A six-layer architecture for the digital twin: a manufacturing case study implementation


Industry 4.0, cyber-physical production systems (CPPS) and the Internet of Things (IoT) are current focusses in automation and data exchange in manufacturing, arising from the rapid increase in capabilities in information and communication technologies and the ubiquitous internet. A key enabler for the advances promised by CPPSs is the concept of a digital twin, which is the virtual representation of a real-world entity, or the physical twin. An important step towards the success of Industry 4.0 is the establishment of practical reference architectures. This paper presents an architecture for such a digital twin, which enables the exchange of data and information between a remote emulation or simulation and the physical twin. The architecture comprises different layers, including a local data layer, an IoT Gateway layer, cloud-based databases and a layer containing emulations and simulations. The architecture can be implemented in new and legacy production facilities, with a minimal disruption of current installations. This architecture provides a service-based and real-time enabled infrastructure for vertical and horizontal integration. To evaluate the architecture, it was implemented for a small, but typical, physical manufacturing system component.

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  1. Bagheri, B. & Lee, J. (2015). Big future for cyber-physical manufacturing systems. [Online]. Available: http://www.designworldonline.com/big-future-for-cyber-physical-manufacturing-systems/. Retrieved July 05, 2017.

  2. Baheti, R., & Gill, H. (2011). Cyber-physical systems. The Impact of Control Technology,12(1), 161–166.

    Google Scholar 

  3. Baur, C. & Wee, D. (2015). Manufacturing’s next act. [Online]. Available: http://www.mckinsey.com/business-functions/operations/our-insights/manufacturings-next-act. Retrieved July 05, 2017.

  4. Borangiu, T., Oltean, E., Răileanu, S., Anton, F., Anton, S. & Iacob, I. (2020). Embedded digital twin for ARTI-type control of semi-continuous production processes. In Service oriented, holonic and multi-agent manufacturing systems for industry of the future. SOHOMA 2019. studies in computational intelligence (vol. 853, pp. 113–133). Springer, Cham.

  5. Bottani, E., Cammardella, A., Murino, T. & Vespoli, S. (2017). From the cyber-physical system to the digital twin: The process development for behaviour modelling of a cyber guided vehicle in M2M logic. In Proceedings of the summer school Francesco Turco (pp. 96–102).

  6. Cavalieri, S., & Chiacchio, F. (2013). Analysis of OPC UA performances. Computer Standards and Interfaces,36(1), 165–177.

    Article  Google Scholar 

  7. Cavalieri, S. & Cutuli, G. (2010). Performance evaluation of OPC UA. In 2010 IEEE 15th conference on emerging technologies & factory automation (ETFA 2010) (pp. 1–8).

  8. Cearley, D. (2016). Gartner’s top 10 strategic technology trends for 2017. [Online]. Available: https://www.forbes.com/sites/gartnergroup/2016/10/26/gartners-top-10-strategic-technology-trends-for-2017/#629bc186b336. Retrieved November 27, 2017.

  9. Defuse Security. (2017). Salted Password Hashing - Doing it Right. [Online]. Available: https://crackstation.net/hashing-security.htm. Retrieved March 15, 2018.

  10. Feuer, Z. & Weissman, Z. (2017). The value of the digital twin. [Online]. Available: https://community.plm.automation.siemens.com/t5/Digital-Transformations/The-value-of-the-digital-twin/ba-p/385812. Retrieved July 05, 2017.

  11. Grieves, M. (2014). Digital twin: Manufacturing excellence through virtual factory replication. Melbourne: White Paper.

    Google Scholar 

  12. Grieves, M. (2015). How A “Digital Twin” Can Warrant Products Are Built As Designed. [Online]. Available: https://www.mbtmag.com/article/2015/01/how-‘digital-twin’-can-warrant-products-are-built-designed. Retrieved July 05, 2017.

  13. H2020 - MAYA Project. (2019). Multi-disciplinArY integrated simulAtion and forecasting tools, empowered by digital continuity and continuous real-world synchronization, towards reduced time to production and optimization. [Online]. Available: http://maya-euproject.com/index.php/project. Retrieved July 19, 2019.

  14. Hoppe, S. (2017). There is no Industrie 4.0 without OPC UA. [Online]. Available: https://opcconnect.opcfoundation.org/2017/06/there-is-no-industrie-4-0-without-opc-ua/. Retrieved October 03, 2017.

  15. Kagermann, H., Helbig, J., Hellinger, A. & Wahlster, W. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Securing the future of German manufacturing industry; final report of the Industrie 4.0 Working Group.

  16. Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W. (2018). Digital Twin in manufacturing: A categorical literature review and classification. IFAC-PapersOnLine,51(11), 1016–1022.

    Article  Google Scholar 

  17. Lee, E. A. (2015). The past, present and future of cyber-physical systems: A focus on models. Sensors (Basel),15(3), 4837–4869.

    Article  Google Scholar 

  18. Lee, J., Bagheri, B., & Kao, H.-A. (2015). A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters,3, 18–23.

    Article  Google Scholar 

  19. Lee, E.A. & Seshia, S.A. (2017). Introduction to embedded systemsA cyber-physical systems approach. 2nd ed.

  20. Leitão, P., Colombo, A. W., & Karnouskos, S. (2016). Industrial automation based on cyber-physical systems technologies: Prototype implementations and challenges. Computers in Industry,81, 11–25.

    Article  Google Scholar 

  21. Liu, Y., Peng, Y., Wang, B., Yao, S., & Liu, Z. (2017). Review on cyber-physical systems. IEEE/CAA Journal of Automatica Sinica,4(1), 27–40.

    Article  Google Scholar 

  22. M.A.C. Solutions. (2017). KEPServerEX V6 OPC Server. [Online]. Available: https://www.mac-solutions.net/en/products/industrial-data-comms/opc-communications-suite/item/157-kepserverex-v6-opc-server. Retrieved November 21, 2017.

  23. Manufacturing Industry Digital Innovation Hubs (MIDIH). (2018). Functional and Modular Architecture of MIDIH CPS/IOT System (Public Version). [Online]. Available: http://midih.eu/documents/MIDIH Reference architecture.pdf. Retrieved July 19, 2019.

  24. Marr, B. (2017). What is digital twin technologyAnd why is it so important? [Online]. Available: https://www.forbes.com/sites/bernardmarr/2017/03/06/what-is-digital-twin-technology-and-why-is-it-so-important/#26203f1c2e2a. Retrieved January 22, 2018.

  25. Martin, J. (2017). The value of automation and power of the digital twin. [Online]. Available: https://newsignature.com/articles/value-automation-power-digital-twin/. Retrieved November 27, 2017.

  26. Monostori, L., Kádár, B., Bauernhansl, T., Kondoh, S., Kumara, S., Reinhart, G., et al. (2016). Cyber-physical systems in manufacturing. CIRP Annals—Manufacturing Technology,65(2), 621–641.

    Article  Google Scholar 

  27. Morgan, J., & O’Donnell, G. E. (2018). Cyber physical process monitoring systems. Journal of Intelligent Manufacturing,29(6), 1317–1328.

    Article  Google Scholar 

  28. Nakutis, Z., Deksnys, V., Jarusevicius, I., Dambrauskas, V., Cincikas, G., & Kriauceliunas, A. (2016). Round-trip delay estimation in OPC UA ServerClient communication channel. Elektronika ir Elektrotechnika,22(6), 80–84.

    Article  Google Scholar 

  29. National Institute of Standards and Technology. (2013). Foundations for innovation in cyber-physical systems. National Institute of Standards and Technology: Workshop Report.

    Google Scholar 

  30. OPC Foundation. (2015). Update for IEC 62541 (OPC UA) Published. [Online]. Available: https://opcfoundation.org/news/opc-foundation-news/update-iec-62541-opc-ua-published/. Retrieved September 28, 2017.

  31. Oracle. (2017). Digital twins for IoT applications: A comprehensive approach to implementing IoT digital twins (White Paper). Redwood Shores.

  32. Oztemel, E. & Gursev, S. (2018). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing. 29:1–56.

  33. Patel, K. T., & Chotai, N. P. (2011). Documentation and records: Harmonized GMP requirements. Journal of Young Pharmacists,3(2), 138–150.

    Article  Google Scholar 

  34. PTC Inc. (2017). ClientAce user manual. [Online]. Available: https://www.kepware.com/en-us/products/clientace/documents/clientace-manual.pdf. Retrieved March 08, 2018.

  35. Răileanu, S., Borangiu, T., Ivănescu, N., Morariu, O., & Anton, T. (2020). Integrating the digital twin of a shop floor conveyor in the manufacturing control system. In T. Borangiu, D. Trentesaux, P. Leitão, A. Giret Boggino, & V. Botti (Eds.), Service oriented, holonic and multi-agent manufacturing systems for industry of the future. SOHOMA 2019. studies in computational intelligence (Vol. 853, pp. 134–145). Cham: Springer.

    Google Scholar 

  36. Redelinghuys, A. J. H., Basson, A. H., & Kruger, K. (2019a). A six-layer digital twin architecture for a manufacturing cell. In T. Borangiu, D. Trentesaux, A. Thomas, & S. Cavalieri (Eds.), Service orientation in holonic and multi-agent manufacturing. SOHOMA 2018 studies in computational intelligence (Vol. 803, pp. 412–423). Cham: Springer.

    Google Scholar 

  37. Redelinghuys, A.J.H., Basson, A.H. & Kruger, K. 2019b. Cybersecurity Considerations for Industrie 4.0. In D. Dimitrov, D. Hagedorn-Hansen, & K. von Leipzig (Eds.) International conference on competitive manufacturing (COMA 19). Knowledge valorisation in the age of digitalization (pp. 266–271). Stellenbosch.

  38. Redelinghuys, A. J. H., Kruger, K., & Basson, A. H. (2020). A six-layer architecture for digital twins with aggregation. In T. Borangiu, D. Trentesaux, P. Leitão, A. Giret Boggino, & V. Botti (Eds.), Service oriented Holonic and multi-agent manufacturing (pp. 171–182). Cham: Springer.

    Google Scholar 

  39. Rovere, D., Pedrazzoli, P., dal Maso, G., Alge, M., & Ciavotta, M. (2019). A Centralized Support Infrastructure (CSI) to Manage CPS Digital Twin, towards the Synchronization between CPS Deployed on the Shopfloor and Their Digital Representation. In J. Soldatos, O. Lazaro, & F. Cavadini (Eds.), The digital shopfloor—Industrial automation in the industry 4.0 Era: performance analysis and applications (pp. 317–335). Denmark: River Publishers.

    Google Scholar 

  40. Salvador Palau, A., Dhada, M. H., & Parlikad, A. K. (2019). Multi-agent system architectures for collaborative prognostics. Journal of Intelligent Manufacturing,30(8), 2999–3013.

    Article  Google Scholar 

  41. Schleich, B., Anwer, N., Mathieu, L., & Wartzack, S. (2017). Shaping the digital twin for design and production engineering. CIRP Annals—Manufacturing Technology.,66(1), 141–144.

    Article  Google Scholar 

  42. Schroeder, G. N., Steinmetz, C., Pereira, C. E., & Espindola, D. B. (2016). Digital twin data modeling with automationML and a communication methodology for data exchange. IFAC-PapersOnLine,49(30), 12–17.

    Article  Google Scholar 

  43. Shafto, M., Conroy, M., Doyle, R. & Glaessgen, E. (2010). DRAFT modeling, simulation, information Technology & Processing Roadmap. Technology Area.

  44. Siemens. (2014). Plant Simulation. [Online]. Available: https://www.plm.automation.siemens.com/en/products/tecnomatix/manufacturing-simulation/material-flow/plant-simulation.shtml#lightview%26url=/en_us/Images/7541_tcm1023-4957.pdf%26title=TecnomatixPlantSimulation%26description = Simulate,visualize,analyze. Retrieved October 05, 2017.

  45. Soldatos, J., Lazaro, O. & Cavadini, F. (2019). The digital shopfloorIndustrial automation in the Industry 4.0 Era: Performance analysis and applications.

  46. Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., & Sui, F. (2018). Digital twin-driven product design, manufacturing and service with big data. International Journal of Advanced Manufacturing Technology,94(9–12), 3563–3576.

    Article  Google Scholar 

  47. Tao, F., Qi, Q., Wang, L., & Nee, A. Y. C. (2019). Digital twins and cyber–physical systems toward smart manufacturing and industry 4.0: Correlation and comparison. Engineering.,5(4), 653–661.

    Article  Google Scholar 

  48. Vachalek, J., Bartalsky, L., Rovny, O., Sismisova, D., Morhac, M. & Loksik, M. (2017). The digital twin of an industrial production line within the industry 4.0 concept. In Proceedings of the 2017 21st international conference on process control, PC 2017 (pp. 258–262).

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Redelinghuys, A.J.H., Basson, A.H. & Kruger, K. A six-layer architecture for the digital twin: a manufacturing case study implementation. J Intell Manuf 31, 1383–1402 (2020). https://doi.org/10.1007/s10845-019-01516-6

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  • Industry 4.0
  • Cyber physical systems (CPS)
  • Internet of things (IoT)
  • Digital twin
  • OPC
  • Tecnomatix