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The requirements of Industry 4.0 determine the necessity to change thinking in the field of production development, adopted management methods and modernisation of production resources. When planning the implementation of a new production system (or retrofit), it is possible to use the RAMI 4.0 reference model, which was published in April 2015 by the VDI/VDE Society Measurement and Automatic Control. A key aspect of modern industrial systems is connectivity and trouble-free data exchange. In the case of data exchange, the basic element holding back the development of Industry 4.0 is the lack of standardisation, as well as the lack of interoperability between IIoT network nodes. Modern IIoT applications require high network throughput, low latency and reliability. In view of such guidelines, efficient communication standards and specialised equipment are required. Edge Computing is one of the most important technology trends of the 21st century that will play a key role in the IIoT market. Due to the diversity of available technologies and solutions, no universal standards have been developed to date that can be referred to when planning, building and implementing new applications. The article presents an overview of the most popular industrial communication protocols and their systematisation in terms of meet the requirements for IIoT devices.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
art. no. 2023307
Opis fizyczny
Bibliogr. 21 poz., rys., tab.
Twórcy
autor
- APA Group, Tarnogorska 251 St., 44-105 Gliwice, Poland
autor
- Silesian University of Technology, Faculty of Mechanical Engineering, Konarskiego 18A St., 44-100 Gliwice, Poland
Bibliografia
- 1. Mychlewicz C, Piątek Z. From industry 4.0 to smart factory. Siemens 2017; 5: 32.
- 2. Dziurdzia M, Janiszewski M, Gęborys P, Gawrysiak M, Jankovic-Żelazna A. Industry 4.0, the challenges of modern production. PwC; 4.
- 3. Chunquan L, Yaqiong C, Yuling S. A review of industrial big data for decision making in intelligent manufacturing. Engineering Science and Technology, an International Journal 2022; 29: 1-16. https://doi.org/10.1016/j.jestch.2021.06.001.
- 4. Pollak A, Hilarowicz A, Walczak M, Gąsiorek D. A framework of action for implementation of industry 4.0. An empirically based research. Sustainability 2020; 12.
- 5. Baptista LF, Barata J. Piloting industry 4.0 in SMEs with RAMI 4.0: an enterprise architecture approach. Procedia Computer Science 2021; 192: 2826-2835. https://doi.org/10.1016/j.procs.2021.09.053.
- 6. Benešl T, Kaczmarczyk V, Sýkora T, Arm J, Dvorský P, Husák M, Marcoň P, Bradáč Z. Asset administration shell - manufacturing processes energy optimization. IFAC – PapersOnLine 2022; 55(4): 334-339. https://doi.org/10.1016/j.ifacol.2022.06.055.
- 7. Alessandria E, Seno L, Vitturi S. Performance analysis of Ethernet/IP networks. IFAC Proceedings Volumes 2007; 40(22): 391-398. https://doi.org/10.3182/20071107-3-FR-3907.00054.
- 8. Ferrari P, Flammini A, Vitturi S. Performance analysis of PROFINET networks. Computer Standards & Interfaces 2006; 28(4): 369-385. https://doi.org/10.1016/j.csi.2005.03.008.
- 9. Dahlman E, Parkvall S, Sköld J. The next generation wireless access technology. 5G NR (Second Edition): Springer Elsevier; 2021. https://doi.org/10.1016/B978-0-12-822320-8.00005-2.
- 10. https://elearning.przemyslprzyszlosci.gov.pl/slownikpojec/protokol-komunikacyjny/.
- 11. Elamanov S, Son H, Flynn B, Ki Yoo S, Dilshad N, Song JS. Interworking between Modbus and internet of things platform for industrial services. Digital Communications and Networks; 2022. https://doi.org/10.1016/j.dcan.2022.09.013.
- 12. Schleipen M, Gilani SS, Bischoff T, Pfrommer J. OPC UA & Industrie 4.0 - Enabling technology with high diversity and variability. Procedia CIRP 2016; 57: 315-320. https://doi.org/10.1016/j.procir.2016.11.055.
- 13. Mishra B, Kertesz A. The use of MQTT in M2M and IoT systems: a survey. IEEE Access 2020; 8: 201071- 201086. https://doi.org/10.1109/ACCESS.2020.3035849.
- 14. Atmoko RA, Riantini R, Hasin MK. IoT real time data acquisition using MQTT protocol. Journal of Physics: Conference Series 2017; 853: 1-6. https://doi.org/10.1088/1742-6596/853/1/012003.
- 15. Bhardwaj A, Kaushik K, Bharany S; Rehman AU, Hu YC, Eldin ET, Ghamry NA. IIoT: traffic data flow analysis and modeling experiment for smart IoT devices. Sustainability 2022; 14(14645): 1-18. https://doi.org/10.3390/su142114645.
- 16. Tashtoush YM, Darweesh DA, Husari G, Darwish OA, Darwish Y, Issa LB, Ashqar HI. Agile approaches for cybersecurity systems, IoT and intelligent transportation. IEEE Access 2022; 10: 1360-1375. https://doi.org/10.1109/ACCESS.2021.3136861.
- 17. Zhang T, Li Y, Philip Chen CL. Edge computing and its role in industrial internet: methodologies, applications, and future directions. Information Sciences 2021; 557: 34 - 65. https://doi.org/10.1016/j.ins.2020.12.021.
- 18. Yi S, Li C, Li Q. A survey of fog computing: concepts, applications and issues. Mobidata '15: Proceedings of the 2015 Workshop on Mobile Big Data 2015; 15: 37-42. https://doi.org/10.1145/2757384.2757397.
- 19. https://nazca40.pl/en/nazca-4-0-industry-iiotplatform-english/.
- 20. Mychlewicz C, Piątek Z. Siemens report - from industry 4.0 to smart factory. Siemens 2017; 22-24.
- 21. Van Glabbeek R, Deac D, Perale T, Steenhaut K, Braeken A. Flexible and efficient security framework for many-to-many communication in a publish/subscribe architecture. Sensors 2022; 22: 7391.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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