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DTMN a Modelling Notation for Digital Twins

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Enterprise Design, Operations, and Computing. EDOC 2022 Workshops (EDOC 2022)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 466))

Abstract

Modelling and developing digital twin solutions is a growing and promising trend followed by enterprises with the ambition to improve decision-making and accelerate risk assessment and production time. However, as a current emerging trend, there is no recognised standard nor a unique solution that provides support for all the characteristics of a digital twin. This article builds upon the result of a literature review that we conducted to extract the main characteristics attributed to Digital Twins. The identified characteristics guided the proposal of a Digital Twin Modelling Notation (DTMN). In this work we present the DTMN meta-model supported by a graphical modelling notation. This modelling notation can be used as a starting point to design and reason about Digital Twin solutions.

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Notes

  1. 1.

    https://www.iso.org/standard/81442.html.

  2. 2.

    https://csrc.nist.gov/publications/detail/nistir/8356/draft.

  3. 3.

    www.digitaltwinconsortium.org/.

  4. 4.

    https://www.adoxx.org/live/home.

  5. 5.

    The proposed library and additional information about DTMN are available on: https://pros.unicam.it/dtmn/.

References

  1. Alam, K.M., El-Saddik, A.: C2PS: a digital twin architecture reference model for the cloud-based cyber-physical systems. IEEE Access 5, 2050–2062 (2017)

    Article  Google Scholar 

  2. Analytics, I.: IoT platforms: the central backbone of the Internet of Things. In: White Paper (2015)

    Google Scholar 

  3. Anto Budiardjo, D.M.: Digital twin system interoperability framework. Digital Twin Consortium (2021)

    Google Scholar 

  4. Atkinson, C., Kuhne, T.: Model-driven development: a metamodeling foundation. IEEE Softw. 20(5), 36–41 (2003)

    Article  Google Scholar 

  5. Atkinson, C., Kühne, T.: Taming the complexity of digital twins. IEEE Softw. 39(2), 27–32 (2022)

    Article  Google Scholar 

  6. Ayoobkhan, M.U.A., et al.: Smart connected digital products and IoT platform with the digital twin, pp. 330–350. IGI Global (2021)

    Google Scholar 

  7. Bhattacharyya, A., Izgi, E.: Digital twin technologies for high performance manufacturing. IBM White paper (2018)

    Google Scholar 

  8. Boje, C., Guerriero, A., Kubicki, S., Rezgui, Y.: Towards a semantic construction digital twin: directions for future research. Autom. Constr. 114, 103179 (2020)

    Google Scholar 

  9. Bordeleau, F., et al.: Towards model-driven digital twin engineering: current opportunities and future challenges. In: International Conference on Systems Modelling and Management, pp. 43–54 (2020)

    Google Scholar 

  10. Botkina, D., Hedlind, M., Olsson, B., Henser, J., Lundholm, T.: Digital twin of a cutting tool. Procedia Cirp 72, 215–218 (2018)

    Article  Google Scholar 

  11. Christian, J., et al.: Model-driven digital twin construction: synthesizing the integration of cyber-physical systems with their information systems. In: Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, pp. 90–101 (2020)

    Google Scholar 

  12. Clark, T., Kulkarni, V., Whittle, J., Breu, R.: Engineering digital twin-enabled systems. IEEE Softw. 39(2), 16–19 (2022)

    Article  Google Scholar 

  13. Clark, T., Sammut, P., Willans, J.: Applied metamodelling: a foundation for language driven development. arXiv:1505.00149 (2015)

  14. Compagnucci, I., Corradini, F., Fornari, F., Polini, A., Re, B., Tiezzi, F.: Modelling notations for IoT-aware business processes: a systematic literature review. In: Del Río Ortega, A., Leopold, H., Santoro, F.M. (eds.) BPM 2020. LNBIP, vol. 397, pp. 108–121. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-66498-5_9

    Chapter  Google Scholar 

  15. Corradini, F., Fedeli, A., Fornari, F., Polini, A., Re, B.: FloWare: an approach for IoT support and application development. In: Augusto, A., Gill, A., Nurcan, S., Reinhartz-Berger, I., Schmidt, R., Zdravkovic, J. (eds.) BPMDS/EMMSAD -2021. LNBIP, vol. 421, pp. 350–365. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-79186-5_23

    Chapter  Google Scholar 

  16. Corradini, F., Fedeli, A., Fornari, F., Polini, A., Re, B.: Floware: a model-driven approach fostering reuse and customisation in IoT applications modelling and development. Softw. Syst. Model. 1–28 (2022). https://doi.org/10.1007/s10270-022-01026-9

  17. Corradini, F., Fedeli, A., Fornari, F., Polini, A., Re, B.: Towards a digital twin modelling notation. In: DASC/PiCOM/CBDCom/CyberSciTech22. IEEE (2022)

    Google Scholar 

  18. Corradini, F., Fedeli, A., Fornari, F., Polini, A., Re, B.: X-IoT: a model-driven approach for cross-platform IoT applications development. In: SAC 2022 pp. 1448–1451 (2022)

    Google Scholar 

  19. Dalibor, M., et al.: Towards a model-driven architecture for interactive digital twin cockpits. Concept. Model. 12400, 377–387 (2020)

    Article  Google Scholar 

  20. Demkovich, N., Yablochnikov, E., Abaev, G.: Multiscale modeling and simulation for industrial cyber-physical systems. In: IEEE Industrial Cyber-Physical Systems, pp. 291–296 (2018)

    Google Scholar 

  21. Dobrescu, R., Merezeanu, D., Mocanu, S.: Context-aware control and monitoring system with IoT and cloud support. Comput. Electron. Agric. 160, 91–99 (2019)

    Article  Google Scholar 

  22. Fahmideh, M., Zowghi, D.: An exploration of IoT platform development. Inf. Syst. 87, 1–25 (2020). Article number 101409

    Google Scholar 

  23. Fill, H.: Enterprise modeling: from digital transformation to digital ubiquity. In: Federated Conference on Computer Science and Information Systems, vol. 21, pp. 1–4 (2020)

    Google Scholar 

  24. Harper, K.E., Ganz, C., Malakuti, S.: Digital twin architecture and standards. IIC J. Innov. 12, 72–83 (2019)

    Google Scholar 

  25. He, Y., Guo, J., Zheng, X.: From surveillance to digital twin: challenges and recent advances of signal processing for industrial internet of things. IEEE Signal Process. 35(5), 120–129 (2018)

    Article  Google Scholar 

  26. Hoffmann, J., Heimes, P., Senel, S.: IoT platforms for the internet of production. IEEE Internet Things J. 6(3), 4098–4105 (2019)

    Article  Google Scholar 

  27. Hribernik, K., Cabri, G., Mandreoli, F., Mentzas, G.: Autonomous, context-aware, adaptive digital twins-state of the art and roadmap. Comput. Ind. 133, 103508 (2021)

    Google Scholar 

  28. Jones, D., Snider, C., Nassehi, A., Yon, J., Hicks, B.: Characterising the digital twin: a systematic literature review. J. Manuf. Sci. Technol. 29, 36–52 (2020)

    Article  Google Scholar 

  29. Kulkarni, V., Clark, T.: Towards adaptive enterprises using digital twins. In: International Conference on Research Challenges in Information Science, pp. 1–5 (2019)

    Google Scholar 

  30. Lim, K.Y.H., Zheng, P., Chen, C.: A state-of-the-art survey of digital twin: techniques, engineering product lifecycle management and business innovation perspectives. J. Intell. Manuf. 31(6), 1313–1337 (2020)

    Article  Google Scholar 

  31. Lu, Y., Liu, C., Wang, K.I., Huang, H., Xu, X.: Digital Twin-driven smart manufacturing: connotation, reference model, applications and research issues. Robot. Comput. Integr. Manuf. 61, 101837 (2020)

    Google Scholar 

  32. Madni, A.M., Madni, C.C., Lucero, S.D.: Leveraging digital twin technology in model-based systems engineering. Syst. 7, 7 (2019)

    Article  Google Scholar 

  33. Minerva, R., Lee, G.M., Crespi, N.: Digital twin in the IoT context: a survey on technical features, scenarios, and architectural models. IEEE Proc. 108(10), 1785–1824 (2020)

    Article  Google Scholar 

  34. Negri, E., Fumagalli, L., Macchi, M.: A review of the roles of digital twin in cps-based production systems. Procedia Manuf. 11, 939–948 (2017)

    Article  Google Scholar 

  35. Qi, Q., et al.: Enabling technologies and tools for digital twin. Manuf. Syst. J. 58, 3–21 (2021)

    Article  Google Scholar 

  36. Sandkuhl, K., Stirna, J.: Supporting early phases of digital twin development with enterprise modeling and capability management: requirements from two industrial cases. Enterp. Bus. Process Inf. Syst. Model. 387, 284–299 (2020)

    Google Scholar 

  37. Schroeder, G., et al.: Visualising the digital twin using web services and augmented reality. In: Conference on Industrial Informatics, pp. 522–527 (2016)

    Google Scholar 

  38. Schroeder, G.N., Steinmetz, C., Rodrigues, R.N., Henriques, R.V.B., Rettberg, A., Pereira, C.E.: A methodology for digital twin modeling and deployment for industry 4.0. Proc. IEEE 109(4), 556–567 (2021)

    Google Scholar 

  39. Semeraro, C., Lezoche, M., Panetto, H., Dassisti, M.: Digital twin paradigm: a systematic literature review. Comput. Ind. 130, 103469 (2021)

    Article  Google Scholar 

  40. Singh, M., Fuenmayor, E., Hinchy, E.P., Qiao, Y., Murray, N., Devine, D.: Digital twin: origin to future. Appl. Syst. Innov. 4(2), 1–19 (2021). Article number 36

    Google Scholar 

  41. Stark, R., Damerau, T.: Digital twin. In: Chatti, S., Tolio, T. (eds.) CIRP Encyclopedia of Production Engineering. Springer, Berlin, Heidelberg (2019). https://doi.org/10.1007/978-3-642-35950-7_16870-1

  42. Steinmetz, C., Rettberg, A., Ribeiro, F.G.C., Schroeder, G., Pereira, C.E.: Internet of Things ontology for digital twin in cyber physical systems. In: Symposium on Computing Systems Engineering, pp. 154–159 (2018)

    Google Scholar 

  43. Talkhestani, B.A., Jazdi, N., Schloegl, W., Weyrich, M.: Consistency check to synchronize the digital twin of manufacturing automation based on anchor points. Procedia CIRP 72, 159–164 (2018)

    Article  Google Scholar 

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

    Google Scholar 

  45. Tao, F., Zhang, H., Liu, A., Nee, A.Y.C.: Digital twin in industry: state-of-the-art. IEEE Trans. Ind. Inf. 15(4), 2405–2415 (2019)

    Article  Google Scholar 

  46. Trauer, J.E.A.: What is a digital twin? - definitions and insights from an industrial case study in technical product development. In: DESIGN Conference, vol. 1, pp. 757–766 (2020)

    Google Scholar 

  47. VanDerHorn, E., Mahadevan, S.: Digital twin: generalization, characterization and implementation. Decis. Support Syst. 145, 113524 (2021)

    Google Scholar 

  48. Velosa, A., Middleton, P.: Emerging Technologies: Revenue Opportunity Projection of Digital Twins, Gartner, Stamford, Conn. (2022). Accessed June 2022

    Google Scholar 

  49. Vrabič, R., Erkoyuncu, J.A., Butala, P., Roy, R.: Digital twins: understanding the added value of integrated models for through-life engineering services. Procedia Manuf. 16, 139–146 (2018). int. Conf. on Through-life Engineering Services

    Google Scholar 

  50. Davis, W.S.: HIPO hierarchy plus input-process-output. the information system consultant’s handbook: systems analysis and design, pp. 503–511 (1988)

    Google Scholar 

  51. Xiao, R., Wu, Z., Wang, D.: A finite-state-machine model driven service composition architecture for Internet of Things rapid prototyping. Futur. Gener. Comput. Syst. 99, 473–488 (2019)

    Article  Google Scholar 

  52. Zhang, C., Xu, W., Liu, J., Liu, Z., Zhou, Z., Pham, D.T.: A reconfigurable modeling approach for digital twin-based manufacturing system. Procedia Cirp 83, 118–125 (2019)

    Article  Google Scholar 

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Acknowledgements

This work has been partially supported by the MIUR project PRIN “Fluidware” (A Novel Approach for Large-Scale IoT Systems, n. 2017KRC7KT) and by Marche Region in implementation of the financial programme POR MARCHE FESR 2014-2020, project “Miracle” (Marche Innovation and Research fAcilities for Connected and sustainable Living Environments), CUP B28I19000330007.

Author information

Authors and Affiliations

  1. Computer Science Division, University of Camerino, Camerino, Italy

    Flavio Corradini, Arianna Fedeli, Fabrizio Fornari, Andrea Polini & Barbara Re

Authors
  1. Flavio Corradini
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  2. Arianna Fedeli
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  3. Fabrizio Fornari
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  4. Andrea Polini
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  5. Barbara Re
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Corresponding author

Correspondence to Fabrizio Fornari .

Editor information

Editors and Affiliations

  1. University of Twente, Enschede, The Netherlands

    Tiago Prince Sales

  2. TU Wien, Vienna, Austria

    Henderik A. Proper

  3. University of Twente, Enschede, The Netherlands

    Giancarlo Guizzardi

  4. Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

    Marco Montali

  5. Free University of Bozen-Bolzano, Bolzano, Italy

    Fabrizio Maria Maggi

  6. University of Twente, Enschede, The Netherlands

    Claudenir M. Fonseca

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Corradini, F., Fedeli, A., Fornari, F., Polini, A., Re, B. (2023). DTMN a Modelling Notation for Digital Twins. In: Sales, T.P., Proper, H.A., Guizzardi, G., Montali, M., Maggi, F.M., Fonseca, C.M. (eds) Enterprise Design, Operations, and Computing. EDOC 2022 Workshops . EDOC 2022. Lecture Notes in Business Information Processing, vol 466. Springer, Cham. https://doi.org/10.1007/978-3-031-26886-1_4

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  • DOI: https://doi.org/10.1007/978-3-031-26886-1_4

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