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Abstract. Although it is experiencing a wide diffusion, there are still several limits to the use of additive manufacturing (AM) for the fabrication of metal components. This includes low productivity, poor dimensional accuracy and uncertainty about the mechanical properties of the final parts. The main cause of these undesirable effects lies in the intrinsic complexity of the metal AM processes, such as Laser Metal Deposition (LMD). Accurate monitoring of the process and optimization of the process parameters are therefore of fundamental importance to ensure the overall quality of the product. Nowadays, several optical methods are under development for the monitoring of geometric characteristics and their correlation with specific process parameters, such as the standoff distance. This paper presents a comparative study between two optical in-process monitoring methods performed on AISI 316L multilayer samples produced by the LMD process. The first is a laser line section method based on a laser diode mounted on the deposition head, while the second method uses a high-resolution CMOS camera placed on the horizontal plane with a front view of the sample. In both cases, ad-hoc image processing algorithms were used to process the data, reconstruct the morphology of the component, and extract geometrical information. Results were then validated using an offline scanning system and micrographic analyses. Both proposed systems allowed the monitoring of the deposition quality using appropriate Key Performance Indicators (KPIs). The study showed a good capability of the prototype systems to detect deposition defects due to undesired variations of the process conditions and to monitor the standoff distance.

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