Virtual, Digital and Hybrid Twins: A New Paradigm in Data-Based Engineering and Engineered Data

Abstract

Engineering is evolving in the same way than society is doing. Nowadays, data is acquiring a prominence never imagined. In the past, in the domain of materials, processes and structures, testing machines allowed extract data that served in turn to calibrate state-of-the-art models. Some calibration procedures were even integrated within these testing machines. Thus, once the model had been calibrated, computer simulation takes place. However, data can offer much more than a simple state-of-the-art model calibration, and not only from its simple statistical analysis, but from the modeling and simulation viewpoints. This gives rise to the the family of so-called twins: the virtual, the digital and the hybrid twins. Moreover, as discussed in the present paper, not only data serve to enrich physically-based models. These could allow us to perform a tremendous leap forward, by replacing big-data-based habits by the incipient smart-data paradigm.

How to tell the difference between a model and a digital twin

“…An alternative approach to improving computational efficiency for models based on partial differential equations is the application of model order reduction (MOR) methods [23]. The approach seeks to characterise the system being modelled in terms of a small number of functions or "modes".…”

Digital twins: development and implementation challenges within Moroccan context

“…This section of the survey aimed to identify the perception of the context in regards to the notion of digital twins, and the definitions concluded through the state of the art [46]. Through the responses we were able to gather from the selected sample we could notice that for many of them the notion is still an abstraction, and for many industrial the notion was still unknown.…”

Exploiting data in smart factories: real-time state estimation and model improvement in metal forming mass production

“…The connection is two-sided, as press shop observations can be used for model improvement, and models can be used for real-time interpretation of these observations. Data from the press shop can be employed to identify and characterize the deviations between model and reality, that originate either from deliberate simplification or ignorance of the actual physics [1]. Advanced process models which incorporate both data from physics-based models as well as production data can be used for process monitoring, predictive maintenance and real-time process control, potentially leading to unprecedented improvements in production accuracy and efficiency.…”

“…The development of hybrid models that combine physicsbased models with real production data has the potential to tremendously impact general engineering [1] and the metal forming industry [2]. Although it is still difficult to find fully developed case studies of real-time data-driven modelling in metal forming, many researchers are already making significant steps towards this future prospect.…”

“…The key step to be taken is to determine a robust and accurate procedure for merging data from physics-based models with production data. Chinesta et al [1] review several data aggregation techniques, for the development of so-called 'Hybrid Twins'. They focus on the combination with model order reduction, as real-time feedback for process control is a main application area for these models.…”