Open Access
| Issue |
ITM Web Conf.
Volume 46, 2022
International Conference on Engineering and Applied Sciences (ICEAS’22)
|
|
|---|---|---|
| Article Number | 03004 | |
| Number of page(s) | 6 | |
| Section | Artificial Intelligence in Supply Chain Management | |
| DOI | https://doi.org/10.1051/itmconf/20224603004 | |
| Published online | 06 June 2022 | |
- H. Kagermann, W. D. Lukas., & W. Wahlster, “Industry 4.0: With the Internet of Things on the Way to the 4th Industrial Revolution. VDI nachrichten, 13, 2011. [Google Scholar]
- G. Di Bona, V. Duraccio, A. Silvestri, and A. Forcina, “Validation and application of a safety allocation technique (integrated hazard method) to an aerospace prototype,” In: Proceedings of the IASTED international conference on modelling, identification, and control, MIC. pp 284–290, 2014. [Google Scholar]
- D. Falcone, A. Silvestri, G. Bona, and al, “Study and modelling of very flexible lines through simulation”, 2010. [Google Scholar]
- D. Falcone, A. Silvestri, A. Forcina, and A. Pacitto, “Modeling and simulation of an assembly line: a new approach for assignment and optimization of activities of operators,” In: MAS (The International Conference on Modeling and Applied Simulation), Rome. pp 12–14, 2011 [Google Scholar]
- A. C. Pereire, J. Dinis-Carvalho, A. C. Alves, and P. Arezes, “How Industry 4.0 can enhance Lean practices,” FME Transactions, 47(4),810-822, 2019. [CrossRef] [Google Scholar]
- K. D.Thoben, S. Wiesner, and T. Wuest, ““Industrie 4.0” and smart manufacturing-a review of research issues and application examples,” International journal of automation technology, 11(1),4-16, 2017. [CrossRef] [Google Scholar]
- J. M. Koh., M. Sak, H.X. Tan, H. Liang, F. Folianto and T. Quek, “Efficient data retrieval for large-scale smart city applications through applied Bayesian inference”, Proceedings of the 10th, 2015 [Google Scholar]
- Hans W. Ittmann1, “The impact of big data and business analytics on supply chain management”, 2014. [Google Scholar]
- F. J. Villanueva, C. Aguirre, D. Villa, M. J. Santofimia and J. C. López, “Smart City data stream visualization using Glyphs”, Proceedings of the 8th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), pp. 399-403, IEEE, Birmingham, United Kingdom, 2014. [Google Scholar]
- P. Russom, “Big Data Analytics, TDWI Best Practices Report”, Fourth Quarter, 2011. [Google Scholar]
- International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), pp. 1-6, IEEE, Singapore. [Google Scholar]
- D. NamIoT,and M. Sneps-Sneppe, “Context-aware data discovery”, In Proceedings of the 16th International Conference on Intelligence in Next Generation Networks (ICIN), pp. 134-141, IEEE, Berlin, 2012. [Google Scholar]
- A. Corradi, G. Curatola, L. Foschini, R. Ianniello, and C. R. De Rolt, “Automatic extraction of POIs in smart cities: Big data processing in ParticipAct”, Proceedings of the International Symposium on Integrated Network Management, pp. 1059-1064, IEEE, Ottawa, 2015. [Google Scholar]
- A. Mohd, and al, “Improving material quality management and manufacturing organizations system through Industry 4.0 technologies,” Materials Today: Proceeding, 2021. [Google Scholar]
- L. Atzori, A. Iera, and G. Morabito, “The internet of things: A survey,” Computer Networks, 54(15),2787–2805, 2010. [Google Scholar]
- H.S. Birkel and E. Hartmann, “Internet of things– the future of managing supply chain risks,” Supply Chain Management: An International Journal, 2020. [Google Scholar]
- H. Golpîra, “A novel Multiple Attribute Decision Making approach based on interval data using U2P- Miner algorithm,” Data Knowl. Eng. 115 116–128, 2018. [CrossRef] [Google Scholar]
- R.H. Weber, “Internet of Things–New security and privacy challenges,” Comput. Law Secur. Rev. 26 (2010) 23–30. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.