only a huge collection of information, but it utilizes connections between the information and meta information to explicitly add semantics [10].”
BackgroundData-driven digital twin technology for optimized control in process systems.
He, R., Chen, G.-M., Dong, C., Sun, S., & Shen, X.-Y. (2019) · ISA transactions · doi:10.1016/j.isatra.2019.05.011 · Cited by 176 · see citing works
Arowoiya, 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 driven human–robot collaborative assembly
Bilberg, A., & Malik, A. A. (2019) · CIRP Annals · doi:10.1016/j.cirp.2019.04.011 · Cited by 401 · see citing works
Microsimulation of electric vehicle energy consumption and driving range
Xie, Y., Li, Y.-Y., Zhao, Z., Dong, H., Wang, S.-Q., Liu, J.-P., Guan, J.-H., & Duan, X.-B. (2020) · Applied Energy · doi:10.1016/j.apenergy.2020.115081 · Cited by 171 · see citing works
Rocca, R., Rosa, P., Sassanelli, C., Fumagalli, L., & Terzi, S. (2020) · Sustainability · doi:10.3390/su12062286 · Cited by 171 · see citing works
“CPS being at base of the pyra id (field level) leads to a convergence of physical and digital worlds within the Digital Twin [15] by allowing a real-ti e si ulation of processes, aterial flows, and energy consu ptions [60].”
BackgroundTowards Security-Aware Virtual Environments for Digital Twins
Eckhart, M., & Ekelhart, A. (2018) · CPSS@AsiaCCS · doi:10.1145/3198458.3198464 · Cited by 169 · see citing works
“The term "Digital Twin" was coined by Shafto et al. [29] and describes the use of holistic simulations to virtually mirror a physical system [26].”
Background
- Authors
- Rosen, R., von Wichert, G., Lo, G., & Bettenhausen, K. D.
- Affiliations
- Siemens (Germany) (DE)
- Siemens (United States) (US)
- Corresponding author
- Rosen, Roland
- Lo, George
- Bettenhausen, Kurt D.
- Venue
- IFAC-PapersOnLine
- Publisher
- Elsevier BV
- Published
- 2015
- Volume
- 48
- Issue
- 3
- Pages
- 567-572
- ISSN
- 2405-8963 (ISSN-L)
- OpenAlex
- W2346505350
- Cited by
- 1,474
- References
- 2
- Citations by year
- 2026: 113 · 2025: 163 · 2024: 202 · 2023: 226 · 2022: 200 · 2021: 183 · 2020: 138 · 2019: 142 · 2018: 73 · 2017: 22 · 2016: 11 · 2012: 1
- FWCI
- 61.97
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IFAC-PapersOnLine (publishedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- Industry 4.0, digital twin, future of manufacturing, future of work, industrial automation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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