Digital Twin Requirements in the Context of Industry 4.0
Digital Twin (DT) is being considered a significant enabler for Industry 4.0 initiatives. Within Industry 4.0, the amount of digital product information generated and collected over the entire lifecycle has been growing. Current information and communication technologies, including data storage, data processing, and wireless data transmission, may be leveraged to digitally mirror the lifecycle of a corresponding physical product with increasing level of detail. A DT creates a link between physical products and their virtual models with more comprehensive data and accumulation of knowledge. Therefore, a DT may be applied to enhance simulation, traceability and to support the offering of value-added services along the lifecycle. However, the definition of a DT and its requirements are not yet fully established. The characteristics a DT model should possess to be widely used in manufacturing remains an open question in the literature. The concept is still broad and dependent on the lifecycle stage and industry sector of application. Therefore, the objective of this paper is to propose an initial synthesis of DT requirements based on a literature review and industry interviews. The literature review focuses on the content analysis of papers published from 2010 to 2018 and indexed in the ISI Web of Science database. The interviews were conducted with industry representatives in Brazil. The results show that DT requirements are related to real-time data, integration, and fidelity. Besides, it shows that industry requirements are close to literature and the actual implementation of DT is the future of research in this field.
KeywordsDigital Twin Industry 4.0 Product lifecycle management
The authors thank the Coordination for the Improvement of Higher Education Personnel (Capes), the Brazilian National Council for Scientific and Technological Development (CNPq), and the German Research Foundation (DFG) for supporting related projects. The authors also thank the companies involved for providing real case applications.
- 1.Hobsbawn, E.: The Age of Revolution (1961)Google Scholar
- 2.Kagermann, H., Wahlster, W., Helbig, J.: Recommendations for implementing the strategic initiative INDUSTRIE 4.0. Final report of the Industrie 4.0 Working Group 82 (2013)Google Scholar
- 6.Zhang, H., Liu, Q., Chen, X., et al.: A digital twin-based approach for designing and decoupling of hollow glass production line. IEEE Access 1 (2017). https://doi.org/10.1109/access.2017.2766453
- 11.Anderl, R.: Industrie 4.0 - advanced engineering of smart products and smart production. In: 19° Seminário Internacional de Alta Tecnologia, Piracicaba (2014)Google Scholar
- 12.Piccard, A., Anderl, R.: Integrated component data model for smart production planning. In: 19° Seminário Internacional de Alta Tecnologia, Piracicaba (2014)Google Scholar
- 13.Brettel, M., Friederichsen, N., Keller, M., Rosenberg, M.: How virtualization, decentralization and network building change the manufacturing landscape: an Industry 4.0 perspective. Int. J. Mech. Aerosp. Ind. Mechatron. Eng. 8, 37–44 (2014)Google Scholar
- 22.Canedo, A.: Industrial IoT lifecycle via digital twins. In: Proceedings of the Eleventh IEEE/ACM/IFIP International Conference on Hardware/Software Codesign System Synthesis - CODES 2016, vol. 1 (2016). https://doi.org/10.1145/2968456.2974007
- 29.Vachálek, J., Bartalský, L., Rovný, O., et al.: The digital twin of an industrial production line within the Industry 4. 0 concept. In: 21st International Conference on Process Control, pp. 258–262 (2017)Google Scholar