Converging Telco-Grade Solutions 5G and beyond to Support Production in Industry 4.0
Source abstract
Abstract
The Industry 4.0 initiative has been showing the way for industrial production to optimize operations based on collecting, processing, and sharing data. There are new requirements on the production floor: flexible but ultra-reliable, low latency wireless communications through interoperable systems can share data. Further challenges of data sharing and storage arise when diverse systems come into play at the Manufacturing Operations Management and Business Planning & Logistics levels. The emerging complex cyber-physical systems of systems need to be engineered with care. Regarding industrial requirements, the telecommunication industry has many similarities to production—including ultra-reliability, high complexity, and having humans “in-the-loop”. The current paper aims to provide an overview of converging telco-grade solutions that can be successfully applied in the wide sense of industrial production. These toolsets range from model-driven engineering through system interoperability frameworks, 5G- and 6G-supported manufacturing, and the telco-cloud to speech recognition in noisy environments.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Digital Transformation in Industry · IoT and Edge/Fog Computing · Flexible and Reconfigurable Manufacturing Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics (BME), 1117 Budapest, Hungary
Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics (BME), 1117 Budapest, Hungary
Department of Automation and Applied Informatics, Budapest University of Technology and Economics (BME), 1117 Budapest, Hungary
Department of Electronics Technology, Budapest University of Technology and Economics (BME), 1117 Budapest, Hungary
Funding
European Programme ECSEL Joint Undertaking (JU) · NKFIH
References (100+)
Show source-provided references
1. An integrated framework for service quality, customer value, satisfaction: Evidence from China’s telecommunication industry10.1023/B:ISFI.0000046375.72726.67 ↗
2. GSMA (2022, July 26). Mobile Telecommunications Security Threat Landscape. White Paper. Available online: https://www.gsma.com/security/wp-content/uploads/2020/02/2020-SECURITY-THREAT-LANDSCAPE-REPORT-FINAL.pdf.
3. Ayers, M.L. (2012). Telecommunications System Reliability Engineering, Theory, and Practice, John Wiley & Sons.10.1002/9781118423165 ↗
4. Varga, P., and Olaszi, P. (2013, January 15–18). LTE core network testing using generated traffic based on models from real-life data. Proceedings of the 2013 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Kattankulathur, India.10.1109/ANTS.2013.6802892 ↗
5. ITU-R (2022, July 26). IMT Vision—Framework and Overall Objectives of the Future Development of IMT for 2020 and Beyond. M. 2083-0. Available online: https://www.itu.int/dms_pubrec/itu-r/rec/m/R-REC-M.2083-0-201509-I!!PDF-E.pdf.
6. Sniderman, B., Mahto, M., and Cotteleer, M.J. (2016). Industry 4.0 and Manufacturing Ecosystems, Deloitte University Press. Report.
7. Kozma, D., Varga, P., and Hegedüs, C. (2019, January 2–4). Supply Chain Management and Logistics 4.0 - A Study on Arrowhead Framework Integration. Proceedings of the 2019 8th International Conference on Industrial Technology and Management (ICITM), Cambridge, UK.10.1109/ICITM.2019.8710670 ↗
8. Soos, G., Ficzere, D., Padovani, R., Franko, A., Veress, S., and Varga, P. (2021, January 13–16). 5G Networks for Industrial Applications: The Ecosystem of NPNs. Proceedings of the IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Hyderabad, India.
9. Industrial Frameworks for Internet of Things: A Survey
10. (2020, December 29). OMA SpecWorks: Lightweight M2M (LWM2M). Available online: https://www.omaspecworks.org/what-is-oma-specworks/iot/lightweight-m2m-lwm2m/.
11. (2020, December 29). Open Connectivity Foundation: OCF Specifications. Available online: https://openconnectivity.org/specs.
12. (2020, December 29). Industrial Data Spaces Association: IDS Reference Architecture Model. Available online: https://www.internationaldataspaces.org/the-principles/.
13. (2020, December 29). Autosar Official Website. Available online: https://www.autosar.org.
14. (2020, December 29). BaSys 4.0: Basic System Industry 4.0. Available online: https://www.basys40.de.
15. (2020, December 29). Fiware: The oPen Source Platform for Our Smart Digital Future. Available online: https://www.fiware.org.
16. Making System of Systems Interoperable—The Core Components of the Arrowhead Framework10.1016/j.jnca.2016.08.028 ↗
17. Delsing, J., Eliasson, J., van Deventer, J., Derhamy, H., and Varga, P. (2016, January 12–14). Enabling IoT Automation using Local Clouds. Proceedings of the 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), Reston, VA, USA.10.1109/WF-IoT.2016.7845474 ↗
18. Hegedus, C., Varga, P., and Frankó, A. (2018, January 15–18). Secure and trusted inter-cloud communications in the arrowhead framework. Proceedings of the 2018 IEEE Industrial Cyber-Physical Systems (ICPS), Saint Petersburg, Russia.10.1109/ICPHYS.2018.8390802 ↗
19. (2020, December 29). Eclipse Arrowhead. Available online: https://projects.eclipse.org/projects/iot.arrowhead.
20. Delsing, J., Varga, P., Ferreira, L., Albano, M., Puñal Pereira, P., Eliasson, J., Carlsson, O., and Derhamy, H. (2022, July 26). The Arrowhead Framework Architecture: Arrowhead Framework. Available online: https://www.taylorfrancis.com/chapters/edit/10.1201/9781315367897-13/arrowhead-framework-architecture-jerker-delsing-pal-varga-luis-ferreira-michele-albano-pablo-pu%C3%B1al-pereira-jens-eliasson-oscar-carlsson-hasan-derhamy?context=ubx.
21. Derhamy, H., Eliasson, J., Delsing, J., Pereira, P.P., and Varga, P. (2015, January 8–11). Translation error handling for multi-protocol SOA systems. Proceedings of the 2015 IEEE 20th Conference on Emerging Technologies Factory Automation (ETFA), Luxembourg.10.1109/ETFA.2015.7301473 ↗
22. Kozma, D., Soos, G., and Varga, P. (2019, January 22–25). Supporting Digital Production, Product Lifecycle and Supply Chain Management in Industry 4.0 by the Arrowhead Framework—A Survey. Proceedings of the IEEE International Conference on Industrial Informatics (INDIN), Helsinki-Espoo, Finland.10.1109/INDIN41052.2019.8972216 ↗
23. Supporting Digital Supply Chains by IoT Frameworks: Collaboration, Control, Combination10.36244/ICJ.2020.4.4 ↗
24. Enabling high-level application development for the Internet of Things10.1016/j.jss.2015.01.027 ↗
25. Hudak, P. (2022, July 26). Domain Specific Languages. Available online: http://cs448h.stanford.edu/DSEL-Little.pdf.
26. Selic, B., and Gérard, S. (2014). An Introduction to UML Profiles. Modeling and Analysis of Real-Time and Embedded Systems with UML and MARTE, Available online: https://www.sciencedirect.com/science/article/pii/B978012416619600002X?via%3Dihub.10.1016/B978-0-12-416619-6.00002-X ↗
27. Dhouib, S., Cuccuru, A., Fèvre, F.L., Li, S., Maggi, B., Paez, I., Rademarcher, A., Rapin, N., Tatibouet, J., and Tessier, P. (2022, July 26). Papyrus for IoT—A Modeling Solution for IoT. Available online: https://ido2016.sciencesconf.org/122755/20161108_IoTNokia_vfinal.pdf.
28. IEC 61499 Architecture, Engineering Methodologies and Software Tools
29. (2020, December 03). IEC61499 IMPLEMENTATIONS. Available online: https://www.iec61499.de/tools.htm.
30. Strasser, T., Rooker, M., Ebenhofer, G., Zoitl, A., Sunder, C., Valentini, A., and Martel, A. (2008, January 13–16). Framework for Distributed Industrial Automation and Control (4DIAC). Proceedings of the 2008 6th IEEE International Conference on Industrial Informatics, Daejeon, Korea.10.1109/INDIN.2008.4618110 ↗
31. (2020, December 03). Eclipse Vorto. Available online: https://www.eclipse.org/vorto/.
32. Nguyen, X., Tran, H.T., Baraki, H., and Geihs, K. (2015, January 14–16). FRASAD: A framework for model-driven IoT Application Development. Proceedings of the IEEE 2nd World Forum on Internet of Things (WF-IoT), Milan, Italy.10.1109/WF-IoT.2015.7389085 ↗
33. Model-Based Software Engineering to Tame the IoT Jungle10.1109/MS.2017.11 ↗
34. Harrand, N., Fleurey, F., Morin, B., and Husa, K.E. (2016, January 2–7). ThingML: A Language and Code Generation Framework for Heterogeneous Targets. Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems, Palais du Grand Large, Saint Malo, Brittany, France.10.1145/2976767.2976812 ↗
35. Vasilevskiy, A., Morin, B., Haugen, Ø., and Evensen, P. (2016, January 19–21). Agile development of home automation system with ThingML. Proceedings of the 2016 IEEE 14th International Conference on Industrial Informatics (INDIN), Poitiers, France.10.1109/INDIN.2016.7819183 ↗
36. Fleurey, F., and Morin, B. (2017, January 5–7). ThingML: A Generative Approach to Engineer Heterogeneous and Distributed Systems. Proceedings of the 2017 IEEE International Conference on Software Architecture Workshops (ICSAW), Gothenburg, Sweden.10.1109/ICSAW.2017.63 ↗
37. Alves, M.P., Delicato, F.C., and Pires, P.F. (2017, January 4–6). IoTA-MD: A Model-Driven Approach for Applying QoS Attributes in the Development of the IoT Systems. Proceedings of the Symposium on Applied Computing, Marrakech, Morocco.10.1145/3019612.3019800 ↗
38. (2020, December 03). OMG MDA. Available online: https://www.omg.org/mda/.
39. Nepomuceno, T., Carneiro, T., Maia, P.H., Adnan, M., Nepomuceno, T., and Martin, A. (April, January 30). AutoIoT: A framework based on user-driven MDE for generating IoT applications. Proceedings of the 35th Annual ACM Symposium on Applied Computing, Brno, Czech Republic.
40. (2020, December 30). MagicDraw. Available online: https://www.nomagic.com/products/magicdraw.
41. Kulcsár, G., Koltai, K., Tanyi, S., Péceli, B., Horváth, Á., Micskei, Z., and Varga, P. (2020, January 20–24). From Models to Management and Back: Towards a System-of-Systems Engineering Toolchain. Proceedings of the NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium, Budapest, Hungary.10.1109/NOMS47738.2020.9110310 ↗
42. (2020, December 03). Unified Modeling Language). Available online: https://www.omg.org/spec/UML/2.5/About-UML/.
43. (2020, October 20). Systems Modeling Language. Available online: https://sysml.org/.
44. Thramboulidis, K., Bochalis, P., and Bouloumpasis, J. (2017, January 22–25). A framework for MDE of IoT-based manufacturing cyber-physical systems. Proceedings of the IoT’17, Linz, Austria.10.1145/3131542.3131554 ↗
45. Thramboulidis, K., and Christoulakis, F. (2015). UML4IoT-A UML profile to exploit IoT in cyber-physical manufacturing systems. arXiv.10.1016/j.compind.2016.05.010 ↗
46. Costa, B., Pires, P.F., and Delicato, F.C. (September, January 31). Modeling IoT Applications with SysML4IoT. Proceedings of the 2016 42th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), Limassol, Cyprus.10.1109/SEAA.2016.19 ↗
47. (2020, December 03). Systems Modeling Language Requirement Diagram. Available online: https://sysml.org/sysml-faq/what-is-requirement-diagram.html.
48. (2020, December 03). OMG MARTE. Available online: https://www.omg.org/spec/MARTE/About-MARTE/.
49. (2020, December 03). Eclipse Sirius. Available online: https://www.eclipse.org/sirius/.
50. (2020, December 03). Eclipse Xtext. Available online: https://www.eclipse.org/Xtext/.
51. (2020, December 03). UML Profile for Modeling QoS and FT Characteristics and Mechanisms Specification (QoS&FT). Available online: https://www.omg.org/spec/QFTP/1.1/PDF.
52. (2020, December 03). PrismTech. Available online: http://www.prismtech.com/.
53. (2020, December 03). MicroEJ’s Operating System. Available online: https://www.microej.com/product/vee/.
54. (2020, December 03). 4diac FORTE. Available online: https://www.eclipse.org/4diac/en_rte.php.
55. Steinberg, D., Budinsky, F., Paternostro, M., and Merks, E. (2009). EMF: Eclipse Modeling Framework 2.0, Addison-Wesley Professional. [2nd ed.].
56. Rapin, N. (2016, January 23–30). Reactive Property Monitoring of Hybrid Systems with Aggregation. Proceedings of the RV, Madrid, Spain.10.1007/978-3-319-46982-9_28 ↗
57. (2020, December 03). VIATRA. Available online: https://www.eclipse.org/viatra/.
58. Wang, X., and Gao, L. (2020). Development of Industry 4.0. When 5G Meets Industry 4.0, Springer.10.1007/978-981-15-6732-2_3 ↗
59. Gandhi, P., Sharma, R., and Maheshwari, A. (2019, January 21–23). Creating Internet of Things for the Benefit of Indian Society. Proceedings of the 2019 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET), Chennai, India.10.1109/WiSPNET45539.2019.9032716 ↗
60. Ericsson (2018). 5G estimated to reach 1.5 billion subscriptions in 2024—Ericsson Mobility Report. IEEE Veh. Technol. Mag., 14, 4–10.10.1109/MVT.2019.2919852 ↗
61. (2022, March 08). Mobile Subscriptions Outlook. Available online: https://www.ericsson.com/en/reports-and-papers/mobility-report/dataforecasts/mobile-subscriptions-outlook.
62. ITU-R (2022, July 26). Minimum requirements related to technical performance for IMT-2020 radio interface(s). Report M.2410-0, ITU-R. Available online: https://www.itu.int/pub/R-REP-M.2410-2017.
63. The shift to 6G communications: Vision and requirements10.1186/s13673-020-00258-2 ↗
64. Zhao, Y., Yu, G., and Xu, H. (2019). 6G Mobile Communication Network: Vision, Challenges and Key Technologies. arXiv.10.1360/N112019-00033 ↗
65. Padhi, P.K., and Charrua-Santos, F. (2021). 6G Enabled Industrial Internet of Everything: Towards a Theoretical Framework. Appl. Syst. Innov., 4.10.3390/asi4010011 ↗
66. Mogyorósi, F., Revisnyei, P., Pašić, A., Papp, Z., Törös, I., Varga, P., and Pašić, A. (2022). Positioning in 5G and 6G Networks—A Survey. Sensors, 22.10.3390/s22134757 ↗
67. Jiang, J. (2017, January 13–17). An improved Cyber-Physical Systems architecture for Industry 4.0 smart factories. Proceedings of the 2017 International Conference on Applied System Innovation (ICASI), Sapporo, Japan.10.1109/ICASI.2017.7988589 ↗
68. Schweichhart, K. (2022, July 26). Reference Architectural Model Industrie 4.0 (RAMI 4.0). An Introduction. Available online: https://www.plattform-i40.
69. Potentials of the asset administration shell of Industrie 4.0 for service-oriented business models10.1016/j.procir.2017.03.009 ↗
70. Sharma, R., and Villányi, B. (2020, January 2–4). Two-Tier analyzed content filtering based Data Management Architecture in Industry 4.0. Proceedings of the 2020 IEEE 15th International An improved Cyber-Physical Systems architecture Conference of System of Systems Engineering (SoSE), Budapest, Hungary.10.1109/SoSE50414.2020.9130464 ↗
71. A method to align a manufacturing execution system with Lean objectives10.1080/00207543.2010.548409 ↗
72. Agent learning in autonomic manufacturing execution systems for enterprise networking10.1016/j.cie.2012.06.004 ↗
73. Legat, C., Lamparter, S., and Vogel-Heuser, B. (2013). Knowledge-based technologies for future factory engineering and control. Service Orientation in Holonic and Multi Agent Manufacturing and Robotics, Springer.10.1007/978-3-642-35852-4_23 ↗
74. RFID-enabled real-time manufacturing execution system for mass-customization production10.1016/j.rcim.2012.08.001 ↗
75. Real-time data acquisition system and HMI for MES10.1007/s12206-012-0615-0 ↗
76. RFID-enabled indoor positioning method for a real-time manufacturing execution system using OS-ELM10.1016/j.neucom.2015.05.120 ↗
77. Redundancy and scalability for virtualized MES systems with programmable infrastructure10.1016/j.compind.2015.08.011 ↗
78. Implementing a WebAPP-based Software Framework for Manufacturing Execution Systems10.1016/j.ifacol.2015.06.112 ↗
79. Agent-based communication to map and exchange shop floor data between MES and material flow simulation based on the open standard CMSD10.1016/j.ifacol.2016.07.796 ↗
80. Toward a cloud-based manufacturing execution system for distributed manufacturing10.1016/j.compind.2014.01.015 ↗
81. Towards mixed reality in SCADA applications10.1016/j.ifacol.2015.06.450 ↗
82. Arica, E., and Powell, D. (2017, January 10–13). Status and future of manufacturing execution systems. Proceedings of the 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore.10.1109/IEEM.2017.8290242 ↗
83. Koch, M.T., Baars, H., Lasi, H., and Kemper, H.G. (2010, January 12–15). Manufacturing Execution Systems and Business Intelligence for Production Environments. Proceedings of the AMCIS, Lima, Peru.
84. Schmidt, A., Otto, B., and Österle, H. (2011). A functional reference model for manufacturing execution systems in the automotive industry. Wirtsch. Proc., 302–311.
85. Manufacturing execution systems: A vision for managing software development10.1016/j.jss.2014.11.015 ↗
86. Agent-based manufacturing execution systems for short-series production scheduling10.1016/j.compind.2016.07.009 ↗
87. An overview of next-generation manufacturing execution systems: How important is MES for industry 4.0?10.1016/j.promfg.2019.02.083 ↗
88. Viable system model for manufacturing execution systems10.1016/j.procir.2013.06.016 ↗
89. Wang, M., Dai, Q., Zhang, X., Luo, X., and Zhong, R. (2010, January 17–19). A RFID-enabled MES for real-time pharmaceutical manufacturing supervision. Proceedings of the 2010 IEEE International Conference on RFID-Technology and Applications, Guangzhou, China.10.1109/RFID-TA.2010.5529858 ↗
90. Manufacturing execution through e-Factory system10.1016/j.procir.2012.07.101 ↗
91. An ISA-95-based manufacturing intelligence system in support of lean initiatives10.1007/s00170-012-4223-z ↗
92. Grauer, M., Karadgi, S.S., Metz, D., and Schäfer, W. (2010, January 23–25). An Approach for Real-Time Control of Enterprise Processes in Manufacturing using a Rule-Based System. Proceedings of the MKWI, Göttingen, Germany.10.17875/gup2010-1403 ↗
93. Distributed control of production systems10.1016/j.engappai.2009.05.001 ↗
94. Paredes, F., Herrojo, C., Mata-Contreras, J., Moras, M., Núñez, A., Ramon, E., and Martín, F. (2018). Near-field chipless radio-frequency identification (RFID) sensing and identification system with switching reading. Sensors, 18.10.3390/s18041148 ↗
95. Ateya, A.A., Muthanna, A., Gudkova, I., Abuarqoub, A., Vybornova, A., and Koucheryavy, A. (2018). Development of intelligent core network for tactile internet and future smart systems. J. Sens. Actuator Netw., 7.10.3390/jsan7010001 ↗
96. Edge computing in 5G: A review10.1109/ACCESS.2019.2938534 ↗
97. Computing, caching, and communication at the edge: The cornerstone for building a versatile 5G ecosystem10.1109/MCOM.2017.1700105 ↗
98. Energy-efficient offloading for mobile edge computing in 5G heterogeneous networks10.1109/ACCESS.2016.2597169 ↗
99. Living on the edge: The role of proactive caching in 5G wireless networks10.1109/MCOM.2014.6871674 ↗
100. Huang, S.C., Luo, Y.C., Chen, B.L., Chung, Y.C., and Chou, J. (2017, January 22–25). Application-aware traffic redirection: A mobile edge computing implementation toward future 5G networks. Proceedings of the 2017 IEEE 7th International Symposium on Cloud and Service Computing (SC2), Kanazawa, Japan.10.1109/SC2.2017.11 ↗