A study on spectral characterization and quality detection of direct metal deposition process based on spectral diagnosis
- 21 Downloads
In the process of laser additive manufacturing, the transmission efficiency of laser energy and the forming quality are influenced by the plasma which plays a fundamental role in coupling the incident radiation to the material. The aim of this work is to present an effective spectral diagnosis method for quality research in laser additive manufacturing. A spectrum acquisition system for direct metal deposition (DMD) was established by using fiber optic spectrometer to collect the radiation during the forming process under different process parameters. The relationships between laser powers, powder feeding rate, traverse speed, and the radiation intensity of the plasma were found. Meanwhile, special wavelengths were chosen to establish the time-domain diagram (the relationship between the intensity and time) corresponding to the process, and some forming defects caused by the changes of processing parameters were correlated with the spectral information. What is more, to diagnose the defects automatically, statistical process control (SPC) method was used to analyze the correlations between intensity fluctuation and the forming defects. The findings of the paper will be helpful to understand the formative mechanism and influencing factors of laser-induced plasma during laser additive manufacturing and lay the foundations for automatic quality control of laser additive manufacturing process.
KeywordsLaser additive manufacturing Laser induced plasma Spectroscopic diagnosis SPC control
Unable to display preview. Download preview PDF.
This research was supported by the Natural Science Foundation of Shandong Province (No. ZR2017MEE042).
- 2.Dutta B, Singh V, Natu H, Choi J, Mazumder J (2009) Direct metal deposition. Adv Mater Process 167(3):29–31Google Scholar
- 6.Pekkarinen J, Salminen A, Kujanpää V, Ilonen J, Lensu L, Kälviäinen H (2013) Laser cladding using scanning optics-effect of the powder feeding angle and gas flow on process stability. Opt Laser Technol 30:590–599Google Scholar
- 8.Song L, Mazumder J (2012) Identification of phase transformation using optical emission spectroscopy for direct metal deposition process. Proc SPIE 8239:11Google Scholar
- 11.Lee SH (2013) Spectroscopic studies and mathematical modeling of laser material interaction for development of intelligent quality monitoring system. Dissertation, University of MichiganGoogle Scholar
- 14.Morgan SA, Fox M, McLean M, Hand DP (1997) Real-time process control in CO2 laser welding and direct casting: focus and temperature. Laser Mater Process Conf 11:290–299Google Scholar
- 15.Smurov I, Ignatiev M (1996) Real time pyrometry in laser surface treatment. In: Mazumder J (ed) Laser processing: surface treatment and film deposition. NATO ASI Series (Series E: Applied Sciences). Springer, Dordrecht, pp 1955–1961Google Scholar
- 16.Griffith ML, Hofmeister WH, Knorovsky GA, Maccallum DO, Schlienger EM, Smugeresky JE (2002) Direct laser additive fabrication system with image feedback control. USGoogle Scholar
- 19.Ralchenko Y, Kramida AE, Reader J, Team NA (2011) NIST atomic spectra database (version 4.1.0). https://physics.nist.gov/asd. Accessed May 2011
- 21.Meggers WF, Corliss CH, Scribner BF (1975) Tables of spectral-line intensities. National Bureau of Standards Monograph, WashingtonGoogle Scholar
- 22.Griem HR (1964) Plasma spectroscopy. McGraw-Hill, New YorkGoogle Scholar
- 23.Lajunen LHJ, Peramaki P (2004) Spectrochemical analysis by atomic absorption and emission. Royal Society of Chemistry, CambridgeGoogle Scholar
- 24.Oakland JS (2007) Statistical process control. Butterworth-Heinemann Ltd, OxfordGoogle Scholar