Towards Digital Twins Cloud Platform: Microservices and Computational Workflows to Rule a Smart Factory
Abstract
The concept of "Industry 4.0" considers smart factories as data-driven and knowledge enabled enterprise intelligence. In such kind of factory, manufacturing processes and final products are accompanied by virtual models -- Digital Twins. To support Digital Twins concept, a simulation model for each process or system should be implemented as independent computational service. The only way to implement an orchestration of a set of independent services and provide scalability for simulation is to use a cloud computing platform as a provider of the computing infrastructure. In this paper, we describe a Digital Twin-as-a-Service (DTaaS) model for simulation and prediction of industrial processes using Digital Twins.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
By means of APIs, a set of physical objects, through their logical object counterparts, can be made interoperable within a complex environment to cooperate and achieve specific business results.
“By means of APIs, a set of physical objects, through their logical object counterparts, can be made interoperable within a complex environment in order to cooperate and achieve specific business results [181].”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [181]
No citation lists for this paper
No citation lists for this paper yet — checked again daily.
References 4 · Cited by 60
- Authors
- Borodulin, K., Radchenko, G., Shestakov, A., Sokolinsky, L., Tchernykh, A., & Prodan, R.
- Affiliations
- South Ural State University (RU)
- CICESE Research Center, Ensenada, Mexico
- Universität Innsbruck (AT)
- Venue
- Proceedings of the10th International Conference on Utility and Cloud Computing
- Publisher
- ACM
- Published
- 2017-12-05
- Pages
- 209-210
- OpenAlex
- W2771835742
- Cited by
- 60
- References
- 4
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 7 · 2023: 8 · 2022: 10 · 2021: 6 · 2020: 11 · 2019: 6 · 2018: 5
- FWCI
- 8.84
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE/ACM International Conference on Utility and Cloud Computing (UCC) (publishedVersion)
- Funders
- Russian Foundation for Basic Research (15-29-07959)
- Act 211 Government of the Russian Federation (02.A03.21.0011)
- Österreichische Forschungsförderungsgesellschaft (5077019)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
- Keywords
- digital twin, cloud platform, Industry 4.0, smart factory, industrial process simulation, service orchestration, scalability, computational services
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
