The DOI matches its Crossref record.
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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In the citing paper
“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]
Citations
Cites
No references could be resolved yet.
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
Cited by
Sorted by citations
Items 1,001–1,003 of 1,003
Park, S., & Kim, K.-H. (2025) · International Conference on Information Networking · doi:10.1109/icoin63865.2025.10992851 · Cited by 2
“Docker was used to containerize the digital twin services, ensuring scalability and ease of deployment [5].”
InfluentialDriving ESG Goals Through Digital Twin Technology: A Path to Sustainable Computing
Govindaraj, J., & Selvaraj, V. (2024) · 2024 4th International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS) · doi:10.1109/icuis64676.2024.10866456 · Cited by 1
Towards Digital Twin Integrated Border Control
Tobing, V., Hamzah, M., Chew, J., & Hamdan, M. (2024) · IEEE International Conference on Computing (ICOCO) · doi:10.1109/icoco62848.2024.10928191 · Cited by 1
“During that time, the twin in Apollo’s Program was implemented in hardware form [40].”
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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