ADMOS 2023

Interpretable and Reusable Reduced Order Models for Digital Twins in Manufactory as a Service

  • Zambrano, Valentina (Instituto Tecnológico de Aragón - ITAINNOVA)
  • Viejo, Ismael (Instituto Tecnológico de Aragón - ITAINNOVA)
  • Lopez, Guillermo (Instituto Tecnológico de Aragón - ITAINNOVA)
  • Alfonso, Jesus (Instituto Tecnológico de Aragón - ITAINNOVA)
  • Rodriguez, Jose Manuel (Instituto Tecnológico de Aragón - ITAINNOVA)
  • Beltran, Gabriel (Instituto Tecnológico de Aragón - ITAINNOVA)
  • Talasila, Prasad (Aarhus University)
  • Calvo, Susana (Instituto Tecnológico de Aragón - ITAINNOVA)

Please login to view abstract download link

The increasing interest on Digital Twins (DTs) solutions in Industry 4.0 (I4.0) is transforming industrial processes towards a more pro table and sustainable production. In an industrial environment DTs enable the creation of virtual replica of industrial products, services and processes, allowing a more effective management. The DIGITbrain project ( aims for the development of an integrated digital platform to provide Small and Medium-sized Enterprises (SMEs) access to DT technology. Within this context several use cases have been created using different types of models. We have developed models using CAELIA, an authoring tool eveloped at ITAINNOVA for Reduced Order Model (ROM) generation and management [1]. CAELIA ROMs are obtained through the Twinkle library (which can work both on dense and sparse data, and it is especially designed for unstructured data), and are based on self-adapted Tensor Rank Decomposition (TRD), for further details please refer to [2]. Moreover, we have developed real time consimulation structure linking Gazebo robot environment and controllers in Matlab using delay compensators [3]. The use case is a quarter car, as a sample for the foreseen vehicles to be integrated into a set of automated robots flot, by means of co-simulation. Such a system of robotic vehicles uses RabbitMQ for node-master communications, enabling remote control and autonomous movements. All use cases devolped at ITAINNOVA were conceived within the DIGITbrain environment, where all applications must be entirely reusable. A recombination of use case parts were proven to be reused in different scenarios, such as co-simulation and Machine Learning (ML) paradigm. REFERENCES [1] Zambrano, V., Mueller-Roemer, J., Sandberg, M., Talasila, P., Zanin, D., Larsen, P. G., ... and Stork, A. (2022). Industrial digitalization in the industry 4.0 era: Classi cation, reuse and authoring of digital models on Digital Twin platforms. Array, 14, 100176 [2] Zambrano, V., Rodríguez-Barrachina, R., Calvo, S., and Izquierdo, S. (2020). TWINKLE: A digital-twin-building kernel for real-time computer-aided engineering. SoftwareX, 11, 100419. [3] Alfonso, J., Rodriguez, J. M., Bernad, C., Beliautsou, V., Ivanov, V., and Castellanos, J. A. (2022, May). Geographically distributed real-time co-simulation of electric vehicle. In 2022 8th International Conference on Control, Decision and Information Technologies (CoDIT) (Vol. 1, pp. 1002-1007). IEEE.