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A Cyber-Physical Systems Paper Survey About the Concept, Architecture and Challenges for the Deployment within the Concept of Industry 4.0

References [1] http://industry4.sk - Sova Group portal about the Industry 4.0 revolution [Online]. [Accessed: 03-2019] Available at http://industry4.sk . [2] JIRKOVSKÝ, V. 2017. Semantic integration in the context of cyber-physical systems. Dissertation thesis. [3] TANUSKA, P., SPENDLA, L., KEBISEK, M., VAZAN, P., HRCKA, L. 2017. Data Integration and Transformation Proposal for Big Data Analyses in Automotive Industry. In: 21st IEEE International Conference on Intelligent Engineering Systems 2017 (INES 2017) , Larnaca, pp. 97 – 102, ISBN 978

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Brief Overview of Modelling Methods, Life-Cycle and Application Domains of Cyber-Physical Systems

R eferences [1] P. Gao, R. Hensley, and A. Zielke, “A road map to the future for the auto industry,” McKinsey Quarterly , October 2014. [2] E. A. Lee, “CPS Foundations,” Proceedings of the 47th Design Automation Conference , DAC ‘10, New York, pp. 737–742, 2010. [3] E. A. Lee, “Cyber Physical Systems: Design Challenges,” In Proceedings of the 11th Symposium on Object Oriented Real-Time Distributed Computing , IEEE Computer Society, Washington, pp. 363–369, 2008. [4] V. Gunes, S. Peter, T. Givargis, and F. Vahid, “A Survey on Concepts

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Anomaly detection techniques in cyber-physical systems

Abstract

Nowadays, when multiple aspects of our life depend on complex cyber-physical systems, automated anomaly detection, prevention and handling is a critical issue that inuence our security and quality of life. Recent catastrophic events showed that manual (human-based) handling of anomalies in complex systems is not recommended, automatic and intelligent handling being the proper approach. This paper presents, through a number of case studies, the challenges and possible solutions for implementing computer-based anomaly detection systems.

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A Review of Recent Reference Architectures for Cyber-Physical Systems, in the Industry 4.0 Era

Abstract

With the uptake of the IoT in the industrial domain, a whole new range of cyber-physical systems has emerged; Industry 4.0 is the title given to this technological domain of highly interconnected, data-rich systems. To aid the development of such systems, a range of reference architectures has been developed throughout the years. This paper reviews a number of recent reference architectures, detailing their essential traits as well as identifying aspects that need to be further explored in order to obtain reference architectures better tuned to generating cyber-physical social systems.

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Suitability of OPC UA for distributed energy monitoring

References Baheti, R., & Gill, H. (2011). Cyber-physical systems. The impact of control technology , 12 (1), 161–166. Crockford, D. (2006). The application/json media type for javascript object notation (json) (No. No. RFC 4627). ElMaraghy, H. A. (2005). Flexible and reconfigurable manufacturing systems paradigms. International journal of flexible manufacturing systems , 17 (4), 261–276. Hunkeler, U., Truong, H. L., & Stanford-Clark, A. (2008). MQTT-S—A publish/subscribe protocol for Wireless Sensor Networks. Communication systems

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Fourth industrial revolution: a way forward to attain better performance in the textile industry

. Therefore, the fourth industrial revolution is key to the promotion of organisational performance. Industry 4.0 has important elements, such as big data, cyber-physical systems (CPS), the interoperability, the Internet of Things (IoT) and a smart city. The industrial revolution is mostly based on these five factors. However, the current study examined the effect of three major factors, namely, CPS, the interoperability and a smart city (a smart factory, a smart product) on the production and services of textile companies in Malaysia. These three elements of Industry 4

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Main Requirements of a Cyber Physical Production System Demonstrator

References 1. E. V. G. D. V. Z. D. Mourtzis, “Cyber-Physical Systems and Education 4.0 –The Teaching Factory 4.0 Concept,” Procedia Manufacturing, vol. 23, pp. 129-134, 2018. 2. “ SmartFactory KL,” [Online]. Available: https://smartfactory.de . [Accessed 2019]. 3. A. P. J. P. Iris Gräßler, “Creation of a Learning Factory for Cyber Physical Production Systems,” Procedia CIRP, vol. 54, pp. 107-112, 2016. 4. R. J. B. G. E. J. N. Zsolt Kemeny, “The MTA SZTAKI Smart Factory: platform for research and project-oriented skill development in

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State of the Art in the Healthcare Cyber-physical Systems/ Veselības aizsardzības kiberfizikālo sistēmu apskats Современное состояние медицинских кибер-физических систем

References [1] “Cyber-Physical Systems Week” [Online]. Available: http://www.cpsweek.org/ [Accessed: Sept. 1, 2014]. [2] D. Patterson, J. Hennessy, Computer Organization and Design: The Hardware Ssoftware Interface. 5th edition. Morgan Kaufmann, 2013. [3] “Cyber-Physical Systems” [Online]. Available: http://cyberphysicalsystems.org/ [Accessed: Sept. 1, 2014]. [4] A. Milenkovic, C. Otto, E. Jovanov, “Wireless sensor networks for personal health monitoring: issues and an implementation,” Computer

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Internet of Things in the Context of Industry 4.0: An Overview

-2805. Baheti, R., & Gill, H. (2011). Cyber-physical systems. The Impact of Control Technology, T. Samad and AM Annaswamy. IEEE Control Systems Society , 1 . Bauer, H., Baur, C., Mohr, D., Tschiesner, A., Weskamp, T., Alicke, K., & Wee, D. (2016). Industry 4.0 after the initial hype–Where manufacturers are finding value and how they can best capture it. McKinsey Digital . Bhardwaj, S., Jain, L., & Jain, S. (2010). Cloud computing: A study of infrastructure as a service (IAAS). International Journal of engineering and information Technology , 2 (1), 60

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Present state and future application of smart technologies in manufacturing processes

-markit-digital-orbit-brochure.pdf Kim, S., & Park, S., 2017. CPS(Cyber Physical System) based Manufacturing System Optimizatio, Procedia Computer Science, 122, 518–524. https://doi.org/10.1016/j.procs.2017.11.401 Li, B., Hou, B., Yu, W., Lu, X., & Yang, C., 2017. Applications of artificial intelligence in intelligent manufacturing , A review. Frontiers of Information Technology & Electronic Engineering, 18(1), 86–96. https://doi.org/10.1631/FITEE.1601885 Lu, Y., & Ju, F., 2017. S mart Manufacturing Systems based on Cyber-physical Manufacturing Services (CPMS) , IFAC-PapersOnLine, 50

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