Digital twin technology is rapidly evolving within the Industry 4.0 realm and is emerging as a powerful tool for companies to transform themselves and proceed towards digitalisation of their operations. Often, digital twin technology embeds some artificial intelligent models, in the attempt of achieving a so-called ‘Intelligent Digital Twin’, with even more enhanced capabilities of data analysis, fault detection, decision-making support, prediction, and many more. In line with the advantages coming from the synergy between digital twin and advanced deep learning algorithms, a Convolutional Neural Network has been developed within this thesis work, thought as a component of a broader Digital Twin comprehensive framework for Resistance Spot Welding quality monitoring.