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About The Importance of Autonomy and Digital Twins for the Future of Manufacturing
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Industrie 4.0 - the “brand” name of the German initiative driving the future of manufacturing - is one of several initiatives around the globe emphasizing the importance of industrial manufacturing for economy and society. Besides the socio-economical if not political question which has to be answered - including the question about the future of labor - there are a couple of substantial technical and technological questions that have to be taken care of as well.
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“In Table 1 seven articles developed ' ad-hoc ' systems to build DT: for the management of a didactic production line [26], to construct a MES in Android systems [43], to build user guides for safety reason [60,62], and to evaluate the performances of a cloud-based DT [74,75];”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [62]
In the citing paper
“For this aspect, the articles considered can be divided into two different categories: (i) those that effectively use a cloud and build a cloud-based DT application, marked in the table as [27,34,37,43,47,48,54,56,62,67,74-76], (ii) those that construct the DT application in a virtual space with the use of a software highlighting the possibility to build it also in a cloud”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [62]
In the citing paper
“Also, there are papers that mainly belong to the first group but also offer services of the second group ([39,40,50,70]), and vice versa ([56,61,62]).”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [62]
In the citing paper
“It can also be implemented for its capability to represent and deal with a continuous flow of data [48] [49].”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [48]
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Research works printed but not linked: 2
- Siemens 2014. A worldwide production language, Siemens Industry Journal, 01 | 2014 | siemens.com/industry
- Tenorth, 2013, KnowRob – A Knowledge Processing Infrastructure for Cognition-enabled Robots, International Journal of Robotics Research (IJRR), 32
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BackgroundMethodGrübel, J. (2022) · arXiv.org · doi:10.48550/arxiv.2202.07104 · Cited by 3
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“A comprehensive virtual representation that captures all relevant information of a potential or existing physical product, spanning from the atomic scale to the macroscopic geometric structure (Rosen et al. 2015).”
Attar, A., Zhong, S., Luis, M., & Sucala, V. (2026) · Syst. · doi:10.3390/systems14030335 · Cited by 2
“This evolution toward integrated, real-time, and autonomous simulation-based manufacturing systems represents a fundamental shift toward truly smart manufacturing paradigms, where simulation serves not merely as an analysis tool but as an integral component of the production system itself [31,32].”
Developing a Digital Twin for Human Performance Assessment in Human–Machine Interaction
Novak, E., Javernik, A., Palčić, I., & Ojsteršek, R. (2026) · Machines · doi:10.3390/machines14030346 · Cited by 4
“While traditional digital twin applications focus primarily on equipment, automation, and system-level optimization [1,4,19], far fewer studies incorporate human performance variability and learning effects into virtual models [10,14,15].”
InfluentialDigital twin model for performance analysis and manufacturing process optimization
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“…product past, current and possible future states, and facilitates the development of product related intelligent services ” 3 Rosen et al., 2015 [29] “ A very realistic model of the current state of the process and their own behavior in interaction with their environment in the real world ” 4…”
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“[20] CONCLUSIONS:”
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“Experimental results demonstrate the effectiveness of the proposed model in various scenarios, highlighting its potential to transform traditional IoT networks into self-adaptive and resilient systems [8].”
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“The digital twin has been defined as a new simulation paradigm that extends the use of simulation to all phases of the product lifecycle [17], [18].”
MethodCox, C., Gopsill, J., & Hicks, B. (2021) · Proceedings of the Design Society · doi:10.1017/pds.2021.91 · Cited by 2
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MethodHistorical Perspective of the Development of Digital Twins
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BackgroundInfluentialReal-time communication between PLC and Dymola for virtual commissioning application
Tebani, K., Plateaux, R., Puyenchet, C., Penas, O., Baroux, C., & Limou, S. (2020) · 2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET) · doi:10.1109/ic_aset49463.2020.9318223 · Cited by 2
“For example, we can mention the following developed approaches: Digital Twin [8], [9], model checking [10], [11], virtual commissioning [12], [13].”
BackgroundMethodThe Evolution from Digital Mock-Up to Digital Twin
Dai, S., Zhao, G.-H., Yu, Y., & Bao, Q.-W. (2020) · International Conference on Machine Learning and Intelligent Systems · doi:10.3233/faia200781 · Cited by 2
“From DMU to”
A Decentralized Structure for the Digital Shadows of Internet of Production
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Simulation of Vertical and Horizontal Integration of Cyber-Physical Systems
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BackgroundAn Application of a Digital Twin to Robotic System Design for an Unstructured Environment
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“Extending the usefulness of a simulation past BOL is predicted to be a significant area of research in the near future [7].”
BackgroundLeinonen, E., Firouzian, A., Partanen, C., & Pulli, P. (2019) · International Conference on Engineering, Technology and Innovation · doi:10.1109/ice.2019.8792663 · Cited by 2
“According to [21], Digital Twin approach can be seen as the next wave of modeling from a simulation point of view (Figure 1).”
Hierarchical Simulation of Production Systems
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“These systems help to realize the proposed digital twin [1] by integrating all relevant information and evaluating the actual and future dynamics of the manufacturing process under volatile boundary conditions.”
BackgroundSavarino, P., Abramovici, M., & Göbel, J. (2018) · Product Lifecycle Management · doi:10.1007/978-3-030-01614-2_36 · Cited by 2
Entwicklungstendenzen für die Produktionsarbeit von morgen
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“So wird Autonomie innerhalb der Produktion ermöglicht [7].”
BackgroundThe Design of Environment Monitoring Systems Based on Digital Twins in Smart Home
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“The DT will build a closed loop between the physical and virtual worlds [5-7].”
BackgroundChanging Manufacturing Landscape: From a Factory to a Network
Michelsen, K.-E., Collan, M., Savolainen, J., & Ritala, P. (2021) · Handbook of Smart Materials, Technologies, and Devices · doi:10.1007/978-3-030-58675-1_2-1 · Cited by 2
ROBOPPRESSO: Design and Implementation of Robot-Barista Services Using COBOT and IoT
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“그동안 공장과 비를 이용한 방법 로봇 프로그래밍 과정 [12] 과 현재와 미 래의 제조 환경을 변화시킬 수 있는 잠재력을 가진 Digital Twin [13] 은 시스템의 안정적인 운영과 관리에 이 바지할 것이다.”
Reliability Analysis of Cyber-Physical Systems
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A Framework for Operator Assist Apps of Automated Systems
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Self-citationConceptual design driven digital twin configuration
Wang, Y., Liu, L., & Liu, A. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818918-4.00003-8 · Cited by 3
Ditzel, L., Alexandre, P. F., Seleme, R., Silva, W. D. A., & Zattar, I. C. (2020) · Brazilian Journal of Development · doi:10.34117/bjdv6n9-158 · Cited by 2
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“Standardized information models and ontologies have been shown to streamline deployment for new equipment [11], [12].”
Zhao, Z., Mei, J., Li, H., Teng, X., & Du, J. (2026) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2026.101164
DT2: Decision-Targeted Digital Twins
Amad, H., & van der Schaar, M. (2026) · arXiv.org · doi:10.48550/arxiv.2606.25923 · Cited by 1
“DTs are appealing in many domains, such as finance (Slepneva et al., 2021), climate science (Voosen, 2020), manufacturing (Rosen et al., 2015), energy (Ismail et al., 2024), agriculture (Purcell & Neubauer, 2023), robotics (Mazumder et al., 2023), and medicine (Katsoulakis et al., 2024), due to…”
Omoloja, Y. O., Ogunwa, T., Marian, R. M., & Chahl, J. (2026) · Applied System Innovation · doi:10.3390/asi9060123 · Cited by 1
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Identifying and characterising uncertainty in digital twin engineering
Tiali, B. E. B., Creff, S., Kallel, A., & Anwer, N. (2026) · Digital Twin · doi:10.1080/27525783.2026.2668886 · Cited by 1
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“23 Continuing with digitalization, Rosen et al. 24 discussed the challenges of growing digitalization in manufacturing and opportunities for productivity, including modularity, connectivity, as well as autonomy in manufacturing systems and environments, where machines are operating intelligently…”
Archana, P., Swathi, G., Divya, N. V., Rao, M. M., Venkatesh, D., Lakshmi, D. D., Venkatasivanagaraju, S., & Manjunath, C. (2026) · Ecological Engineering & Environmental Technology · doi:10.12912/27197050/218520 · Cited by 2
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“Broader developments around digital twins and autonomous systems are outlined, where platforms like Siemens Xcelerator and Microsoft Azure are benchmarked for their effectiveness in enabling sustainable, high-fidelity simulations of manufacturing environments [79, 80].”
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Real2Sim via Active Perception with Behavior Trees Automatically Generated by VLMs
Adami, A., Zudaire, S., Carli, R., & Falco, P. (2026) · doi:10.48550/arxiv.2601.08454 · Cited by 1
“Digital twins are essential for safely testing control policies and training reinforcement learning agents prior to real-world deployment [1].”
Khatouri, S., Sahebsara, F., Hieb, M. R., & Raz, A. K. (2026) · AIAA SciTech Forum · doi:10.2514/6.2026-2122 · Cited by 1
Walton, R. B., Ciarallo, F. W., & Champagne, L. E. (2026) · International Journal of Production Economics · doi:10.1016/j.ijpe.2026.109912 · Cited by 1
Huy, P. Q., & Phuc, V. K. (2026) · SN Business & Economics · doi:10.1007/s43546-025-01041-0 · Cited by 1
“Digital twin emerges as a precursor to predictive capabilities, allowing companies to make proactive, data-driven decisions regarding their production (Rosen et al. 2015) and the consumer market.”
Anik, M. A., Rahman, A., Islam, S., Khan, M. I., Ahsan, M., & Wasi, A. T. (2026) · Digital Twins and Applications · doi:10.1049/dgt2.70039 · Cited by 1
Digital Twins and Their Applications in Modeling Different Levels of Manufacturing Systems: A Review
Saeedi, S. (2025) · arXiv.org · doi:10.48550/arxiv.2511.06119 · Cited by 1
“[38], [40], [41], [43], [44] Real-time State Monitoring and Service Providing real-time monitoring of product operation and facilitating various product services, including energy consumption analysis and user behavior analysis.”
Bahfir, S., Belkorchi, W., & Zemmouchi-Ghomari, L. (2025) · Australian Journal of Multi-Disciplinary Engineering · doi:10.1080/14488388.2025.2565021 · Cited by 1
“Historically, the idea of ‘twin’ systems originated with NASA during the Apollo program, where identical vehicles simulated conditions of space missions (Rosen et al. 2015).”
Cui, Y.-P., An, B., Wu, Z., Shang, Z.-Y., & Zhang, X. (2025) · Italian National Conference on Sensors · doi:10.3390/s25185810 · Cited by 1
“RESON et al. [16] demonstrated that simulation data could support the operation of a digital twin, showing that such data can drive digital twin models.”
Hu, C., & Zhu, J. (2025) · Wood Material Science and Engineering · doi:10.1080/17480272.2025.2551742 · Cited by 1
“Digital twins were first proposed by Professor Michael Grieves of the University of Michigan in 2003, and have been used by the US Department of Defense, NASA, Siemens, and other organizations.”
Application of Digital Twin Technology in Intelligent Digital Power Grid
Xiang, B., Chang, H., Sun, L., & Ye, Y. (2025) · 2025 8th Asia Conference on Energy and Electrical Engineering (ACEEE) · doi:10.1109/aceee66257.2025.11148644 · Cited by 1
“In 2015, Roland Rosen et al. [14] considered digital twins to be entities capable of quickly responding to events, autonomously executing advanced tasks, and possessing decision-making, coordination, and execution capabilities, as well as interacting with their environment in the real world.”
A Zhuangzian Approach to the Digital Divide: Digital Twins and the Equality of Things (齊)
Cordeiro‐Rodrigues, L., & Zhang, Q. (2025) · Global Philosophy · doi:10.1007/s10516-025-09756-3 · Cited by 1
“NASA called this problem-solving approach the ‘Twin Strategy’ (Rosen et al. 2015; Miskinis 2019; Wagg et al. 2020; Hu et al. 2021).”
Al-Mistarehi, B. W., Shtayat, A., Moridpour, S., Maabreh, H., Mijwil, M. M., Imam, R., & Al-Omari, A. A. (2025) · Innovative Infrastructure Solutions · doi:10.1007/s41062-025-02108-5 · Cited by 1
“This convergence of the physical and virtual worlds is driving innovation in all sectors, making digitalization one of the main driving forces [34].”
Advancing Electrical Engineering Education with Digital Tools for Electromagnetic Characterization
Bojita, A., Buburuza, A., & Purcar, M. (2025) · 2025 34th Annual Conference of the European Association for Education in Electrical and Information Engineering (EAEEIE) · doi:10.1109/eaeeie65428.2025.11136405 · Cited by 1
“When combined with simulation platforms and sensor data, Digital Twins facilitate iterative design improvements and enable informed decision-making at every development stage [1], [7].”
A Holistic View of Digital Twin Capabilities: From Development to Achieved Value
Galera‐Zarco, C. (2025) · IEEE Technology and Engineering Management Conference - Latin America (TEMSCON LATAM) · doi:10.1109/temsconlatam65810.2025.11238399 · Cited by 1
“Moreover, technical integration capabilities involving AI, IoT devices, legacy systems, and external data sources are critical for maintaining accurate digital representations and ensuring seamless interaction within digital ecosystems [18], [19].”
Application of Modeling and Simulation in a Self-Reprogrammable Prototype of a Manufacturing System
Ferro, R., Oliveira, J. D. D., Cordeiro, G., & Ordonez, R. (2025) · Applied Sciences · doi:10.3390/app15063298 · Cited by 1
Thermal Performance Analysis of LOX/LCH4 Engine Feed Systems Using CFD Modeling
Hernandez, I., Orozco, S., Hossain, M. A., & Choudhuri, A. (2025) · Fluids · doi:10.3390/fluids10030062 · Cited by 1
Uncovering key success factors for enhanced office-site communication through digital twins
Chalipour, A., Noorzai, E., Golabchi, M., & Nourzad, S. H. H. (2025) · The TQM Journal · doi:10.1108/tqm-04-2024-0146 · Cited by 1
Using Digital Twins in the Aerospace Industry
Arsenieva, N. V., Putyatina, L. M., Тарасова, Н. В., & Tikhonov, G. V. (2025) · Russian Engineering Research · doi:10.3103/s1068798x2470360x · Cited by 1
“Since digital twins may integrate different data (for example, environmental, operational, and technological data), autonomous systems may react to changes in state as they occur [9].”
Metadata
- Authors
- Rosen, R., von Wichert, G., Lo, G., & Bettenhausen, K. D.
- Affiliations
- Siemens (Germany) (DE)
- Siemens (United States) (US)
- Corresponding author
- Rosen, Roland
- Lo, George
- Bettenhausen, Kurt D.
- Venue
- IFAC-PapersOnLine
- Publisher
- Elsevier BV
- Published
- 2015
- Volume
- 48
- Issue
- 3
- Pages
- 567-572
- ISSN
- 2405-8963 (ISSN-L)
- OpenAlex
- W2346505350
- Cited by
- 1,474
- References
- 2
- Citations by year
- 2026: 113 · 2025: 163 · 2024: 202 · 2023: 226 · 2022: 200 · 2021: 183 · 2020: 138 · 2019: 142 · 2018: 73 · 2017: 22 · 2016: 11
- FWCI
- 61.97
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- IFAC-PapersOnLine (publishedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- Industry 4.0, digital twin, future of manufacturing, future of work, industrial automation
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