METAL RECOVERY FROM WASTE

Transcription

1 METAL RECOVERY FROM WASTE Helga Marise Jordão Ferreira Instituto Superior Técnico, Universidade de Lisboa, Lisboa, 2014 ABSTRACT In shredding plants end of life vehicles (ELV) are first shred in pieces and then separate in mixed scrap by mechanical processing. The mixed scrap is sent to specialized processing plants to achieve high grade fractions of different material streams for metallurgical and other uses. In Portugal, right now, there aren t specialized processing plants, and thus the mixed scrap is exported. This work was developed in collaboration with Recifemetal S.A. shredding plant. The main objective was to identify processing techniques for mixed scrap of non-ferrous metals with the aim to integrate a specialized processing line of non-ferrous metals in the company. A representative non-ferrous sample from a shredding plant was studied. Zorba 0-25 is 66% of aluminum, 7% of copper, 15% of brass/bronze and 6% of zinc alloy. The remaining 6% are nonmetallic and mixed particles. Gravity concentration with shaking table was chosen to separate the light fraction from the heavy fraction.. Design of experiments, two level complete design, was used to study the separation of fraction <10mm with shaking table. The results of the optimal response show 3 products with high grade (>90%). 1. INTRODUCTION In the European Union (EU) the recycling of scrap has increased significantly in recent decades, representing between 40% and 60% of metal production (COM (2008) 699). Recovering metals such as steel, iron, copper and aluminum for recycling is not only economically viable, but energy efficient and environment sound (i.e. reduce volumes waste from extractive industry). Also, scrap recycling helps to decrease the strong dependence of Europe on imports of metallic resources. One type of waste that has high metal grade is end-of-life vehicles (ELV). The typical composition of an ELV is: 68% of ferrous metals, 8% of non-ferrous metals and 24% of nonmetals (i.e. plastics, rubber) (TRL2003). ELV recycling is an industry that exists for decades driven by metal recovery and re-sale of used parts. Presently about 75% of total mass of an ELV is recycled within the EU, however, the percentages of reuse, recycling and recovery vary significantly between member states (Eurostat, 2014). 1

2 ELV typical operations include depollution (removal of hazardous components, i.e. battery, fluids, oil) and manually dismantled for reusable or recyclable parts (i.e. tires and alloy wheels). Then vehicle-hulk is sent to shredding plants. A general flow sheet for the processing of car scrap is given in Figure 5. Size reduction is carried out in car shredders to obtain appropriate liberation of materials to be separated. Steel is recovered by magnetic separation and after is hand sorted to remove copper or other non-metals materials that eventually are present in this fraction. The nonferrous mix is screened into several size fractions to improve subsequent separation. Typical size fractions produced from the nonferrous mix are 0 12 mm, mm, and +65 mm. The largest size fraction is usually hand sorted to recover the nonferrous metals. The nonferrous metal content of the mm fraction starts with the removal of non-metallic components, such as plastic, textile, and wood, using eddy current subsequently, the resulting nonferrous pre-concentrate is subjected to a two-step heavy medium sink-float separation at different medium densities. The first step is carried out at a cut density of 2.0g/cm 3 to separate magnesium (having a specific gravity of ρ=1.74 g/cm 3 ) together with heavy plastics and rubber. In the second step, the medium density is set at about 3.0 g/cm 3 to separate aluminum (ρ=2.7 g/cm 3 ) from the heavy nonferrous metals (ρ>6 g/cm 3 ). The sink product of the second heavy medium separation step is a heavy nonferrous mix, mainly consisting of copper, brass, zinc alloys, (Figure 7). The fine fraction (<12mm) is normally exported to Southeast Asia countries for manual sorting as it is not economically viable in Europe. The aim of this study was to evaluate the use of shaking table to separate the fine fraction of non-ferrous scrap. For the study it was used a non-ferrous scrap sample from a shredding plant located in Portugal. Full factorial design in two levels was used to design the experiment and to develop a mathematical model describing the relationship between recovery of copper and aluminum and three operating parameters. 2. MATERIALS AND METHODS 2.1. Materials characterization A representative sample of non-ferrous scrap of a shredding plant from Portugal was used in this study. Size analysis through screening, visual composition analysis by particle size class and particle shape was conducted. Aluminum and copper particles from fraction <10mm were milled separately with a cutting mill with an 8mm sieve. The milled samples were subjected to screening with a sieve of 2mm to remove the fines particles create by the mill (less than 0.5% of the total mass). Has the method define to characterize shaking table product s was hand sorting only aluminum and copper were selected to simplify. Two samples (A1 and A2) were created with 70% of aluminum and 30% of copper and they were used as the feed for shaking table separation. 2

3 2.2. Shaking table A Wilfley shaking table was used in this study. It consists of a slightly inclined and of rectangular shape, covered with riffles (raised bars running perpendicular to the feed side of the table). The feed enters on the top of the table where there is also the feed water. In mining processing the feed is done by pulp, but in this study it was a dry feed. Wash water is distributes longitudinally to the table. The table is vibrated longitudinally using a slow forward stroke and a rapid return, which causes the particles to move along the deck parallel to the motion. Under the effect of table motion and flowing film by the wash water, the particles stratify with the heavier particles on the bottom, and they move from right to left. Owing to decreasing taper of the riffles, the exposed upper surface of the stratified material is acted upon by crosscurrents of water and by the inclination of the deck, as indicated by the arrow, and is moved downhill. Shaking table technique was applied on feed 2-8 mm size fraction, and three parameters were studied. The parameters are namely: inclination angle, feed water rate and wash water rate Figure 1: Wilfley shaking table unit. 1: Feeding water; 2: Dry feed; 3: Shaking mechanism; 4: Washing water; 5: Heavy products discharge; 6: Light products discharge Preliminary study A preliminary study was carried out to determine a narrower set of parameter ranges for yield optimization. The preliminary study was conducted in the same apparatus and with the same procedure as design of experiments. In the preliminary experiments, inclination angle range of 0-17º, feeding water range 0-8L/min and washing water range 0-8L/min were examined. According to preliminary results, the study ranges chosen for inclination angle, feeding water and washing water were 13-15º, 1-3L/min e 3-5L/min, respectively Experimental design and data analysis Software package, Design-Expert 9.0.3, Stat-Ease, Inc., Minneapolis, USA, was used for experimental design, data analysis, and model building to study the relationship between copper and aluminum recovery and three operating parameters. Analysis of variance (ANOVA) was used to estimate the statistical parameters. F-test was used to estimate the significance of all terms in the polynomial equation within 95% confidence interval. Table 1 shows 2 3 full 3

4 factorial design matrix. The three selected operating parameters, inclination angle, feeding water rate and washing water rate were defined as X1, X2, and X3, respectively. Each parameter was coded at two levels, -1 (minimum), and +1 (maximum). Copper recovery response was coded as ηcu and aluminum recovery response as ηal. Running the full complement of all possible factor combinations means that we can estimate all the main and interaction effects. There are three main effects, three two-factor interactions, and one threefactor interaction, all of which appear in the full model as follows: Y = β0 + β1x1 + β2x2 + β3x3 + β12x1x2 + β13x1x3 + β23x2x3 + β123x1x2x3 + ε (Eq.1) In Eq.1 Y is the predicted response, β 0, βi and β ij are the regression parameters. Eq. 1 was then modified by eliminating the terms found statistically insignificant, starting from the high-order ones. The final model will be presented as Eq. 2 and Eq.3. Table 1: Plan experiments domain defined by levels of the parameters Factors Symbol Unit Inclination angle A º Feeding water rate B L/min 1 3 Washing water rate C L/min 3 5 Table 2: Full factorial 2 3 design matrix and experiments results. Run Coded Factors Responses X1 X2 X3 ηcu (%) ηal (%) ,7 43, ,2 13, ,8 4, ,1 0, ,3 0, ,5 0, ,0 2, ,2 0, ,2 46, ,7 8, ,5 26, ,1 8, ,6 38, ,4 0, ,6 3, ,0 0,1 4

5 Acumulative passing (%) 3. RESULTS AND DISCUSSIONS 3.1. Characterization of non-ferrous scrap The results shown particle size lies between 0-20mm. The composition is 66% of aluminum, 7% of copper, 15% of brass/bronze and 6% of zinc alloy. The remaining 6% correspond to nonmetallic and mixed particles. The analysis of composition by size class revealed no significant differences in composition by particle size. In terms of shape the fraction size >10mm have mainly flat shape and irregular boundaries and the other fraction (<10mm) display an elongated shape, like cables Size (mm) Figure 2: Distribution curve of the reference sample 15% 7% 3% 6% 3% 66% Aluminum Copper Brass Zinc alloy Contaminants Mix particles Figure 3: Sample composition 5

6 % by mass of an material in the size class mm mm mm mm -10+8mm -8+6mm -6+4mm -4+2mm 0 Aluminum Copper Brass Zinc alloy Contaminants Mix particles Figure 4: Composition by size class Experiment results and data analysis The Design-Expert software program was used to analyze each response to the regression model of the parameters listed in table 1.Table 2 shows the experiment results along with the design matrix. In table 3 and 4 represents the ANOVA statistical analysis for both copper recovery response and aluminum recovery response, respectively. The factors angle inclination, feeding water and washing water are all significant factors for copper recovery. For aluminum recovery the factors with significance are the same as before more the interaction between inclination angle - feeding water and inclination angle washing water. The values in table 3 and 4 indicate the will fitting of the experimental results to the polynomial model equations for both responses and hence accuracy of these models. η Cu = X1 4.90X X3 Eq. 2 η Al = X1 6.60X2 6.68X X1X X1X3 Eq.3 6

7 Source Table 3: ANOVA for copper recovery response. Sum of squares Degree of freedom Mean square F-value p-value Model < X1-inclination angle < X2 - Feeding water X3 Washing water < X1X X1X X2X X1X2X Pure error Correction total Table 4: ANOVA for aluminum recovery response. Source Sum of squares Degree of freedom Mean square F-value p-value Model < X1-inclination angle < X2 - Feeding water < X3 Washing water < X1X X1X X2X X1X2X Pure error Correction total Optimization of the experimental parameters Table 5 shows the optimum parameters that give maximum recovery of coper with minimum recovery of akuminum. The results of applying the optimum parameters obtained (Table 5) for shaking table separation are shown in table 6. It is shown that a shaking table concentrate with 95.6 % Cu and 77.8 % recovery is obtained. 7

8 Table 5: Optimization parameters for shaking table separation. Parameters Inclination angle (degree) Feeding water rate (L/min) 2.78 Washing water rate (L/min) 4.95 Table 6: Responses of shaking table at optimum parameters. Box 1 Box 2 Box 3 Copper recovery (%) 77.8% 21.8% 0.4% Aluminum recovery (%) 1.5% 85.0% 13.5% Cooper grade (%) 95.6% 9.9% 1.3% Aluminum grade (%) 4.4% 90.1% 98.7% 4. Conclusions Separation between the light and heavy fraction using shaking table gravity separation was successfully achieved. A statistical design using the full factorial 2 3 design of experiments was conducted to study the effect of main combination parameters. Two mathematical models for calculation of copper and aluminum recovery in the separation is suggested according to the statistical experimental design. The best combination for the shaking table is obtained with inclination angle 11º, feeding water rate 3L/min, and washing water flow rate 5L/min. A shaking table product containing 95.6% Cu and recovery of 77.8 % by weight was obtained from a feed containing 30 % Cu. REFERENCES Anderson, M. J. & Whitcomb, P. J., DOE Simplified: Practical Tools for Effective Experimentation. 2nd ed. New York: Productivity Press. B.I.R., B. o. I. R., Global Non-Ferrous Scrap Flows with focus on Aluminium and Copper, Bruxelas: Bureau of International Recycling. B.I.R., B. o. I. R., Non-Ferrous Metals. [Online] Available at: [Acedido em Julho 2014]. Burt, R. O., Gravity Concentration Technology. In: D. Fuerstenau, ed. Development in Mineral Processing. s.l.:elsevier Science Publishers B.V.. 8

9 COM(2008)699, A Iniciativa "Matérias-Primas" - atender às necessidades críticas para assegurar o crescimento e emprego na Europa, Bruxelas: Comunicação da Comissão ao Parlamento Europeu e ao Concelho. Cortez, L. & Durão, F., Textos de Apoio ao Curso de Técnicas Laboratoriais de Mineralurgia. Lisboa: Instituto Superior Técnico Laboratório de Mineralurgia e Planeamento Mineiro. Fiore, S., Ruffino, B. & Zanetti, M., Automobile Shredder Residues in Italy: Characterization and valorization opportunities. Waste Management, pp Fisher, R., The Design of Experiments, New York: Hafner. Manouchehri, H., Mapping and development of shredding product stream(s): Four shredding plants in Sweden (what should be done for better performance of the plants?), s.l.: JERNKONTORETS FORSKNING The swedish Steel Producers Association. Manouchehri, H., Looking at Shredding Plant Configuration and Its Performance for Developing Shredding Product Stream (An Overview), s.l.: JERNKONTORET FORSKNING The Swedish Steel Producers Association. Wills, B. & Napier-Munn, T., Mineral Processing Technology: An introduction to the pratical aspects of the oretreatment and mineral recovery. 7 ed. New York: Elsevier Science & Technology Books. 9