The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Industry 4.0 and the New Simulation Modelling Paradigm
Open accessAbstract
Background and Purpose: The aim of this paper is to present the influence of Industry 4.0 on the development of the new simulation modelling paradigm, embodied by the Digital Twin concept, and examine the adoption of the new paradigm via a multiple case study involving real-life R&D cases involving academia and industry. Design: We introduce the Industry 4.0 paradigm, presents its background, current state of development and its influence on the development of the simulation modelling paradigm. Further, we present the multiple case study methodology and examine several research and development projects involving automated industrial process modelling, presented in recent scientific publications and conclude with lessons learned. Results: We present the research problems and main results from five individual cases of adoption of the new simulation modelling paradigm. Main lesson learned is that while the new simulation modelling paradigm is being adopted by big companies and SMEs, there are significant differences depending on company size in problems that they face, and the methodologies and technologies they use to overcome the issues. Conclusion: While the examined cases indicate the acceptance of the new simulation modelling paradigm in the industrial and scientific communities, its adoption in academic environment requires close cooperation with industry partners and diversification of knowledge of researchers in order to build integrated, multi-level models of cyber-physical systems. As shown by the presented cases, lack of tools is not a problem, as the current generation of general purpose simulation modelling tools offers adequate integration options.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
About The Importance of Autonomy and Digital Twins for the Future of Manufacturing
Rosen, R., von Wichert, G., Lo, G., & Bettenhausen, K. D. (2015) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2015.06.141 · Cited by 1,474
Cited by
Lim, K. Y. H., Zheng, P., & Chen, C.-H. (2020) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01512-w · Cited by 700
Industry 4.0 in the port and maritime industry: A literature review
de la Peña Zarzuelo, I., Freire Soeane, M. J., & López Bermúdez, B. (2020) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2020.100173 · Cited by 269
Microgrid Digital Twins: Concepts, Applications, and Future Trends
Bazmohammadi, N., Madary, A., Vasquez, J. C., Mohammadi, H. B., Khan, B., Wu, Y., & Guerrero, J. M. (2022) · IEEE Access · doi:10.1109/access.2021.3138990 · Cited by 233
Nair, M. M., Tyagi, A. K., & Sreenath, N. (2021) · 2021 International Conference on Computer Communication and Informatics (ICCCI) · doi:10.1109/iccci50826.2021.9402498 · Cited by 181
Brosinsky, C., Westermann, D., & Krebs, R. (2018) · 2018 IEEE International Energy Conference (ENERGYCON) · doi:10.1109/energycon.2018.8398846 · Cited by 165
Metadata
- Authors
- Rodič, B.
- Venue
- Organizacija
- Publisher
- Walter de Gruyter GmbH
- Published
- 2017-08-01
- Volume
- 50
- Issue
- 3
- Pages
- 193-207
- ISSN
- 1318-5454 (ISSN-L)
- 1581-1832
- OpenAlex
- W2746518050
- Cited by
- 302
- References
- 1
- FWCI
- 28.79
- Type
- journal article
- Language
- en
- Open access
- diamond
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Industry 4.0 and the New Simulation Modelling Paradigm. https://app.cochat.ai/papers/10.1515/orga-2017-0017
- The paper
- Rodič, B. (2017). Industry 4.0 and the New Simulation Modelling Paradigm. Organizacija. https://doi.org/10.1515/orga-2017-0017
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.