Abstract
In-process monitoring and control are essential for quality assurance and consistency of laser-based directed energy deposition (DED-LB) processes. Detection of irregularities during deposition in terms of defects or flaws is based on in -situ monitoring of output process parameters such as temperature, melt-pool geometry, or deposition height. The real-time feedback of these output parameters allows the development of control strategies for real-time adjustment of input process parameters, such as laser power or scanning speed, to correct detected deviations from the desired output process parameters. Therefore, criteria such as, sensitivity, stability, correlation, trends, and interactions of the input-output process parameters have a direct impact on controller design, establishing, for example, control limits or tolerance ranges of the output parameters. This paper focuses on the study of the characteristics of output process parameters to input process parameters. This research involves analyzing and comparing the deposition of single tracks under various input process parameters, including laser power, and scanning speed. Melt-pool geometry and temperature are estimated from a visual camera and a hyperspectral line camera, whereas the final deposition geometry is obtained from a laser triangulation scanner. The results show the linearity between input and output process parameters, the steadiness of the output process parameters, the relations between melt-pool and final deposition, and offer insights to design effective in-process control systems.
Original language | English |
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Article number | 042047 |
Number of pages | 11 |
Journal | Journal of Laser Applications |
Volume | 36 |
Issue number | 4 |
DOIs | |
Publication status | Published - 15 Oct 2024 |
Bibliographical note
Jorge Sanchez-Medina started pursuing a Ph.D. in 2019 at the Acoustic and Vibrations Research Group of the Vrije Universiteit Brussel, Belgium. He received his M.Sc. degree in Telecommunications Engineering in 2011 from Universidad de Las Palmas de Gran Canaria, Spain, after doing an Erasmus programme at the Katholieke Universiteit Leuven, Belgium, where he did his thesis in advanced signal processing techniques for the real-time data compression of biomedical sensors. From 2011 to 2019 he worked as engineer in different fields and European countries, where he spent most of his time in the automotive industry in Germany.Keywords
- Additive Manufacturing
- sensing
- control systems
- temperature estimation
- Image Processing and Computer Vision
- DED
- Control Strategies