Engineering of Next Generation Cyber-Physical Automation System Architectures

  • Matthias FoehrEmail author
  • Jan Vollmar
  • Ambra Calà
  • Paulo Leitão
  • Stamatis Karnouskos
  • Armando Walter Colombo


Cyber-Physical-Systems (CPS) enable flexible and reconfigurable realization of automation system architectures, utilizing distributed control architectures with non-hierarchical modules linked together through different communication systems. Several control system architectures have been developed and validated in the past years by research groups. However, there is still a lack of implementation in industry. The intention of this work is to provide a summary of current alternative control system architectures that could be applied in industrial automation domain as well as a review of their commonalities. The aim is to point out the differences between the traditional centralized and hierarchical architectures to discussed ones, which rely on decentralized decision-making and control. Challenges and impacts that industries and engineers face in the process of adopting decentralized control architectures are discussed, analysing the obstacles for industrial acceptance and the new necessary interdisciplinary engineering skills. Finally, an outlook of possible mitigation and migration actions required to implement the decentralized control architectures is addressed.


CPS in production Future automation systems Industrial systems engineering Migration strategy System architectures 



The authors would like to thank the European Commission for the support, and the partners of the EU Horizon 2020 project PERFoRM (2016b) for the fruitful discussions. The PERFoRM project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 680435.


  1. ACATECH: Cyber-Physical Systems: driving force for innovation in mobility, health, energy and production. Tech. rep., ACATECH – German National Academy of Science and Engineering. (2011)
  2. ANSI/ISA: ANSI/ISA-95.00.01-2010 (IEC 62264-1 Mod) Enterprise-Control System Integration – Part 1: Models and Terminology. (2010)
  3. Antzoulatos, N., Castro, E., Scrimieri, D., Ratchev, S.: A multi-agent architecture for plug and produce on an industrial assembly platform. Prod. Eng. Res. Devel. 8 (6), 773–781 (2014); doi:10.1007/s11740-014-0571-xCrossRefGoogle Scholar
  4. Broy, M., Schmidt, A.: Challenges in engineering Cyber-Physical Systems. Computer 47 (2), 70–72 (2014); doi:10.1109/mc.2014.30CrossRefGoogle Scholar
  5. Castellini, P., Cristalli, C., Foehr, M., Leitão, P., Paone, N., Schjolberg, I., Tjonnas, J., Turrin, C., Wagner, T.: Towards the integration of process and quality control using multi-agent technology. In: IECON 2011 – 37th Annual Conference of the IEEE Industrial Electronics Society (2011); doi: 10.1109/iecon.2011.6119347
  6. Colombo, A.W., Karnouskos, S.: Towards the factory of the future: a service-oriented cross-layer infrastructure. In: ICT Shaping the World: A Scientific View, pp. 65–81. European Telecommunications Standards Institute/Wiley, New York (2009)Google Scholar
  7. Colombo, A.W., Karnouskos, S., Mendes, J.M.: Factory of the future: a service-oriented system of modular, dynamic reconfigurable and collaborative systems. In: Springer Series in Advanced Manufacturing, pp. 459–481. Springer, London (2010); doi: 10.1007/978-1-84996-119-6_15
  8. Colombo, A.W., Karnouskos, S., Bangemann, T.: A system of systems view on collaborative industrial automation. In: 2013 IEEE International Conference on Industrial Technology (ICIT) (2013); doi:10.1109/icit.2013.6505980Google Scholar
  9. Colombo, A.W., Bangemann, T., Karnouskos, S.: IMC-AESOP outcomes: paving the way to collaborative manufacturing systems. In: 2014 12th IEEE International Conference on Industrial Informatics (INDIN) (2014a); doi:10.1109/indin.2014.6945517Google Scholar
  10. Colombo, A.W., Bangemann, T., Karnouskos, S., Delsing, J., Stluka, P., Harrison, R., Jammes, F., Martínez Lastra, J.L. (eds.): Industrial Cloud-based Cyber-Physical Systems: The IMC-AESOP Approach. Springer, New York (2014b)Google Scholar
  11. Delsing, J., Eliasson, J., Kyusakov, R., Colombo, A.W., Jammes, F., Nessaether, J., Karnouskos, S., Diedrich, C.: A migration approach towards a SOA-based next generation process control and monitoring. In: IECON 2011 – 37th Annual Conference of the IEEE Industrial Electronics Society (2011); doi: 10.1109/iecon.2011.6120045
  12. Delsing, J., Rosenqvist, F., Carlsson, O., Colombo, A.W., Bangemann, T.: Migration of industrial process control systems into service oriented architecture. In: IECON 2012 – 38th Annual Conference on IEEE Industrial Electronics Society, Montreal, QC (2012); doi: 10.1109/iecon.2012.6389039
  13. DIN: Reference Architecture Model Industrie 4.0 (RAMI4.0). Tech. rep., Deutsches Institut für Normung (DIN). (2016)
  14. Friedrich, J., Scheifele, S., Verl, A., Lechler, A.: Flexible and modular control and manufacturing system. Procedia CIRP 33, 115–120 (2014); doi:10.1016/j.procir.2015.06.022CrossRefGoogle Scholar
  15. Goncalves, G., Reis, J., Pinto, R., Alves, M., Correia, J.: A step forward on intelligent factories: a smart sensor-oriented approach. In: Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA) (2014); doi:10.1109/etfa.2014.7005227Google Scholar
  16. IEC: White paper factory of the future. Tech. rep., IEC – International Electrotechnical Commission (2015)Google Scholar
  17. Kagermann, H., Wahlster, W., Helbig, J.: Securing the future of German manufacturing industry: recommendations for implementing the strategic initiative industrie 4.0. Tech. rep., ACATECH – German National Academy of Science and Engineering. (2013)
  18. Karnouskos, S.: Efficient sensor data inclusion in enterprise services. Datenbank-Spektrum 9 (28), 5–10 (2009)Google Scholar
  19. Karnouskos, S.: Realising next-generation web service-driven industrial systems. Int. J. Adv. Manuf. Technol. 60 (1–4), 409–419 (2011); doi:10.1007/s00170-011-3612-zGoogle Scholar
  20. Karnouskos, S., Colombo, A.W.: Architecting the next generation of service-based SCADA/DCS system of systems. In: 37th Annual Conference of the IEEE Industrial Electronics Society (IECON 2011), Melbourne (2011); doi:10.1109/iecon.2011.6119279Google Scholar
  21. Karnouskos, S., Somlev, V.: Performance assessment of integration in the cloud of things via web services. In: 2013 IEEE International Conference on Industrial Technology (ICIT) (2013); doi:10.1109/icit.2013.6505983Google Scholar
  22. Karnouskos, S., Baecker, O., de Souza, L.M.S., Spiess, P.: Integration of SOA-ready networked embedded devices in enterprise systems via a cross-layered web service infrastructure. In: 2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007), pp. 293–300 (2007); doi:10.1109/efta.2007.4416781Google Scholar
  23. Karnouskos, S., Guinard, D., Savio, D., Spiess, P., Baecker, O., Trifa, V., de Souza, L.M.S.: Towards the real-time enterprise: service-based integration of heterogeneous SOA-ready industrial devices with enterprise applications. IFAC Proc. Vol. 42 (4), 2131–2136 (2009); doi:10.3182/20090603-3-ru-2001.0551CrossRefGoogle Scholar
  24. Karnouskos, S., Savio, D., Spiess, P., Guinard, D., Trifa, V., Baecker, O.: Real-World Service Interaction with Enterprise Systems in Dynamic Manufacturing Environments. Springer Series in Advanced Manufacturing, pp. 423–457. Springer, New York (2010); doi: 10.1007/978-1-84996-119-6_14
  25. Karnouskos, S., Colombo, A.W., Bangemann, T.: Trends and challenges for cloud-based industrial cyber-physical systems. In: Industrial Cloud-based Cyber-Physical Systems: The IMC-AESOP Approach, pp. 231–240, Springer, New York (2014a); doi: 10.1007/978-3-319-05624-1_11
  26. Karnouskos, S., Colombo, A.W., Bangemann, T., Manninen, K., Camp, R., Tilly, M., Sikora, M., Jammes, F., Delsing, J., Eliasson, J., Nappey, P., Hu, J., Graf, M.: The IMC-AESOP architecture for cloud-based industrial Cyber-Physical Systems. In: Industrial Cloud-Based Cyber-Physical Systems, pp. 49–88. Springer, New York (2014b); doi: 10.1007/978-3-319-05624-1_3
  27. Lee, E.A.: Cyber physical systems: design challenges. In: 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC), pp. 363–369 (2008); doi:10.1109/ISORC.2008.25Google Scholar
  28. Leitão, P., Karnouskos, S.: A survey on factors that impact industrial agent acceptance. In: Industrial Agents: Emerging Applications of Software Agents in Industry, pp. 401–429. Elsevier, Amsterdam (2015a); doi:10.1016/b978-0-12-800341-1.00022-xGoogle Scholar
  29. Leitão, P., Karnouskos, S. (eds.): Industrial Agents: Emerging Applications of Software Agents in Industry. Elsevier, Amsterdam (2015b)Google Scholar
  30. Leitão, P., Barbosa, J., Vrba, P., Skobelev, P., Tsarev, A., Kazanskaia, D.: Multi-agent system approach for the strategic planning in ramp-up production of small lots. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics (2013); doi:10.1109/smc.2013.807Google Scholar
  31. Leitão, P., Rodrigues, N., Turrin, C., Pagani, A.: Multi-agent system integrating process and quality control in a factory producing laundry washing machines. IEEE Trans. Ind. Inf. 11 (4), 879–886 (2015); doi:10.1109/tii.2015.2431232CrossRefGoogle Scholar
  32. Leitão, P., Colombo, A.W., Karnouskos, S.: Industrial automation based on cyber-physical systems technologies: Prototype implementations and challenges. Comput. Ind. 81, 11–25 (2016a); doi:10.1016/j.compind.2015.08.004CrossRefGoogle Scholar
  33. Leitão, P., Karnouskos, S., Ribeiro, L., Lee, J., Strasser, T., Colombo, A.W.: Smart agents in industrial Cyber–Physical Systems. Proc. IEEE 104 (5), 1086–1101 (2016b); doi:10.1109/jproc.2016.2521931CrossRefGoogle Scholar
  34. MacKenzie, C.M., Laskey, K., McCabe, F., Brown, P.F., Metz, R.: Reference model for service oriented architecture 1.0. (2006)
  35. McKinsey: Industry 4.0: How to navigate digitization of the manufacturing sector. Tech. rep., McKinsey Digital. (2015)
  36. Onori, M., Maffei, A., Durand, F.: The IDEAS plug and produce system. In: International Conference on Advanced Manufacturing Engineering and Technologies, NewTech (2013)Google Scholar
  37. PERFoRM: Definition of the system architecture. Tech. rep., Deliverable D2.2, PERFoRM project. (2016a)
  38. PERFoRM: Production harmonizEd Reconfiguration of Flexible Robots and Machinery (PERFoRM) project, European Commission, horizon 2020 programme. (2016b)
  39. Sayed, M.S., Lohse, N., Sondberg-Jeppesen, N., Madsen, A.L.: SelSus: Towards a reference architecture for diagnostics and predictive maintenance using smart manufacturing devices. In: 2015 IEEE 13th International Conference on Industrial Informatics (INDIN), Institute of Electrical and Electronics Engineers (IEEE) (2015); doi:10.1109/indin.2015.7281990Google Scholar
  40. SOCRADES: Service-Oriented Cross-layer infRAstructure for Distributed smart Embedded devices (SOCRADES) project, European Commission, FP6 Programme. (2016)
  41. Stokic, D., Scholze, S., Barata, J.: Self-learning embedded services for integration of complex, flexible production systems. In: IECON 2011 – 37th Annual Conference of the IEEE Industrial Electronics Society (2011); doi:10.1109/iecon.2011.6119346Google Scholar
  42. Taisch, M., Colombo, A.W., Karnouskos, S., Cannata, A.: SOCRADES roadmap: The future of SOA-based factory automation. Tech. rep., SOCRADES Project. (2009)
  43. Webb, P., Asif, S.: Advanced flexible automation cell. In: 6th Innovation for Sustainable Aviation in a Global Environment (2011)Google Scholar
  44. Wooldridge, M.: An Introduction to Multi-Agent Systems. Wiley, Harlow (2002)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Matthias Foehr
    • 1
    Email author
  • Jan Vollmar
    • 1
  • Ambra Calà
    • 1
  • Paulo Leitão
    • 2
  • Stamatis Karnouskos
    • 3
  • Armando Walter Colombo
    • 4
  1. 1.Siemens AG Corporate TechnologyErlangenGermany
  2. 2.Polytechnic Institute of BragançaBragançaPortugal
  3. 3.SAPWalldorfGermany
  4. 4.University of Applied Sciences Emden/LeerEmdenGermany

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