(1)Materials Transactions, Vol. 46, No. 12 (2005) pp. 2641 to 2646 Special Issue on Growth of Ecomaterials as a Key to Eco-Society II #2005 The Japan Institute of Metals. Application of Nd:YAG Laser to Aluminum Alloy Sorting Hiroshi Nishikawa1 , Kouhei Seo2; * , Seiji Katayama1 and Tadashi Takemoto1 1 2. Joining and Welding Research Institute, Osaka University, Osaka 567-0047, Japan Graduate school of Engineering, Osaka University, Osaka 565-0081, Japan. It is important to develop an effective sorting system of aluminum to reduce the cascade recycling of aluminum scraps by instead returning the scraps to wrought aluminum. A feasibility study has been conducted to develop a new sorting process of aluminum scraps. In this study, irradiation of an aluminum surface by pulsed Nd:YAG laser and an automatic sorting method by a pattern-matching method were tested to identify the alloy number of aluminum scraps. For sorting test samples, seven aluminum alloys (1050, 2024, 3003, 4343, 5052, 6063, 7075) were selected from seven wrought aluminum alloy series. The surface of the aluminum irradiated and melted by a YAG laser beam. The surface morphology, including the molten area, brightness profile and change in color, was observed after irradiation. There was a difference in the surface morphology among the aluminum alloys after irradiation. The effect of laser irradiation conditions such as the defocus distance, input energy and laser irradiation angle on the surface morphology after irradiation was investigated to establish the appropriate conditions of laser irradiation for sorting aluminum alloys. It was clear that the surface morphology of aluminum seems to depend on physical properties such as thermal conductivity and liquidus temperature. Therefore, it seems possible to establish an automated aluminum sorting method by using the pattern matching method on irradiated aluminum samples. (Received June 21, 2005; Accepted September 9, 2005; Published December 15, 2005) Keywords: aluminum scraps, sorting, wrought aluminum, laser irradiation, surface morphology, pattern matching. 1.. Introduction. Aluminum alloys have been used for the manufacture of cars since the earliest days of the motor industry. In recent times, the use of aluminum alloys has been increasing, especially in automobiles.1) The benefits promised by cars containing aluminum are these: they consume less energy and create fewer polluting emissions. The total annual consumption of aluminum alloy is almost 4 million tons in Japan. As the amount and applications of aluminum increase, the quantity of aluminum scraps, including wrought aluminum and cast aluminum, also continues to increase year after year. Therefore, a recycling technology of aluminum scraps is very important.2) To sell the aluminum scraps for a high price, their alloy numbers (series) must be known and they must be segregated or sorted. Up to now, no appropriate sorting method has been developed; therefore, all mixed aluminum scraps are used as materials for casting, because casting materials have a large tolerance for alloying elements. The method for this type of consumption is cascade recycling, that is, the recycling of high-grade wrought aluminum scraps into low-grade casting materials. However, if this trend continues, the supply of mixed aluminum scraps will outstrip the demand for cast materials. Therefore, all aluminum scraps should be effectively recycled for the waste reduction and energy efficiency. The recycling of aluminum scrap requires only approximately 3% of the energy needed to produce it from ore. Generally speaking, recycling is a very effective way of reducing the load to the global environment. In other research, several papers discuss the recycling of aluminum scrap.3–8) For example, Gronostajski and Matuszak investigated a new method of recycling aluminum and aluminum alloy chips coming from the machining of semifinished products.3) Xiao pointed out that an understanding of *Graduate. Student, Osaka University. the differences between the types of scrap is crucial to the recycling of the scraps because of their complexity of compositions and contaminants.8) It is necessary to establish a more effective recycling system in order to return wrought aluminum to wrought materials, and consequently reduce the cascade use of aluminum to cast materials. So, an automated sorting system of aluminum scraps according to alloy number is required to prevent the increase of mixed aluminum scraps for cascade use. Some sorting technology have already been proposed and studied for light metal recycling: for example, the technology based on laser-induced optical emission spectroscopy is being developed.2,6,9,10) But, these technologies seem to be insufficient for sorting mixed aluminum scraps according to alloy number, because it has been difficult to quantitatively analyze the composition of aluminum alloys with accuracy. On the other hand, laser-induced plasma spectroscopy was also studied for instant identification of post-consumer plastics.11) Recently Nd:YAG laser is frequently used as industrial applications.12–14) As a welding application for aluminum alloy, the effect of aluminum alloy number on the weldability of Nd:YAG laser welding has been studied.15) The purpose of this author’s work is to correctly identify the alloy number of aluminum ally samples by laser irradiation using the Nd:YAG laser. This is a basic study for developing the automated sorting system of aluminum scraps to establish the recycling system of wrought aluminum to wrought materials. Specifically, the effect of laser irradiation conditions such as defocus distance, input energy and laser irradiation angle on the surface morphology after irradiation was investigated to establish the appropriate conditions of laser irradiation for sorting aluminum alloys. 2.. Experiment. Figure 1 shows the schematic diagram of the experimental apparatus for the laser irradiation method. Pulsed Nd:YAG.

(2) 2642. H. Nishikawa, K. Seo, S. Katayama and T. Takemoto. Laser irradiation unit. Molten area, A / mm 2. Laser incident angle. Laser oscillator Sample. −. 1050 5052. 4. Defocus. YAG LASER. + distance. 2024 6063. 3003 7075. 4343. 3 2 1 0 -15. -10. -5. 0. 5. 10. 15. Defocus distance, d / mm. Fig. 1 Schematic diagram of experimental apparatus for laser irradiation method.. Fig. 2 Effect of defocus distance on molten area by laser irradiation. ( ¼ 10 , E ¼ 5 kW  7 ms). 3.. Result and Discussion. Table 1 Experimental parameters for laser irradiation in this work. Defocus distance (mm): d. 15, 10, 5, 0, 5, 10, 15. Input energy (J): E Peak power (kW)Pulse width (ms) Laser incident angle (degree): . 5:0  7:0, 5:0  10:0, 7:0  5:0, 7:5  6:5 10, 20, 30, 40, 50. laser was used as the heat source to melt the surface of the sample. This laser beam is suitable for this experiment because it can partially melt the surface. Table 1 shows the experimental parameters for the laser irradiation. As shown in this table, the input energy, laser incident angle and defocus distance were varied. The effect of these parameters on the surface morphology after irradiation was investigated to establish the appropriate conditions of laser irradiation for sorting aluminum alloys. After the surface of the sample was irradiated, the surface morphology was observed, including the molten area, brightness profile and change in color. Then, the features of the morphology after laser irradiation were extracted for identifying the aluminum alloy numbers. Seven representative aluminum alloy samples were selected from seven wrought aluminum alloy series; 1050, 2024, 3003, 4343, 5052, 6063 and 7075. The basic properties of these aluminum alloys are summarized in Table 2. The size of all samples was 50 mm  50 mm  6 mm.. Table 2. Alloy number. 3.1 Melting of the aluminum alloy To establish the appropriate experimental conditions to identify the aluminum alloy, the effect of laser irradiation conditions, such as defocus distance, input energy and laser irradiation angle on the surface morphology after laser irradiation was investigated. Firstly, the effect of the defocus distance, which is the focus-to-sample distance as shown in Fig. 1, on the morphology of the irradiated area was investigated. The input energy was 5 kW  7 ms and the laser incident angle was 10 . The measuring results of the molten area for seven samples are shown in Fig. 2. For each sample, the molten area is quite different according to defocus distance. On the focus point (the defocus distance is 0 mm), there isn’t a significant difference in the molten area among alloys. On the other hand, the defocus distance of 15 mm gave the best results for identifying the difference in surface morphology after irradiation, because the molten areas significantly differs from each other under this distance compared to other defocus distances. Figure 3 shows examples of the irradiated area using the laser beam at the defocus distance of 0 mm [Fig. 3(a)] and 10 mm [Fig. 3(b)]. The aluminum alloy shown is 1050 alloy. It is clear that not only the molten area but also the surface morphology is quite different according to the defocus distance. On the focus point, the surface of. Basic properties of test samples for this experiment. Nominal chemical composition (max or range, mass %). Alloy system Si. Cu. Mn. Mg. Zn. Al. Thermal conductivity (W/mK). Liquidus temperature (K). 1050. Al. 0.25. 0.05. 0.05. 0.05. 0.05. Bal.. 231. 930. 2024. Al–Cu. 0.5. 3.8–4.9. 0.3–0.9. 1.2–1.8. 0.25. Bal.. 193. 911. 3003. Al–Mn. 0.6. 0.05–0.2. 1.0–1.5. —. 0.1. Bal.. 193. 928. 4343. Al–Si. 11.0–13.5. 0.5–1.3. —. 0.8–1.3. 0.25. Bal.. 180. 886. 5052 6063. Al–Mg Al–Mg–Si. 0.25 0.2–0.6. 0.1 0.1. 0.1 0.1. 2.2–2.8 0.45–0.9. 0.1 0.1. Bal. Bal.. 138 218. 923 928. 7075. Al–Zn–Mg. 0.4. 1.2–2.0. 0.3. 2.1–2.9. 5.1–6.1. Bal.. 130. 908.

(3) Application of Nd:YAG Laser to Aluminum Alloy Sorting. 2643. (b). (a). Fig. 3 Effect of defocus distance on surface morphology. (a) d ¼ 0 mm, (b) d ¼ 10 mm (Aluminum alloy: 1050,  ¼ 10 , E ¼ 5 kW  7 ms). 6 1050 5052. 5. 2024 6063. 3003 7075. 1050 5052. 4343. 4 3 2 1. Molten area, A / mm2. Molten area, A / mm 2. 6. 5. 2024 6063. 3003 7075. 4343. 4 3 2 1 0. 0 5kW 7ms. 7kW 5ms. 5kW 7.5kW 10ms 6.5ms. Input energy, E / J Fig. 4 Effect of input energy on molten area by laser irradiation. (d ¼ 15 mm,  ¼ 10 ). irradiated area is extremely rough because of the high-power laser irradiation. The effect of input energy, which is the product of the peak power and pulse width for laser output, was investigated next. The defocus distance was 15 mm and the laser incident angle was 10 . The measuring results of the molten area for the seven samples are shown in Fig. 4. The molten area for 7 kW  5 ms is larger than that for 5 kW  7 ms because of the stronger peak power. On the other hand, the molten area for 5 kW  10 ms is almost similar to that for 5 kW  7 ms, in spite of the longer pulse width. It is clear that peak power rather than pulse width has a larger effect on the molten area. In view of the performance limitation for the laser oscillator, the input energy of 7:5 kW  6:5 ms gave the best results for identifying the difference of the surface morphology after irradiation. The effect of the laser incident angle on the morphology of the irradiated area was investigated. The defocus distance was 15 mm and the input energy was 7:5 kW  6:5 ms. The measuring results of the molten area for the seven samples are shown in Fig. 5. Except for 1050 alloy, the molten area for each sample does not significantly change according to laser incident angle. For the 1050 alloy, the mirror-like surface of the sample seems to reflect the laser beam when. 0. 10. 20. 30. 40. 50. Laser incident angle, θ /degree Fig. 5 Effect of laser incident angle on molten area by laser irradiation. (d ¼ 15 mm, E ¼ 7:5 kW  6:5 ms). the laser incident angle is 30 , 40 and 50 . Figure 6 shows examples of the irradiated area for the laser incident angle of 10 [Fig. 6(a)] and 50 [Fig. 6(b)]. Aluminum alloy is 5052 alloy. At 10 , the shape of the irradiated area is almost round. At 50 , the shape becomes elliptical, although the molten area is almost similar according to the incident angle. So, it is clear that the laser incident angle of 10 gave the best results for identifying the difference of surface morphology after irradiation. Judging from the above results, the appropriate conditions of laser irradiation for sorting aluminum alloys in this study is as follows: defocus distance is 15 mm, input energy is 7:5 kW  6:5 ms and the laser irradiation angle is 10 . Figure 7 shows the surface morphologies after irradiation by the laser beam under these conditions. As shown in this figure, the size, the color and the shape of the molten area are different among the samples. Therefore, depending on these differences, it is possible to identify the alloy number. These differences of the molten area seem to be caused mainly by the differences of the physical properties, such as the thermal conductivity and liquidus temperature, which depend on the chemical composition. Figure 8 shows the effect of thermal conductivity on the molten area. The molten area surely trends to increase with the decrease of thermal conductivity. Figure 9 shows the effect of the liquidus temperature on the.

(4) 2644. H. Nishikawa, K. Seo, S. Katayama and T. Takemoto. (a). (b). Fig. 6 Effect of laser incident angle on surface morphology. (a)  ¼ 10 , (b)  ¼ 50 (Aluminum alloy: 5052 alloy, d ¼ 15 mm, E ¼ 5 kW  7 ms). 3003. 6. 2024. Molten area, A / mm2. 1050. 4343. 1050 5052. 5. 2024 6063. 3003 7075. 4343. 4 3 2 1 0 100. 150. 200. 250. Thermal conductivity, λ / W/m • K 5052. Fig. 8 Relationship between molten area and thermal conductivity. (d ¼ 15 mm,  ¼ 10 , E ¼ 7:5 kW  6:5 ms). 6063. 7075. 1.0mm. Fig. 7 Surface morphology of each aluminum alloy sample after irradiation. (d ¼ 15 mm,  ¼ 10 , E ¼ 7:5 kW  6:5 ms). Molten area, A / mm2. 6 1050 5052. 5. 2024 6063. 3003 7075. 4343. 4 3 2 1 0 880. 900. 920. 940. Liquidus temperature, T / K. molten area. The molten area trends to increase with the decrease of liquidus temperature. It is clear from these figures that there is a close relationship between the molten area and physical properties such as thermal conductivity and liquidus temperature. It was found that characteristic features could be extracted from each aluminum alloy by the laser irradiation method and the features could be used for the identification of the aluminum alloy series. Therefore, in fact, it would be possible to sort the aluminum scraps according to the. Fig. 9 Relationship between molten area and liquidus temperature. (d ¼ 15 mm,  ¼ 10 , E ¼ 7:5 kW  6:5 ms). aluminum alloy number by using the laser irradiation method. 3.2 Pattern matching method It is necessary to automatically sort the aluminum scraps when the sorting system is utilized commercially. Therefore, the investigation of a pattern-matching method using an.

(5) Application of Nd:YAG Laser to Aluminum Alloy Sorting. Brightness value. 300 200 100 0. Fig. 10 Brightness distribution of 1050 alloy in reference data.. image processing system was performed to establish an automated sorting system of mixed aluminum scraps. In this study, the brightness distribution reflected from the aluminum surface was used as comparative data for the patternmatching method. The brightness distribution, which represents the surface morphology, was described with 256 tones. After irradiation by the laser beam, the brightness distribution on the surface of seven samples (1050, 2024, 3003, 4343, 5052, 6063, 7075) was measured to the create referential data, di (d1 ; d2 ; d3 ; . . . ; di ; . . . ; dn ) where di indicated the brightness value of reference aluminum at position i, that was stored in a computer. For example, Fig. 10 shows the brightness distribution of 1050 alloy in the reference data. Seven unknown samples, which were called No. 1–No. 7, were prepared. In fact, No. 1 was 1050 alloy, No. 2 was 2024 alloy, No. 3 was 3003, No. 4 was 4343, No. 5 was 5052, No. 6 was 6063, and No. 7 was 7075. For the identification of an unknown aluminum alloy, the surface was irradiated and the brightness distribution on the surface was measured and the unknown aluminum data was obtained, hi (h1 ; h2 ; h3 ; . . . ; hi ; . . . ; hn ) where hi indicated the brightness value of the unknown aluminum at position i. The brightness data of the unknown aluminum alloy was compared with the reference data stored in the computer. The difference between the reference data and the unknown aluminum data was computed as shown below, n 1X G¼ jdi  hi j ð1Þ n i¼1 where G is the difference value. When the difference value is smallest, the unknown aluminum is approximately equal to. 2645. the aluminum alloy for the smallest reference data. The alloy number of unknown aluminum is determined. The difference values computed from eq. (1) are shown in Table 3. The table shows the correlation of the unknown sample data, No. 1–No. 7, with the reference data, 1050– 7075. The smallest value for the unknown sample numbers in a row corresponded to the reference data listed in the same row. In other words, the alloy number of the unknown aluminum alloy was decided. Actually, No. 1 fits with 1050, No. 2 fits with 2024, and so on. Therefore, the identification of the unknown aluminum alloys was successfully performed. It was clear that the patter-matching method is useful for the identification of aluminum alloys to automatically sort the mixed aluminum alloys. The basic feasibility of applying the laser irradiation method to automatic sorting system for aluminum scraps was investigated and satisfying results was obtained as described above. As the next step for using commercially, further investigation into irradiation-condition tolerance for sorting is required. On the other hand, in this study, new aluminum alloy samples were used for test samples. Actual aluminum scraps are only from used products. Aluminum scraps exist as irregularly shaped particles and the surface is contaminated by dirt, paint and abrasion. Therefore the effect of the scrap shape and surface on the identification accuracy is now being addressed. 4.. Conclusion. The investigation into the sorting system using the laser irradiation method was performed to sort aluminum scraps according to the aluminum alloy number. The results obtained in this work are summarized as follows. (1) The appropriate conditions of pulsed Nd:YAG laser for sorting aluminum alloys in this study are obtained aas the following: defocus distance is 15 mm, input energy is 7:5 kW  6:5 ms and laser irradiation angle is 10 . (2) When the surface of the aluminum is irradiated and melted by the laser beam, there is a significant difference in the surface morphology depending on the physical properties. (3) The differences of the surface morphology after laser irradiation could be used to identify the aluminum alloy number, and it is possible to sort the aluminum alloys according to their alloy number. (4) It is found that the pattern-matching method is useful to automatically sort aluminum alloy scraps.. Table 3 Result of pattern matching for unknown samples. No. 4. No. 5. No. 6. 1050. No. 1 24:65. No. 2 80.86. No. 3 52.24. 52.41. 41.78. 47.03. No. 7 44.90. 2024. 90.24. 18:30. 107.22. 93.07. 65.13. 63.06. 87.02. 3003. 65.06. 101.83. 15:29. 29.47. 56.56. 60.70. 63.35. 4343. 67.22. 89.64. 32.82. 11:46. 40.59. 39.86. 62.21. 5052. 55.72. 57.37. 61.60. 42.48. 19:53. 22.07. 51.29. 6063. 54.04. 56.78. 65.85. 45.36. 22.03. 19:31. 51.27. 7075. 45.72. 64.69. 62.46. 55.51. 37.83. 36.25. 37:28.

(6) 2646. H. Nishikawa, K. Seo, S. Katayama and T. Takemoto. REFERENCES 1) D. Carle and G. Blount: Mater. Design 20 (1999) 267–272. 2) G. Hoyle: Resource, Conservation and Recycling 15 (1995) 181–191. 3) J. Gronostajski and A. Matuszak: J. Mater. Process. Technol. 92–93 (1999) 35–41. 4) Y. Xiao and M. A. Reuter: Miner. Eng. 15 (2002) 963–970. 5) M. Samuel: J. Mater. Process. Technol. 135 (2003) 117–124. 6) A. Gesing, C. Stewart, R. Wolanski, R. Dalton and L. Berry: 4th Int. Symp. on Recycling of Met. and Engineered Mater., (2000) pp. 1233– 1249. 7) T. P. R. de Jong, H. U. R. Kattentidt and W. L. Dalmijn: 4th Int. Symp. on Recycling of Met. and Engineered Mater., (2000) pp. 1263–1275. 8) Y. Xiao, M. Reuter, P. Vonk and J. Vonken: J. Mater. Process. Technol.. 127 (2002) 96–106. 9) H. P. Sattler: 3rd Int. Symp. on Recycling of Met. and Engineered Mater., (1995) pp. 57–64. 10) A. Rosenfeld, A. Gesing and B. Farahbakhsh: 3rd Int. Symp. on Recycling of Met. and Engineered Mater., (1995) pp. 751–763. 11) J. M. Anzano, I. B. Gornushkin, B. W. Smith and J. D. Winefordner: Polym. Eng. Sci. 40 (2000) 2423–2429. 12) E. C. P. Wong, A. P. Hoult, J. K. Kim and T. X. Yu: J. Mater. Process. Technol. 63 (1997) 579–584. 13) M. Hua, T. Shao, Y. T. Hong and E. C. H. Man: Surf. Coat. Technol. 185 (2004) 127–136. 14) G. K. L. Ng and L. Li: Opt. Laser Technol. 33 (2001) 393–402. 15) M. J. Cieslak and P. W. Fuerschbach: Metall. Trans. B 19B (1988) 319– 328..

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