The robotic welding manufacturing of metal parts is a very important process, especially in heavy industries such as shipbuilding, oil and gas, automotive, and aerospace. There is a great variety of different techniques for manufacturing by robotic welding, and the welding operations are always in a constant process of evolution, as any advance can be significant to avoid defects during the welding process. Although a great deal of research work has been carried out in recent years, thanks to which results and reviews have been presented on this subject, the main aim of this publication is to define and review works that show the advances in the main inspection, modeling, monitoring, and automated operations during the welding process to avoid, or predictively identify, any possible defect in order to obtain an optimum degree of quality in the welding.

The reconstruction of the geometry of weld-deposited materials plays an important role in the control of the torch path in GMAW. This technique, which is classified as a direct energy deposition technology, is experiencing a new emergence due to its use in welding and additive manufacturing. Usually, the torch path is determined by computerised fabrication tools, but these software tools do not consider the geometrical changes along the case during the process. The aim of this work is to adaptively define the trajectories between layers by analysing the geometry and symmetry of previously deposited layers. The novelty of this work is the integration of a profiling laser coupled to the production system, which scans the deposited layers. Once the layer is scanned, the geometry of the deposited bead can be reconstructed and the symmetry in the geometry and a continuous trajectory can be determined. A wall was fabricated under demanding deposition conditions, and a surface quality of around 100 microns and mechanical properties in line with those previously reported in the literature are observed.

The automation of welding processes requires the use of automated systems and equipment, in many cases industrial robotic systems, to carry out welding processes that previously required human intervention. Automation in the industry offers numerous advantages, such as increased efficiency and productivity, cost reduction, improved product quality, increased flexibility and safety, and greater adaptability of companies to market changes. The field of welding automation is currently undergoing a period of profound changes due to a combination of technological, regulatory, and economic factors worldwide. Nowadays, the most relevant aspect of the welding industry is to meet customer requirements by satisfying their needs. To achieve this, the automation of the welding process through sensors and control algorithms ensures the quality of the parts and prevents errors such as porosity, unfused areas, deformations, excessive heat, etc. This paper proposes an intelligent and adaptive system based on the measurement of welding joints using laser scanning and the subsequent analysis of the obtained point cloud to adapt the welding trajectories.