The paper presents a smart modular architecture that allows for a traditional production plant to be transformed into a supervised, fully integrated, and monitored system. The proposed approach is based on using commercial devices to create an industrial Internet of Things network connected to PLCs, CNCs, and sensors on every single plant machinery. The novelty is in the smart architecture, software implementation of the supervision, and monitoring. A base software code, easily adaptable to different applications, allows for highly innovative man-machine interfaces to be created. Therefore, the monitoring of the embedded systems can be obtained through multiple remotable interfaces. The effectiveness of the proposed methodology is demonstrated experimentally on a case study during a mechatronics industry exhibition.

1. [1] G. Eason, B. Noble, and I. N. Sneddon, “On certain integrals of Lipschitz-Hankel type involving products of Bessel functions,” Phil. Trans. Roy. Soc. London, Vol.A247, pp. 529-551, April 1955.
2. [2] D. Singh, G. Tripathi, and A. J. Jara, “A Survey of Internet-of-Things: Future Vision, Architecture, Challenges and Services,” Proc. IEEE World Forum on Internet of Things 2014, Seoul, pp. 287-292, 2014.
3. [3] NIST, “Foundations for innovation in cyber-physical systems: Workshop report,” Transl. J. Magn. Japan, Vol.2, pp. 740-741, 2013.
4. [4] F. Aggogeri, N. Pellegrini, and R. Adamini, “Functional Design in Rehabilitation: Modular Mechanisms for Ankle Complex,” Applied Bionics and Biomechanics, Art. 9707801, 2016.
5. [5] S. J. Hu, “Evolving paradigms of manufacturing: from mass production to mass customization and personalization,” Procedia CIRP, Vol.7, No.0, pp. 3-8, 2013.
6. [6] M. Brettel, N. Friederichsen, M. Keller, and M. Rosenberg, “How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective Industry 4.0,” Int. J. of Information and Communication Engineering, Vol.8, No.1, 2014.
7. [7] X. Yuan, T. Yazawa, H. Ito, T. Otsubo, Y. Maeda, and R. Yamada, “High-efficiency milling of steam turbine blade,” Int. J. Automation Technol., Vol.10, No.6, pp. 993-999, 2016.
8. [8] A. E. Lee, “Cyber physical systems: design challenges,” IEEE Int. symposium object/component/service-oriented real-time distributed computing, Orlando, pp. 363-369, 2008.
9. [9] M. H. Miraz and M. Ali, “A Review on Internet of Things (loT), Internet of Everything (IoE) and Internet of Nano Things (IoNT),” Proc. Internet Technologies and Applications (ITA), pp. 219-224, 2015.
10. [10] N. Benamar, A. Jara, L. Ladid, and D. E. Ouadghiri, “Challenges of the Internet of Things: IPv6 and Network Management,” Proc. Eighth Int. Conf. on Innovative Mobile and Internet Services in Ubiquitous Computing, pp. 328-333, 2014.
11. [11] L. Atzori, A. Iera, and G. Morabito, “The Internet of Things: A Survey,” Computer networks, Vol.54, No.15, pp. 2787-2805, Oct. 2010.
12. [12] J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, “Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions,” Future Generation Computer Systems, pp. 1645-1660, Feb. 2013.
13. [13] A. Borboni, F. Aggogeri, A. Merlo, N. Pellegrini, and C. Amici, “PKM mechatronic clamping adaptive device,” Int. J. of Advanced Robotic Systems, Vol.12, art. 42, 2015.
14. [14] J. A. Stankovic, “Research directions for the internet of things,” IEEE Internet of Things J., Vol.1, No.1, pp. 3-9, Mar. 2014.
15. [15] C. B. Zamfirescu, B. C. Pirvu, J. Schlick, and D. Zuehlke, “Preliminary insides for an anthropocentric cyber-physical reference architecture of the smart factory,” Stud. Inform. Control, Vol.22, pp. 269-278, 2013.
16. [16] S. Poslad, “Ubiquitous computing smart devices, smart environments and smart interaction,” Chippenham: Wiley, 2009.
17. [17] H. Zhuge, “Interactive semantics,” Artif. Intell., Vol.174, pp. 190-204, 2010.
18. [18] G. Biamino, “A semantic model for socially aware objects,” Adv. Int. Things, Vol.2, No.3, pp. 47-55, 2012.
19. [19] M. Brettel, N. Friederichsen, M. Keller, and N. Rosenberg, “How virtualization, decentralization and network building change the manufacturing landscape: an industry 4.0 perspective,” Int. J. Sci. Eng. Technol., Vol.8, No.1, pp. 37-44, 2014.
20. [20] M. Serpelloni, M. Tiboni, M. Lancini, S. Pasinetti, A. Vertuan, and M. Gobbo, “Preliminary study of a robotic rehabilitation system driven by EMG for hand mirroring,” Proc. IEEE Int. Symposium on Medical Measurements and Applications (MeMeA), May 15-18, Benevento, Italy, 2016.
21. [21] M. Tiboni, G. Legnani, M. Lancini, M. Serpelloni, M. Gobbo, and D. Fausti, “ERRSE: Elbow robotic rehabilitation system with an EMG-based force control,” Mechanisms and Machine Science, Vol.49, pp. 892-900, 2018.
22. [22] J. C. R. Licklider, “Man-computer symbiosis,” IRE Trans. Human Factors Electron, Vol.HFE-1, pp. 4-11, 1960.
23. [23] S. Runde, A. Fay, S. Schmitz, and U. Epple, “Wissensbasierte Systeme im Engineering der Automatisierungstechnik,” Automatisierungstechnik, Vol.59, No.1, pp. 42-49, 2011.
24. [24] R. Drath and M. Barth, “Concept for interoperability between independent engineering tools of heterogeneous disciplines,” 2011 IEEE 16th Conf. on Emerging Technologies & Factory Automation (ETFA), pp. 1-8, 2011.
25. [25] W. Schafer and H. Wehrheim, “The Challenges of Building Advanced Mechatronic Systems,” Proc. of 2007 Future of Software Engineering, pp. 72-84, 2007.
26. [26] T. Biagetti and S. Enrico, “Automatic diagnostics and prognostics of energy conversion processes via knowledge-based systems,” Energy, Vol.29, No.12, pp. 2553-2572, 2004.
27. [27] F. Klocke, S. Kratz, T. Auerbach, S. Gierglings, G. Wirtz, and D. Veselovac, “Process Monitoring and Control of Machining Operations,” Int. J. Automation Technol., Vol.5, No.3, pp. 403-411, 2011.
28. [28] F. Aggogeri, A. Borboni, A. Merlo, N. Pellegrini, and R. Ricatto, “Real-time performance of mechatronic PZT module using active vibration feedback control,” Sensors (Switzerland), Vol.16, No.10, art. No.1577, 2016.
29. [29] E. Kunii, T. Matsura, S. Fukushige, and Y. Umeda, “Proposal of Consistency Management Method Between Product and its Life Cycle for Supporting Life Cycle Design,” Int. J. Automation Technol., Vol.6, No.3, pp. 272-278, 2012.
30. [30] J. Y. Chai, T. Sakaguchi, and K. Shirase, “Dynamic Controls of Genetic Algorithm Scheduling in Supply Chain,” Int. J. Automation Technol., Vol.4, No.2, pp. 169-177, 2010.
31. [31] H. Hibino, Y. Fukuda, and T. Kaihara, “A Synchronization Mechanism with Shared Storage Model for Distributed Manufacturing Simulation Systems,” Int. J. Automation Technol., Vol.9. No.3, pp. 248-260, 2015.
32. [32] M. Tiboni and C. Remino, “Condition monitoring of a mechanical indexing system with artificial neural networks,” 1st World Congress on Condition Monitoring (WCCM 2017), London, June 13-16, 2017.
33. [33] N. A. Duffie and R. S. Piper, “Non-hierarchical control of a flexible manufacturing cell,” Robot. Comput.-Integr. Manuf., Vol.3, No.2, pp. 175-179, 1987.
34. [34] N. Pellegrini, “A thermo-dynamical constitutive model based on kinetic approach for shape memory materials,” Advances Materials Research, Vol.651, pp. 42-48, 2013.
35. [35] N. A. Duffie, R. Chitturi, and J. I. Mou, “Fault-tolerant heterarchical control of heterogeneous manufacturing system entities,” J. Manuf. Syst., Vol.7, No.4, pp. 315-328, 1988.
36. [36] C. A. Perani, “POWER-KI Preludio: a programming language,” June 1, 2012. ISBN-13: 978-8890739217
37. [37] M. P. Lukas, “Distributed control systems: Their evaluation and design,” Van Nostrand Reinhold Co., 1986.