Proceedings Article | 12 June 2023
KEYWORDS: Materials properties, Feature extraction, Printing, Metals, Diffractive optical elements, Statistical analysis, Lasers, Infrared sensors, Process control
Laser Metal Deposition (LMD – DED) is an Additive Manufacturing (AM) process that allows the production, and the repairing of 3-D printing metallic parts. This kind of process is complex because it involves a high number of parameters and variables, some of which are difficult to control. The choice of these process parameters influences the quality of the final component, in terms of its mechanical properties. Furthermore, the production of components free of defects and, therefore, reliable is still a challenge and for these reasons, the online monitoring of this kind of process is becoming essential. In this regard, contactless sensors such as infrared cameras, pyrometers, bolometers, and optical cameras with sensors like CMOS, CCD, or photodiode, are usually used. This work focuses on the online monitoring of the Laser Metal Deposition (LMD – DED) process during the production of different coupons in Nickel-based alloy Inconel 718, using thermal data deriving from the analysis of the signal acquired by IR Focal Plane Array sensors. An experimental plan based on a customized Design of Experiments (DOE), in which the main controlled process parameters were the laser scanning speed, the powder flow rate and the laser power, together with some useful their combinations, was carried out. The experimental setup consisted of two microbolometer thermal sensors, one integral with the scanning laser head and the other one laterally and fixed respect to the deposition platform was adopted to monitor the process during the manufacturing of all coupons. By means of ANOVA and regression models, a correlation between process parameters and extracted thermal features was provided. At the end of the process, some hardness tests and macrographs on specific coupons were also performed to evaluate the mechanical properties of the material in correspondence with different combinations of the process parameters. A statistical approach was also employed to describe the results to directly correlate the process parameters and the final mechanical properties with the extracted thermal features.
