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Composition monitoring using plasma diagnostics during direct metal deposition (DMD) process
Optics and Laser Technology 106 (2018) 40–46
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Composition monitoring using plasma diagnostics during direct metal deposition (DMD) process Joonghan Shin a,⇑, J. Mazumder b a b
Department of Mechanical and Automotive Engineering, Kongju National University, 1223-24 Cheonandaero, Seobuk-gu, Cheonan 31080, Republic of Korea Center for Lasers and Plasmas for Advanced Manufacturing, University of Michigan, Ann Arbor, MI 48109-2125, USA
a r t i c l e
i n f o
Article history: Received 3 November 2017 Received in revised form 10 January 2018 Accepted 28 March 2018
Keywords: Plasma Laser Direct metal deposition (DMD) Optical emission spectroscopy (OES) Composition Line intensity ratio
a b s t r a c t The monitoring and controlling of the composition during laser additive manufacturing processes have attracted considerable attention since uniform composition is essential to maintain superior material properties of the fabricated part. In this study, the composition monitoring using plasma diagnostics is successfully carried out during direct metal deposition (DMD) process. Optical emission spectroscopy (OES) is employed to observe the Ni-base superalloy plasma generated during the DMD process. Composition prediction by line intensity ratios and plasma temperature is compared, and their monitoring performance is discussed. Ni-I/Cr-I line ratios almost linearly increase with increasing Ni composition. However, the plasma temperature decreases with the Ni composition. It is also observed that bright and high temperature plasma is produced at relatively high Cr concentration (i.e., low Ni concentration) because of the low boiling point and preferential oxidation of the Cr. The regression line of the line ratio data shows the better prediction of the Ni composition than that of the plasma temperature data. It is suggested that using the plasma temperature as a monitoring tool may not be suitable due to the non-linear characteristics and low sensitivity shown in the plasma temperature data. The regression line of the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio gives the most accurate prediction compared with the regression lines for other combinations of Ni-I and Cr-I lines. The predicted Ni composition error by the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio ranges from 0.02% to 4.5% (average 1.6%), which shows that using the line ratio for monitoring of the composition is quite reasonable. The method to predict Ni composition is also validated through the DMD experiment using as-received Inconel 718 powder with a certified Ni concentration of 50.9% (in atomic percentage). Average prediction for the Ni composition is 51.8% (error 1.6%) when the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio is used. Ó 2018 Elsevier Ltd. All rights reserved.
1. Introduction Direct metal deposition (DMD) is one of the laser additive manufacturing technologies that attract a great attention from many industries. It is essentially similar with laser cladding technology in that powdered metals are dropped on the substrate, and they are melted and deposited on it by a laser beam under an inert atmosphere. However, the DMD could fabricate near-net shape components by integrating the laser cladding technology with computer aided design (CAD) data, sensors and feedback control systems [1–10]. The potential of the DMD process in manufacturing industry is growing more and more. The direct fabrication of molds and dies and the repair of these parts as well as coatings
⇑ Corresponding author. E-mail address: [email protected] (J. Shin). https://doi.org/10.1016/j.optlastec.2018.03.020 0030-3992/Ó 2018 Elsevier Ltd. All rights reserved.
of metallic parts for improvement of surface properties are mostly well known application [11–13]. Various applications for surgical instrument, aerospace and military industry have been also explored [14]. As described above, the DMD technology is a very attractive manufacturing process which is applicable to from surface coatings to complex three dimensional metallic parts in a one-step process. However, like other laser aided manufacturing processes, intrinsic instabilities due to complex laser-matter interaction always exist in the DMD process too. Theses instabilities can come from various sources such as non-uniform powder feed rate, laser power or laser-plasma interaction. The interaction between a shielding gas and melt pool also could be a source of the instability. The instabilities can affect composition and microstructure of the deposits, which in turn can change material properties of the deposits. Uniform elemental composition is important to maintain superior
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material properties in the deposited part. Therefore, the monitoring and controlling of the composition in deposits during the DMD process are highly required. The plasma produced during laser-material interaction is the part that must be studied in all laser assisted manufacturing processes because a portion of laser beam energy is absorbed by plasmas, which can affect processes. In the DMD process, a certain portion of powders is bound to evaporate when the temperature of the melt pool exceeds a boiling temperature of the material, and this causes material loss of the melt pool during the deposition. The plasma formed from these evaporated materials including atoms, ions and electrons. They are closely related with the elemental composition of the melt pool. Therefore, the compositional information of the deposits could be estimated through the observation of the plasma. Many studies associated with plasma diagnostics in laser material processing have been reported. Most of them are for laser ablation [15–21], welding [22–25] and drilling [26,27] that require high power density of the laser beam (>106 W/cm2) for either removing or joining the material. Kumar [15] reported the effect of background gas on plasma during the laser ablation of the copper using optical emission spectroscopy (OES). According to results of the study, the intensity of emission lines increased in presence of a background gas (argon and neon gas) since the plasma was confined to a small region by collision between the background gas and plasma. Sibillano [22] studied the plasma diagnostics of the laser welding process. In this study, a spectrometer only collected emission lights from the top of the keyhole. Plasma temperature during the welding process decreased with laser power and penetration depth since deeper penetration by higher laser power shifted the hottest core of the plasma to the lower position in the keyhole. The plasma diagnostics using OES was also reported for laser drilling [27]. Temporal histories of the plasma parameters including emission line intensity, electron temperature, and number density were examined in relation to drilling depths. It was found that they had an inverse proportional relationship with the drilling depth because of the reduction of material removal and the downward movement of plasma core. The plasma study for the laser additive manufacturing processes such as DMD or laser cladding process is very limited because of the difficulty in observation of the weak plasma generated by a relatively low power density beam (103–105 W/cm2). Tewari [28] observed the plasma produced during laser cladding using OES method to correlate spectral data with elemental compositions in clads. Emission line intensities and their ratios for Nb and Hf atoms and Al ions were used to estimate a relative composition of the species in plasma. The quantitative correlations between line intensity ratios (Nb-I/Al-II and Nb-I/Hf-I) and the Nb concentration in clads were also obtained for different laser powers. It was shown that Nb-I/Al-II and Nb-I/Hf-I ratios linearly increase with increase in the concentration of Nb in the clad. Song et al. studied for the prediction of the real-time Cr composition during the DMD of the pure Cr and H13 tool steel material using OES [29]. In this study, alloyed H13 tool steel powders and high purity Cr powders are mechanically premixed to make different Cr composition in clads. Spectroscopic data including emission line intensity ratios (Cr-I/Fe-I), plasma temperature and electron number density were obtained for the DMD experiments using the powders with various Cr compositions, and they were correlated each other. According to results, the predicted Cr concentration using a line intensity ratio calibration curve was more accurate than that from both plasma temperature and electron number density calibration curve. The smallest error in the Cr concentrations predicted by the line intensity ratio calibration curve was 0.96% (in average). An accurate and robust method to improve the composition prediction performance of the DMD process was proposed
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[30]. In this study, Ti-Al binary metal powders were deposited onto Ti substrates by a fiber laser and the spectral signal of plasma plume during the process was collected by OES. In order to predict the Al concentration in deposits, a mathematical algorithm called support vector regression (SVR) method using spectroscopic parameters as inputs was adopted. The results from the study showed that more accurate prediction for the Al concentration was obtained when both line intensity ratio and line intensity were used as inputs than only line intensity ratio was considered. The SVR method proposed in this study also proved that accurate and universal operating parameter independent prediction was possible for varying operating condition during the process. As described above, plasmas produced during laser material processing have been widely studied for various materials and processes. However, only a few studies have been reported for the plasma diagnostics of the laser additive process so far. In addition, no research has reported the observation of the Ni-base superalloy plasma during the DMD process. In this study, the spectroscopic data of the Ni-base superalloy plasma generated during the DMD process is analyzed in relation to the Ni composition in deposits for the first time. Composition prediction by line intensity ratios and plasma temperature is compared, and their monitoring performance is discussed. There is a well-known composition analysis technique called laser induced breakdown spectroscopy (LIBS) [31,32] which is also based on plasma diagnostics. This technique is able to give a fast and convenient method of composition analysis. However, the application of the LIBS is only confined to the surface analysis of materials. The method proposed in this study can provide not only surface composition but also internal composition of materials through the real-time monitoring of the plasma during the process. It is also expected that the plasma diagnostics from this study could be possibly used in the field of plasma-based deposition [33,34] and etching [35] processes for monitoring and controlling of the important physical and chemical properties.
2. Experimental details A 6 kW CO2 laser (TRUMP Inc.) with a focused beam diameter of 0.5 mm is used as a heat source to deposit material. A laser beam is focused via a copper turning mirror and gold coated focusing mirror. The laser is incorporated into an Allen-Bradley 3-axis CNC machine for precise control of the relative position between the laser beam and substrate. For DMD experiments, powders with five different Ni compositions are made by mechanical mixing of a gasatomized Ni-base superalloy (Inconel 718) powder (125/+45 mesh size) and high purity Cr powder (200 mesh size, 99%). After the DMD experiments, the final Ni compositions of the powders are confirmed through an energy dispersive spectrometer (EDS)
Fig. 1. Ni composition in the DMD layers deposited with five different powders (composition is measured with EDS).
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scan of the deposits. The Ni composition measured by the EDS is in the range of 23.2–50 atomic percentage (at.%). Fig. 1 shows Ni composition data measured with the EDS. The elemental composition of Inconel 718 power used for the DMD powder preparation is shown in Table 1. In this study, Inconel 718 plate (52 mm 52 mm 7 mm) is used as the substrate for deposition of powders. Ar and He are used as a shielding and powder carrier gas, respectively. A shielding gas jet is introduced co-axially to the laser beam through a conical nozzle with the orifice of 5 mm diameter. Powders are fed from the hopper located above laser head. Powder feed rate is controlled by the speed of the motor to rotate the rod plugging up the bottom part of the hopper. Powders are delivered onto the substrate through the 4 small metallic pipes connecting the hopper and laser nozzle. The powders eventually dropped from the nozzle are melted and deposited on the substrate by the laser beam. In this study, the single layer of 2.5 cm length is deposited on the substrate by varying the composition of powder. Table 2 shows the process condition adopted in the DMD experiment. The emission spectra of the plasma created during the DMD process are taken using a high resolution USB fiber optic spectrometer (Ocean optics, HR 2000+) fitted with a 1200 groove/mm grating and an entrance slit of 10 lm width. The spectrometer uses a linear silicon charged coupled device (CCD) array (Sony ILX 511) with 2048 pixels (pixel size: 14 lm 200 lm) to detect spectra. The spectrometer is incorporated into the PC with a spectrometer
Table 1 Element composition of Inconel 718 powder. Element
Ni
Cr
Fe
Nb + Ta
Mo
Ti
Al
At.%
50.9
16
16.3
11.1
4.7
0.8
0.2
operating software for data acquisition. Light is imaged onto the spectrometer entrance slit through an optical fiber (50 lm diameter) connected to a silica collimating lens. The collimating lens is parallel to the substrate, and it is positioned 1 mm above the substrate and 22 cm away from the center of the laser nozzle. The direction of the plasma observation is normal to the moving direction of the substrate. In this study, spectra are recorded over a wavelength range of 270–470 nm. During the DMD process, emission spectra are consecutively recorded with a 20 ms integration time until the process is completed. Fig. 2 shows the schematic diagram of the DMD and OES experimental setup. 3. Results and discussion 3.1. Emission spectra of Ni-base superalloy plasma Fig. 3 shows the typical emission spectrum of the laser-induced plasma obtained in DMD experiments. In order to determine spectroscopic data such as line intensity ratio and plasma temperature, atomic spectral lines for two main elements of the powder, Ni and Cr, are carefully selected from the emission spectra. The atomic spectral lines are identified by atomic line data base of the National Institute of Standards and Technology (NIST) [36]. Two Ni-I lines (351.5 and 352.45 nm) and Cr-I lines (396.36 and 399.11 nm) are chosen to determine the line intensity ratio (Ni-I/Cr-I). Extra Cr-I lines (363.98–399.11 nm) are used to calculate the plasma temperature. These lines are relatively strong and do not overlap with other lines. They also have high transition probabilities, allowing easy detection of the lines. Table 3 shows the spectral data of the lines selected. 3.2. Line intensity and intensity ratio The intensity of the emission line Imn (m is the upper level and n is the lower level for the given transition of an electron, respectively) observed from plasma plume can be expressed by
Table 2 DMD process condition. Laser power (W)
Laser scanning speed (cm/min)
Powder feed rate (g/min)
Shielding gas pressure (kPa)
800
30.5
6
207
Fig. 2. Schematic diagram of the experimental set-up for plasma diagnostics during the DMD process.
Fig. 3. Emission spectrum of the plasma created during the DMD process (a) 343– 356.5 nm and (b) 360–400 nm region.
J. Shin, J. Mazumder / Optics and Laser Technology 106 (2018) 40–46 Table 3 Spectral data for Ni-I and Cr-I lines selected. Wavelength (nm)
Upper energy level, Em (eV)
gm (degeneracy)
A (107/s)
Ni-I, Ni-I, Cr-I, Cr-I, Cr-I, Cr-I, Cr-I, Cr-I,
3.635 3.542 5.949 4.159 5.671 5.667 5.655 5.649
7 5 11 5 15 13 9 7
4.20 10.0 18.0 0.39 13.0 12.0 10.5 10.7
351.50 352.45 363.98 388.52 396.36 396.97 398.39 399.11
Imn ¼ Nm Amn htmn
ð1Þ
where Nm is the population of the upper state, Amn is the transition probability, h is the Planck’s constant, and tmn is the frequency for the spectral line, respectively. According to the relation above, the line intensity measured from emission spectra is proportional to the population of the species associated with a given transition in plasma plume. The plasma plume generated from the DMD process using relatively low beam power density generally contains a high concentration of neutral atoms rather than ions and electrons because of low plasma temperature ranging from 3500 K to 5000 K [29]. Therefore, spectral lines observed in the DMD plasma are manly from neutral atoms, and the intensity of spectral lines is related to the concentration of atoms evaporated from the melt pool. Instead of using the integrated area of the emission line [29], in this study, the new definition for line intensity is adopted to minimize the effect of the continuum background emissions on the calculation of the line ratio. The line intensity used to determine the quantitative ratio is described in Fig. 4. The value of the intensity is obtained by subtracting the continuum intensity from the peak value of the spectral line. The average of the intensities obtained at two ends of the spectral line is considered as the continuum intensity associated with the peak as shown in the figure. Fig. 5 shows Ni-I/Cr-I line intensity ratio as a function of the Ni composition in atomic percentage. The line ratios are determined from the emission spectra obtained during the deposition of powders with five different Ni compositions. As seen in the figure, the Ni-I/Cr-I line intensity ratios increase with the Ni atomic percentage in the powders. In particular, the Ni-I/Cr-I line intensity ratios have a nearly proportional relationship with the Ni composition of the powder. According to the curve fit results of experimental data, it is clearly seen that the slope of the regression line becomes large when the Cr-I line of 399.11 nm is used to calculate the line ratio. This means that the Ni-I/Cr-I line ratio calculated by Cr-I (399.11 nm) can provide a high sensitivity in monitoring of the composition.
Fig. 4. Line intensity used to determine a quantitative ratio.
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The standard deviation error bar of the line ratio calculated also tends to increase with increasing Ni composition (i.e., with decreasing Cr composition). This is attributable to a weak intensity of the plasma plume at low Cr composition. It is observed that the intensity of the plasma light becomes small as the composition of the Cr decreases. Weak and dark plasma produces emission spectra with relatively small intensity, which generally causes a low signal-to-noise ratio of the experiment. Because of this, low intensity spectral line would result in the relatively large variation of the line ratio at small Cr composition. Since a boiling temperature of the Cr (2944 K) is lower than that of the Ni (3186 K), an amount of evaporated material from the melt pool will be much larger at large Cr composition if other process conditions such as laser power and powder feed rate are same. This can explain the reason for generation of the bright plasma when the powder with the large Cr composition is deposited. 3.3. Plasma temperature In this study, the temperature of the plasma is determined by the Boltzmann plot method. It is well known that laser-induced plasmas generally satisfy local thermodynamic equilibrium (LTE) state [17,26,27]. In the LTE condition, collision process dominates the excitation and de-excitation of the species in plasma compared with radiative process, and the populations of the excited states follow a Boltzmann distribution [37].
Nm g ¼ m expðEm =kTÞ N ZðTÞ
ð2Þ
In this equation, Nm, N, gm, Z, Em, k, and T represent the population of the upper state m (cm3), the total number density of the species (cm3), the degeneracy of the upper state m, the partition function, the energy of the upper state (eV), the Boltzmann constant (eV K1), and the electron temperature of the plasma (K), respectively. By using Eq. (1) and simple mathematical treatments, the Eq. (2) can be written as
ln
Imn kmn g m Amn
¼ ln
Nhc 1 Em ZðTÞ kT
ð3Þ
where kmn is the wavelength of the spectral line (nm) and c is the speed of light (m/s). According to Eq. (3), the temperature of the plasma can be estimated from the slope of the linear relationship between the ln(Imnkmn/gmAmn) and Em. Five Cr-I lines in the range of 368.98–399.11 nm are adopted to estimate the plasma temperature from the Boltzmann plot. Fig. 6 shows the result of the Boltzmann plot obtained when the powder with 23.2% Ni composition is used in DMD experiment. The plasma temperature calculated for different Ni compositions is shown in Fig. 7. The temperature is negatively correlated with Ni composition as shown in the figure. It is seen that the linearity of the plasma temperature data is relatively worse than that of the line ratio data shown in Fig. 5. The sensitivity (the slope of the regression line) of the plasma temperature for the Ni composition is very small, 3.1 K/at.%, compared to the plasma temperature (4215–4305 K) determined in this study. Therefore, using the plasma temperature as a tool for composition monitoring may not be appropriate. The increase of the plasma temperature with increasing Cr concentration (i.e., with decreasing Ni concentration) in powder could be ascribed to the effect of the Cr oxidation. It is known that the Cr is primarily oxidized among the elements constituting Ni-base alloys when solid-state Ni-base alloys are exposed to a hot oxidation environment [38]. In fact, Cr has a lower ionization potential compared to Ni, therefore, it can be more easily ionized in plasma plume and interact with oxygen to form oxides. Table 4 shows the ionization potential for Ni and Cr. The
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Fig. 5. Ni-I/Cr-I line intensity ratio as a function of the Ni atomic percentage (a) Ni-I (351.5 nm)/Cr-I (396.39 nm) line ratio, (b) Ni-I (351.5 nm)/Cr-I (399.11 nm) line ratio, (c) Ni-I (352.45 nm)/Cr-I (396.39 nm) line ratio, and (d) Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio.
oxygen residing near laser-material interaction region could promote the oxidation of the Cr in plasma plume. This oxidation process adds extra heat to plasma plume by exothermic reaction. As a result, bright and high temperature plasma is produced when the powder with high Cr composition is used. 3.4. Ni composition prediction by regression lines
Fig. 6. Boltzmann plot using Cr-I lines.
Ni composition is predicted using the regression lines obtained for line intensity ratio and plasma temperature. Fig. 8 shows the predicted Ni composition from the regression lines. The regression lines for the line ratio generally show the better prediction of the Ni composition than the regression line for the plasma temperature. The regression line of the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio gives the most accurate prediction among regressions lines obtained in this study. The Ni composition prediction error from the regression line of the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio varies from 0.02% to 4.5% for the given range of the Ni composition. The average error is only 1.6%, which shows a reasonably good accuracy in the prediction of the composition. Relatively large prediction error from the regression lines for the plasma temperature is mostly due to inaccurate curve fitting of the regression line at the lowest Ni composition. Prediction errors for all regression lines are summarized in Table 5. In order to evaluate the validation of the method to predict elemental composition, as-received Inconel 718 powder with a certi-
Table 4 Ionization potential for Ni and Cr.
Fig. 7. Plasma temperature as a function of the Ni atomic percentage.
Element
1st ionization potential
2nd ionization potential
Ni Cr
737.1 kJ/mole 652.9 kJ/mole
1753.0 kJ/mole 1590.6 kJ/mole
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are used to determine plasma parameters such as a line intensity ratio and plasma temperature. Using them, the correlation between the plasma parameters and Ni composition is successfully developed and validated. It is shown that the line ratio generally gives the better prediction of the Ni composition than that of the plasma temperature. The smallest prediction error obtained is only 1.6%, which proves the feasibility of the composition monitoring method developed in this study. The results from this study may suggest that the plasma diagnostics reported in this study could be used in various plasma-based deposition and etching processes for monitoring of the important material properties. Acknowledgements Fig. 8. Ni composition (at.%) predicted by different regression lines. Straight line shows the target composition of the DMD layer: square, using Ni-I (351.5 nm)/Cr-I (396.36 nm) line ratio regression line; circle, using Ni-I (351.5 nm)/Cr-I (399.11 nm) line ratio regression line; triangle, using Ni-I (352.45 nm)/Cr-I (396.36 nm) line ratio regression line; diamond, using Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio regression line; star, using plasma temperature regression line.
This work was supported by the National Science Foundation (NSF) Industry-University Co-operative Research Center and GE Aviation under the NSF sub-award No. 0438917.
Appendix A. Supplementary material Table 5 Ni composition prediction error by regression lines. Regression line for
Line ratio, Ni-I (351.5 nm)/Cr-I (396.36 nm) Line ratio, Ni-I (351.5 nm)/Cr-I (399.11 nm) Line ratio, Ni-I (352.45 nm)/Cr-I (396.36 nm) Line ratio, Ni-I (352.45 nm)/Cr-I (399.11 nm) Plasma temperature
Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.optlastec.2018.03. 020.
Error (%) Range
Average
2.5–8.3 6.1–18 2.6–10.4 0.02–4.5 6.7–32
4.6 12.2 5.2 1.6 12.6
Fig. 9. Ni composition measured during the DMD of alloyed Inconel 718 powder with a certified Ni composition of 50.9 atomic percentage.
fied Ni concentration of 50.9% (in at.%) is only used for DMD experiment. Fig. 9 shows the Ni concentration predicted during the DMD process. The regress lines for Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio and plasma temperature are used to predict the Ni composition. The case using the line ratio gives the better accuracy in prediction again than that using the plasma temperature. Average prediction for the Ni composition is 51.8% (error 1.6%) when the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio is used for prediction. The method using the plasma temperature shows average prediction of 49.7% (error 2.5%). 4. Conclusions Elemental composition monitoring during the DMD process is carried out by plasma diagnostics using the OES. Atomic spectral lines of two main elements, Ni and Cr, in Ni-base alloy powders
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Full length article
Composition monitoring using plasma diagnostics during direct metal deposition (DMD) process Joonghan Shin a,⇑, J. Mazumder b a b
Department of Mechanical and Automotive Engineering, Kongju National University, 1223-24 Cheonandaero, Seobuk-gu, Cheonan 31080, Republic of Korea Center for Lasers and Plasmas for Advanced Manufacturing, University of Michigan, Ann Arbor, MI 48109-2125, USA
a r t i c l e
i n f o
Article history: Received 3 November 2017 Received in revised form 10 January 2018 Accepted 28 March 2018
Keywords: Plasma Laser Direct metal deposition (DMD) Optical emission spectroscopy (OES) Composition Line intensity ratio
a b s t r a c t The monitoring and controlling of the composition during laser additive manufacturing processes have attracted considerable attention since uniform composition is essential to maintain superior material properties of the fabricated part. In this study, the composition monitoring using plasma diagnostics is successfully carried out during direct metal deposition (DMD) process. Optical emission spectroscopy (OES) is employed to observe the Ni-base superalloy plasma generated during the DMD process. Composition prediction by line intensity ratios and plasma temperature is compared, and their monitoring performance is discussed. Ni-I/Cr-I line ratios almost linearly increase with increasing Ni composition. However, the plasma temperature decreases with the Ni composition. It is also observed that bright and high temperature plasma is produced at relatively high Cr concentration (i.e., low Ni concentration) because of the low boiling point and preferential oxidation of the Cr. The regression line of the line ratio data shows the better prediction of the Ni composition than that of the plasma temperature data. It is suggested that using the plasma temperature as a monitoring tool may not be suitable due to the non-linear characteristics and low sensitivity shown in the plasma temperature data. The regression line of the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio gives the most accurate prediction compared with the regression lines for other combinations of Ni-I and Cr-I lines. The predicted Ni composition error by the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio ranges from 0.02% to 4.5% (average 1.6%), which shows that using the line ratio for monitoring of the composition is quite reasonable. The method to predict Ni composition is also validated through the DMD experiment using as-received Inconel 718 powder with a certified Ni concentration of 50.9% (in atomic percentage). Average prediction for the Ni composition is 51.8% (error 1.6%) when the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio is used. Ó 2018 Elsevier Ltd. All rights reserved.
1. Introduction Direct metal deposition (DMD) is one of the laser additive manufacturing technologies that attract a great attention from many industries. It is essentially similar with laser cladding technology in that powdered metals are dropped on the substrate, and they are melted and deposited on it by a laser beam under an inert atmosphere. However, the DMD could fabricate near-net shape components by integrating the laser cladding technology with computer aided design (CAD) data, sensors and feedback control systems [1–10]. The potential of the DMD process in manufacturing industry is growing more and more. The direct fabrication of molds and dies and the repair of these parts as well as coatings
⇑ Corresponding author. E-mail address: [email protected] (J. Shin). https://doi.org/10.1016/j.optlastec.2018.03.020 0030-3992/Ó 2018 Elsevier Ltd. All rights reserved.
of metallic parts for improvement of surface properties are mostly well known application [11–13]. Various applications for surgical instrument, aerospace and military industry have been also explored [14]. As described above, the DMD technology is a very attractive manufacturing process which is applicable to from surface coatings to complex three dimensional metallic parts in a one-step process. However, like other laser aided manufacturing processes, intrinsic instabilities due to complex laser-matter interaction always exist in the DMD process too. Theses instabilities can come from various sources such as non-uniform powder feed rate, laser power or laser-plasma interaction. The interaction between a shielding gas and melt pool also could be a source of the instability. The instabilities can affect composition and microstructure of the deposits, which in turn can change material properties of the deposits. Uniform elemental composition is important to maintain superior
J. Shin, J. Mazumder / Optics and Laser Technology 106 (2018) 40–46
material properties in the deposited part. Therefore, the monitoring and controlling of the composition in deposits during the DMD process are highly required. The plasma produced during laser-material interaction is the part that must be studied in all laser assisted manufacturing processes because a portion of laser beam energy is absorbed by plasmas, which can affect processes. In the DMD process, a certain portion of powders is bound to evaporate when the temperature of the melt pool exceeds a boiling temperature of the material, and this causes material loss of the melt pool during the deposition. The plasma formed from these evaporated materials including atoms, ions and electrons. They are closely related with the elemental composition of the melt pool. Therefore, the compositional information of the deposits could be estimated through the observation of the plasma. Many studies associated with plasma diagnostics in laser material processing have been reported. Most of them are for laser ablation [15–21], welding [22–25] and drilling [26,27] that require high power density of the laser beam (>106 W/cm2) for either removing or joining the material. Kumar [15] reported the effect of background gas on plasma during the laser ablation of the copper using optical emission spectroscopy (OES). According to results of the study, the intensity of emission lines increased in presence of a background gas (argon and neon gas) since the plasma was confined to a small region by collision between the background gas and plasma. Sibillano [22] studied the plasma diagnostics of the laser welding process. In this study, a spectrometer only collected emission lights from the top of the keyhole. Plasma temperature during the welding process decreased with laser power and penetration depth since deeper penetration by higher laser power shifted the hottest core of the plasma to the lower position in the keyhole. The plasma diagnostics using OES was also reported for laser drilling [27]. Temporal histories of the plasma parameters including emission line intensity, electron temperature, and number density were examined in relation to drilling depths. It was found that they had an inverse proportional relationship with the drilling depth because of the reduction of material removal and the downward movement of plasma core. The plasma study for the laser additive manufacturing processes such as DMD or laser cladding process is very limited because of the difficulty in observation of the weak plasma generated by a relatively low power density beam (103–105 W/cm2). Tewari [28] observed the plasma produced during laser cladding using OES method to correlate spectral data with elemental compositions in clads. Emission line intensities and their ratios for Nb and Hf atoms and Al ions were used to estimate a relative composition of the species in plasma. The quantitative correlations between line intensity ratios (Nb-I/Al-II and Nb-I/Hf-I) and the Nb concentration in clads were also obtained for different laser powers. It was shown that Nb-I/Al-II and Nb-I/Hf-I ratios linearly increase with increase in the concentration of Nb in the clad. Song et al. studied for the prediction of the real-time Cr composition during the DMD of the pure Cr and H13 tool steel material using OES [29]. In this study, alloyed H13 tool steel powders and high purity Cr powders are mechanically premixed to make different Cr composition in clads. Spectroscopic data including emission line intensity ratios (Cr-I/Fe-I), plasma temperature and electron number density were obtained for the DMD experiments using the powders with various Cr compositions, and they were correlated each other. According to results, the predicted Cr concentration using a line intensity ratio calibration curve was more accurate than that from both plasma temperature and electron number density calibration curve. The smallest error in the Cr concentrations predicted by the line intensity ratio calibration curve was 0.96% (in average). An accurate and robust method to improve the composition prediction performance of the DMD process was proposed
41
[30]. In this study, Ti-Al binary metal powders were deposited onto Ti substrates by a fiber laser and the spectral signal of plasma plume during the process was collected by OES. In order to predict the Al concentration in deposits, a mathematical algorithm called support vector regression (SVR) method using spectroscopic parameters as inputs was adopted. The results from the study showed that more accurate prediction for the Al concentration was obtained when both line intensity ratio and line intensity were used as inputs than only line intensity ratio was considered. The SVR method proposed in this study also proved that accurate and universal operating parameter independent prediction was possible for varying operating condition during the process. As described above, plasmas produced during laser material processing have been widely studied for various materials and processes. However, only a few studies have been reported for the plasma diagnostics of the laser additive process so far. In addition, no research has reported the observation of the Ni-base superalloy plasma during the DMD process. In this study, the spectroscopic data of the Ni-base superalloy plasma generated during the DMD process is analyzed in relation to the Ni composition in deposits for the first time. Composition prediction by line intensity ratios and plasma temperature is compared, and their monitoring performance is discussed. There is a well-known composition analysis technique called laser induced breakdown spectroscopy (LIBS) [31,32] which is also based on plasma diagnostics. This technique is able to give a fast and convenient method of composition analysis. However, the application of the LIBS is only confined to the surface analysis of materials. The method proposed in this study can provide not only surface composition but also internal composition of materials through the real-time monitoring of the plasma during the process. It is also expected that the plasma diagnostics from this study could be possibly used in the field of plasma-based deposition [33,34] and etching [35] processes for monitoring and controlling of the important physical and chemical properties.
2. Experimental details A 6 kW CO2 laser (TRUMP Inc.) with a focused beam diameter of 0.5 mm is used as a heat source to deposit material. A laser beam is focused via a copper turning mirror and gold coated focusing mirror. The laser is incorporated into an Allen-Bradley 3-axis CNC machine for precise control of the relative position between the laser beam and substrate. For DMD experiments, powders with five different Ni compositions are made by mechanical mixing of a gasatomized Ni-base superalloy (Inconel 718) powder (125/+45 mesh size) and high purity Cr powder (200 mesh size, 99%). After the DMD experiments, the final Ni compositions of the powders are confirmed through an energy dispersive spectrometer (EDS)
Fig. 1. Ni composition in the DMD layers deposited with five different powders (composition is measured with EDS).
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scan of the deposits. The Ni composition measured by the EDS is in the range of 23.2–50 atomic percentage (at.%). Fig. 1 shows Ni composition data measured with the EDS. The elemental composition of Inconel 718 power used for the DMD powder preparation is shown in Table 1. In this study, Inconel 718 plate (52 mm 52 mm 7 mm) is used as the substrate for deposition of powders. Ar and He are used as a shielding and powder carrier gas, respectively. A shielding gas jet is introduced co-axially to the laser beam through a conical nozzle with the orifice of 5 mm diameter. Powders are fed from the hopper located above laser head. Powder feed rate is controlled by the speed of the motor to rotate the rod plugging up the bottom part of the hopper. Powders are delivered onto the substrate through the 4 small metallic pipes connecting the hopper and laser nozzle. The powders eventually dropped from the nozzle are melted and deposited on the substrate by the laser beam. In this study, the single layer of 2.5 cm length is deposited on the substrate by varying the composition of powder. Table 2 shows the process condition adopted in the DMD experiment. The emission spectra of the plasma created during the DMD process are taken using a high resolution USB fiber optic spectrometer (Ocean optics, HR 2000+) fitted with a 1200 groove/mm grating and an entrance slit of 10 lm width. The spectrometer uses a linear silicon charged coupled device (CCD) array (Sony ILX 511) with 2048 pixels (pixel size: 14 lm 200 lm) to detect spectra. The spectrometer is incorporated into the PC with a spectrometer
Table 1 Element composition of Inconel 718 powder. Element
Ni
Cr
Fe
Nb + Ta
Mo
Ti
Al
At.%
50.9
16
16.3
11.1
4.7
0.8
0.2
operating software for data acquisition. Light is imaged onto the spectrometer entrance slit through an optical fiber (50 lm diameter) connected to a silica collimating lens. The collimating lens is parallel to the substrate, and it is positioned 1 mm above the substrate and 22 cm away from the center of the laser nozzle. The direction of the plasma observation is normal to the moving direction of the substrate. In this study, spectra are recorded over a wavelength range of 270–470 nm. During the DMD process, emission spectra are consecutively recorded with a 20 ms integration time until the process is completed. Fig. 2 shows the schematic diagram of the DMD and OES experimental setup. 3. Results and discussion 3.1. Emission spectra of Ni-base superalloy plasma Fig. 3 shows the typical emission spectrum of the laser-induced plasma obtained in DMD experiments. In order to determine spectroscopic data such as line intensity ratio and plasma temperature, atomic spectral lines for two main elements of the powder, Ni and Cr, are carefully selected from the emission spectra. The atomic spectral lines are identified by atomic line data base of the National Institute of Standards and Technology (NIST) [36]. Two Ni-I lines (351.5 and 352.45 nm) and Cr-I lines (396.36 and 399.11 nm) are chosen to determine the line intensity ratio (Ni-I/Cr-I). Extra Cr-I lines (363.98–399.11 nm) are used to calculate the plasma temperature. These lines are relatively strong and do not overlap with other lines. They also have high transition probabilities, allowing easy detection of the lines. Table 3 shows the spectral data of the lines selected. 3.2. Line intensity and intensity ratio The intensity of the emission line Imn (m is the upper level and n is the lower level for the given transition of an electron, respectively) observed from plasma plume can be expressed by
Table 2 DMD process condition. Laser power (W)
Laser scanning speed (cm/min)
Powder feed rate (g/min)
Shielding gas pressure (kPa)
800
30.5
6
207
Fig. 2. Schematic diagram of the experimental set-up for plasma diagnostics during the DMD process.
Fig. 3. Emission spectrum of the plasma created during the DMD process (a) 343– 356.5 nm and (b) 360–400 nm region.
J. Shin, J. Mazumder / Optics and Laser Technology 106 (2018) 40–46 Table 3 Spectral data for Ni-I and Cr-I lines selected. Wavelength (nm)
Upper energy level, Em (eV)
gm (degeneracy)
A (107/s)
Ni-I, Ni-I, Cr-I, Cr-I, Cr-I, Cr-I, Cr-I, Cr-I,
3.635 3.542 5.949 4.159 5.671 5.667 5.655 5.649
7 5 11 5 15 13 9 7
4.20 10.0 18.0 0.39 13.0 12.0 10.5 10.7
351.50 352.45 363.98 388.52 396.36 396.97 398.39 399.11
Imn ¼ Nm Amn htmn
ð1Þ
where Nm is the population of the upper state, Amn is the transition probability, h is the Planck’s constant, and tmn is the frequency for the spectral line, respectively. According to the relation above, the line intensity measured from emission spectra is proportional to the population of the species associated with a given transition in plasma plume. The plasma plume generated from the DMD process using relatively low beam power density generally contains a high concentration of neutral atoms rather than ions and electrons because of low plasma temperature ranging from 3500 K to 5000 K [29]. Therefore, spectral lines observed in the DMD plasma are manly from neutral atoms, and the intensity of spectral lines is related to the concentration of atoms evaporated from the melt pool. Instead of using the integrated area of the emission line [29], in this study, the new definition for line intensity is adopted to minimize the effect of the continuum background emissions on the calculation of the line ratio. The line intensity used to determine the quantitative ratio is described in Fig. 4. The value of the intensity is obtained by subtracting the continuum intensity from the peak value of the spectral line. The average of the intensities obtained at two ends of the spectral line is considered as the continuum intensity associated with the peak as shown in the figure. Fig. 5 shows Ni-I/Cr-I line intensity ratio as a function of the Ni composition in atomic percentage. The line ratios are determined from the emission spectra obtained during the deposition of powders with five different Ni compositions. As seen in the figure, the Ni-I/Cr-I line intensity ratios increase with the Ni atomic percentage in the powders. In particular, the Ni-I/Cr-I line intensity ratios have a nearly proportional relationship with the Ni composition of the powder. According to the curve fit results of experimental data, it is clearly seen that the slope of the regression line becomes large when the Cr-I line of 399.11 nm is used to calculate the line ratio. This means that the Ni-I/Cr-I line ratio calculated by Cr-I (399.11 nm) can provide a high sensitivity in monitoring of the composition.
Fig. 4. Line intensity used to determine a quantitative ratio.
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The standard deviation error bar of the line ratio calculated also tends to increase with increasing Ni composition (i.e., with decreasing Cr composition). This is attributable to a weak intensity of the plasma plume at low Cr composition. It is observed that the intensity of the plasma light becomes small as the composition of the Cr decreases. Weak and dark plasma produces emission spectra with relatively small intensity, which generally causes a low signal-to-noise ratio of the experiment. Because of this, low intensity spectral line would result in the relatively large variation of the line ratio at small Cr composition. Since a boiling temperature of the Cr (2944 K) is lower than that of the Ni (3186 K), an amount of evaporated material from the melt pool will be much larger at large Cr composition if other process conditions such as laser power and powder feed rate are same. This can explain the reason for generation of the bright plasma when the powder with the large Cr composition is deposited. 3.3. Plasma temperature In this study, the temperature of the plasma is determined by the Boltzmann plot method. It is well known that laser-induced plasmas generally satisfy local thermodynamic equilibrium (LTE) state [17,26,27]. In the LTE condition, collision process dominates the excitation and de-excitation of the species in plasma compared with radiative process, and the populations of the excited states follow a Boltzmann distribution [37].
Nm g ¼ m expðEm =kTÞ N ZðTÞ
ð2Þ
In this equation, Nm, N, gm, Z, Em, k, and T represent the population of the upper state m (cm3), the total number density of the species (cm3), the degeneracy of the upper state m, the partition function, the energy of the upper state (eV), the Boltzmann constant (eV K1), and the electron temperature of the plasma (K), respectively. By using Eq. (1) and simple mathematical treatments, the Eq. (2) can be written as
ln
Imn kmn g m Amn
¼ ln
Nhc 1 Em ZðTÞ kT
ð3Þ
where kmn is the wavelength of the spectral line (nm) and c is the speed of light (m/s). According to Eq. (3), the temperature of the plasma can be estimated from the slope of the linear relationship between the ln(Imnkmn/gmAmn) and Em. Five Cr-I lines in the range of 368.98–399.11 nm are adopted to estimate the plasma temperature from the Boltzmann plot. Fig. 6 shows the result of the Boltzmann plot obtained when the powder with 23.2% Ni composition is used in DMD experiment. The plasma temperature calculated for different Ni compositions is shown in Fig. 7. The temperature is negatively correlated with Ni composition as shown in the figure. It is seen that the linearity of the plasma temperature data is relatively worse than that of the line ratio data shown in Fig. 5. The sensitivity (the slope of the regression line) of the plasma temperature for the Ni composition is very small, 3.1 K/at.%, compared to the plasma temperature (4215–4305 K) determined in this study. Therefore, using the plasma temperature as a tool for composition monitoring may not be appropriate. The increase of the plasma temperature with increasing Cr concentration (i.e., with decreasing Ni concentration) in powder could be ascribed to the effect of the Cr oxidation. It is known that the Cr is primarily oxidized among the elements constituting Ni-base alloys when solid-state Ni-base alloys are exposed to a hot oxidation environment [38]. In fact, Cr has a lower ionization potential compared to Ni, therefore, it can be more easily ionized in plasma plume and interact with oxygen to form oxides. Table 4 shows the ionization potential for Ni and Cr. The
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Fig. 5. Ni-I/Cr-I line intensity ratio as a function of the Ni atomic percentage (a) Ni-I (351.5 nm)/Cr-I (396.39 nm) line ratio, (b) Ni-I (351.5 nm)/Cr-I (399.11 nm) line ratio, (c) Ni-I (352.45 nm)/Cr-I (396.39 nm) line ratio, and (d) Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio.
oxygen residing near laser-material interaction region could promote the oxidation of the Cr in plasma plume. This oxidation process adds extra heat to plasma plume by exothermic reaction. As a result, bright and high temperature plasma is produced when the powder with high Cr composition is used. 3.4. Ni composition prediction by regression lines
Fig. 6. Boltzmann plot using Cr-I lines.
Ni composition is predicted using the regression lines obtained for line intensity ratio and plasma temperature. Fig. 8 shows the predicted Ni composition from the regression lines. The regression lines for the line ratio generally show the better prediction of the Ni composition than the regression line for the plasma temperature. The regression line of the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio gives the most accurate prediction among regressions lines obtained in this study. The Ni composition prediction error from the regression line of the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio varies from 0.02% to 4.5% for the given range of the Ni composition. The average error is only 1.6%, which shows a reasonably good accuracy in the prediction of the composition. Relatively large prediction error from the regression lines for the plasma temperature is mostly due to inaccurate curve fitting of the regression line at the lowest Ni composition. Prediction errors for all regression lines are summarized in Table 5. In order to evaluate the validation of the method to predict elemental composition, as-received Inconel 718 powder with a certi-
Table 4 Ionization potential for Ni and Cr.
Fig. 7. Plasma temperature as a function of the Ni atomic percentage.
Element
1st ionization potential
2nd ionization potential
Ni Cr
737.1 kJ/mole 652.9 kJ/mole
1753.0 kJ/mole 1590.6 kJ/mole
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are used to determine plasma parameters such as a line intensity ratio and plasma temperature. Using them, the correlation between the plasma parameters and Ni composition is successfully developed and validated. It is shown that the line ratio generally gives the better prediction of the Ni composition than that of the plasma temperature. The smallest prediction error obtained is only 1.6%, which proves the feasibility of the composition monitoring method developed in this study. The results from this study may suggest that the plasma diagnostics reported in this study could be used in various plasma-based deposition and etching processes for monitoring of the important material properties. Acknowledgements Fig. 8. Ni composition (at.%) predicted by different regression lines. Straight line shows the target composition of the DMD layer: square, using Ni-I (351.5 nm)/Cr-I (396.36 nm) line ratio regression line; circle, using Ni-I (351.5 nm)/Cr-I (399.11 nm) line ratio regression line; triangle, using Ni-I (352.45 nm)/Cr-I (396.36 nm) line ratio regression line; diamond, using Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio regression line; star, using plasma temperature regression line.
This work was supported by the National Science Foundation (NSF) Industry-University Co-operative Research Center and GE Aviation under the NSF sub-award No. 0438917.
Appendix A. Supplementary material Table 5 Ni composition prediction error by regression lines. Regression line for
Line ratio, Ni-I (351.5 nm)/Cr-I (396.36 nm) Line ratio, Ni-I (351.5 nm)/Cr-I (399.11 nm) Line ratio, Ni-I (352.45 nm)/Cr-I (396.36 nm) Line ratio, Ni-I (352.45 nm)/Cr-I (399.11 nm) Plasma temperature
Supplementary data associated with this article can be found, in the online version, at https://doi.org/10.1016/j.optlastec.2018.03. 020.
Error (%) Range
Average
2.5–8.3 6.1–18 2.6–10.4 0.02–4.5 6.7–32
4.6 12.2 5.2 1.6 12.6
Fig. 9. Ni composition measured during the DMD of alloyed Inconel 718 powder with a certified Ni composition of 50.9 atomic percentage.
fied Ni concentration of 50.9% (in at.%) is only used for DMD experiment. Fig. 9 shows the Ni concentration predicted during the DMD process. The regress lines for Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio and plasma temperature are used to predict the Ni composition. The case using the line ratio gives the better accuracy in prediction again than that using the plasma temperature. Average prediction for the Ni composition is 51.8% (error 1.6%) when the Ni-I (352.45 nm)/Cr-I (399.11 nm) line ratio is used for prediction. The method using the plasma temperature shows average prediction of 49.7% (error 2.5%). 4. Conclusions Elemental composition monitoring during the DMD process is carried out by plasma diagnostics using the OES. Atomic spectral lines of two main elements, Ni and Cr, in Ni-base alloy powders
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