Abstract
A framework for integrating in-process quality inspection for laser welding applications is presented here. The proposed hardware and software architecture was developed in the context of the ZELD-e EIT-funded project and is able to deliver a fully working system for monitoring and quality assessment of laser welding applications, towards the quality improvement and rapid certification of the joints, paired with predictive/preventing control capabilities based on a long-term optimization schema through the utilization of Artificial Intelligence (AI) and Decision Support System technologies in the context of process energy optimization.