The application of advanced computing technologies to process and analyse data to extract knowledge is crucial to meet the system’s complexity and condition changes. On one side, modelling and simulation techniques can be used to create virtual environments, associated with the digital twin concept, where the system model can be exercised according to different scenarios and consequently to design the most optimized strategies, saving costs and time while minimizing the deployment risks and reducing development cycles. On another hand, extracting knowledge from available data requires the use of AI techniques that uncover previously unknown patterns and derive useful models, supporting, e.g., fault detection, diagnosis and prediction.

The use of highly scalable big data repositories and parallel processing power of HPC clusters, contribute to cope with the ubiquitous digitalization of processes, workflows and data in modern society.