Generation of predictive knowledge for the early detection of anomalies in industrial manufacturing processes.

The DETECTA project focuses on the generation of predictive knowledge for the early detection of anomalies in industrial manufacturing processes. 

The main objective is to anticipate incidents caused by component failures or malfunctions in industrial component manufacturing environments. Digitalization and connectivity introduce new risks, but cybersecurity technologies still have limitations in heterogeneous industrial environments. 

The DETECTA project collaborates with knowledge centers and industrial process experts to adopt a hybrid knowledge model to characterize and detect anomalies. 

The project addresses several technological challenges, such as the non-intrusive characterization of processes, the analysis of availability indicators and protection measures in SME environments, the creation of learning models in black box systems to predict failures and cyber-attacks, the analysis of the challenges of the convergence of Operational Technologies and Information Technologies, and the evaluation of an industrial case in an SME in the manufacturing sector.