Online monitoring of direct laser metal deposition process by means of infrared thermography

Abstract

Direct laser metal deposition (LMD–DED) is an additive manufacturing (AM) process that is used to build up and repair high-quality metal components. It works by overlapping layers of powder material and melting them with a laser. To get a stable process without defects and to reach, at the same time, high mechanical properties, a robust assessment and control of the process parameters, and above all of their combination, is required. The ideal goal is to assure the online control, to stop or correct the process in case of unexpected anomalies. In this work, a robust online monitoring of the laser metal deposition (LMD–DED) process based on the use of infrared thermography was developed and proposed. After choosing the suitable process parameters, a customized design of experiments (DOE) was set, and the statistical analysis of different thermal features was carried out to develop the most robust models that correlate them with the input process parameters (laser power, scanning speed, and powder flow rate). The proposed procedure was based on the extraction of different thermal features from suited regions of interest (ROI), performing statistical analyses by means of analysis of variance (ANOVA) and building regression models to correlate the process parameters with the thermal behavior. The obtained results demonstrated the possibility to control the process by means of the chosen thermal features, independent of the position of the ROI. Moreover, the possibility to use the models to detect typical AM defects, and anomalies, online directly during the process, has been proved and verified by destructive macrographs carried out on the manufactured coupons.