Online Validation of Simulation-Based Digital Twins Exploiting Time Series Analysis

Recently, the development of new technologies within the Industry 4.0 revolution enabled to increase the digitization level of manufacturing plants. To benefit from the functionalities of digital twins, it is essential to guarantee a correct alignment between the physical system and the associated digital model along the whole system life cycle, and to assess the validity of the digital model online. Traditional validation techniques cannot be applied for such purpose because of the restrictive assumptions and the need of large amounts of data. This work proposes a novel online validation method to assess the correctness of Discrete Event Simulation models. Validation is done by treating shop-floor data as sequences, and measuring the similarity between the data streams from the physical system and its corresponding digital model. The proposed method has been tested via offline experiments and with an application within a digital twin architecture exploiting a lab-scale manufacturing system.