International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 63 Application of Response Surface Methodology on Beneficiation of Sudanese Chromite Ore via Pilot Plant Shaking Table Separator Mahmoud Motasim Hassan Al-Tigani* 1 , Abdelshakour Awdekarim 2 , Amin Al-Gak Abdueldaem 1 , and Ahmed Abdullah Sadeek Seifelnasr 3 1 Department of Mining Engineering, Faculty of Engineering Sciences, Omdurman Islamic University, Khartoum, Sudan. 2 Department of Chemical Engineering, Faculty of Engineering, University of Khartoum, Khartoum, Sudan. 3 Department of Mining Engineering, Faculty of Petroleum and Mining, Suez Canal University, Suez, Egypt. *Corresponding author: Mahmoud Motasim Hassan Al-Tigani, Department of Mining Engineering, Faculty of Engineering Sciences, Omdurman Islamic University, Khartoum, Sudan, Tel: 00249960579034, E-mail: mahmoud.motasim@oiu.edu.sd Abstract: High grade chromite ore has been decreased constantly due to the importance of chromium element in industrial uses such as metallurgical, chemical, and refractory industries. Therefore, beneficiation of low grade has been more significant .Response Surface Methodology (RSM) is combination of statistical and mathematical methods used for modeling and analyzing problems. In this study, the Central Composite Design (CCD) was applied by using Design-Expert (version 6.0.5) for modeling and optimizing the effect of operating variables on the performance of gravity separation via pilot plant shaking table for chromite ore. Three operating variables were studied, namely feed rate, tilt angle, and flow rate during the tests. The sample under study is low grade chromite ore, containing (30.21%, Cr2O3). The mathematical model equations of ANOVA model revealed that the grade of concentrate is more sensetive for feed rate (g/min) compered to water flow rate (l/min).whereas , recovery of concentrate is more sensetive for tilt angle compered to water flow rate (l/min) and feed rate (g/min). Optimized responses for the beneficiation process were found at concentrate with 48.52% Cr2O3 in with 83.09% recovery and it was achieved at water flow rate 15.33 l/min, tilt angle 2.16 ≈ 2.00 degree, and feed rate of 195.38 g/min. Keywords: Chromite, Mineralogical, Response Surface Methodology (RSM), Central Composite Design (CCD), Pilot Plant Shaking Table, Recovery, Grade, ANOVA Model. 1. Introduction: Chromite (FeO.Cr2O3) is the strategic mineral source for chromium metal , chromium chemicals, refractories, and metallurgical uses[1]. The main use of chromium metal in refractories is the refractory bricks for lining of high temperature furnace, in metallurgy, it is used to produce stainless steels, tool and alloy steels for rod and ball mill media and liners. In chemical industries it is introduced in paint pigments and chemical compounds as an electrolyte in chromium plating baths [2, 3]. Chromite mineral has varied composition based on the chemical formula (Mg, Fe+2) (Cr, Al, Fe+3)2O4. Chromium element can be located as chromium spinel, a complex mineral containing magnesium, iron, aluminum and chromium in varying proportions depending upon the deposit. Iron is replaced by magnesium and similarly chromium by ferric iron and aluminum [4, 5]. Low grade chromite ore is usually treated via gravity separation depended on the differences in specific gravity between chromite mineral and the gangue minerals and rocks such as serpentine and olivine, Spiral concentrators and shaking tables have been used widely in low grade chromite ore processing[6] . Multi Gravity Separator (MGS) is centrifugal force separator used to separate the fine particles (500 10μm) and two minerals closed in specific gravity [7-10]. Various attempts were conducted on development of gravity separation equipment such as shaking table separator[11]. Magnetic separation for chromite mineral is usually performed to improve the Cr/Fe ratio in the concentrate with a Cr: Fe ratio greater than 3:1 for metallurgical uses [12, 13]. In a lower magnetic field intensity (~0.1–0.7 T), chromite mineral can be separated from ferromagnetic minerals (iron-bearing gangue minerals) as the nonmagnetic product [14].Physiochemical separation is used to treatment the ultrafine chromite ore which is generated from comminution stage , selective flocculation method is always used to separate chromite slimes from the gangue[15, 16]. (RSM) is defined as the combination of statistical and mathematical methods that are useful for modeling and analyzing problems[17]. Recently, the application of Response Surface Methodology (RSM) has been used in mineral processing application for obtaining suitable process variables with optimum results at mineral treatment, various experimental designs are used for different objectives such as central composite design was applied for coal cleaning by varying the process variables of multi International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 64 gravity separator[18].However, three-level with three-factor of full factorial experimental design was investigated in different operating parameters on the separation efficiency of Knelson separator[19] . As well as, Box Benhenken experimental design was applied to study the significance of operating parameters on beneficiation of ultrafine chromite particles by selective flocculation [20]. Sudanese chromite ore is considered an important and strategic resource for industrial mineral in Sudan , it occurs in Ingassana Hills in the Blue Nile region and Umm SaqataQala Elnahal in Southern Sudan [21]. Extensive work was conducted for processing of low grade Sudanese chromite using a laboratory shaking table separator and dense media separation [3, 22] . This investigated study aims for modeling and optimization of parameters process via Central Composite Design on beneficiation of massive low-grade Sudanese chromite by using pilot plant shaking table as the separator. 2. Materials and Methods: 2.1 Raw material of chromite sample: A 100 Kg of low-grade chromite ore contained 30.21%, Cr2O3 was taken from the stockpiles of mines at Umm Saqata village in Gedarif, Sudan. The sample was mixed thoroughly to be homogenous, then the representative sample was characterized via Microscopic examinations and X-ray diffraction (XRD). 2.2 Analysis methods: The instrument of X-Ray diffraction (XRD) manufactured by The Analytical X-ray company was used to define phases of minerals using Direct Optical Positioning system (DOPS). For quantitative analysis of minerals oxides, X-ray fluorescence (XRF) was utilized by applied mxios max 4.00kw model. 2.3 Sample preparation: A representative sample of low-grade massive chromite ore was crushed, ground, then screened to -400 μm. The ground product was deslimed via sieve size (80μm), the final ground product was of (-400+80) μm particle size. 2.4 Beneficiation procedure: The central composite design was applied to describe the behavior of relationship between three operating variables. A three factors (feed rate (g/min), tilt angle, and water flow rate (l/min)) and two-level coded (low coded -1 and high coded +1) were used to determine two responses (Grade and recovery) of the produced concentrate. Feed rate (A), water flow rate (B), and tilt angle (C) were independent variables to predict the responses (grade and recovery) of the pilot plant shaking table separator. The independent variables (A, B, C) with their coded and actual levels are presented in Table 1. Table 1.Variables and levels for the two-level and three-factor small factorial design Variables Symbol Real Values of Coded Levels -1 +1 Feed rate (g/min) A 100 200 Water flow rate (l/min) B 15 20 Tilt angle (degree) C 2 4 International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 65 Shaking table of a pilot plant scale was used as the separator to beneficiate low grade chromite ore at Central Metallurgical Research and Development institute in Egypt as depicted in Fig.1. Five hundred grams of low-grade chromite sample (-400+80) μm was used for each experiment. Prior to operation of shaking table, the table was set at required operating conditions for tilt angle and water flow rate l/min, and the then was started. Chromite sample was put into vibration feeder, then continuously fed into the feed box of the table at desired feed rate (g/min), while the vibration feeder was feeding the sample to the shaking table, the sample was separated for heavy minerals (concentrate) and light minerals (tailing). The concentrate and tailing were collected from their collecting pans, then dried and weighed. The concentrate was subjected to (XRF) analysis for chromium oxide quantity evaluation. The above procedure was repeated for each experiment, then ANOVA for Response Surface Quadratic Model was applied on the results of beneficiation for modeling and optimization the parameters of concentration. 3. Results and discussion 3.1 Characterization studies: The results of microscopic studies of the thin and polish sections made from the chromite ore sample are given in Plat.1. Plat.1 (a) reveals that the serpentine rock filling the cracks and it is surrounded by opaqueness minerals (chromite, magnetite, and hematite). Plat.1 (b) demonstrates that the chromite and magnetite particles appeared in euhedral shape and massive texture. The associated gangue minerals with chromite mineral are mainly silicates minerals. Figure.1 shows the X-ray diffraction (XRD) pattern of chromite sample, it reveals that the main phases of mineral in the sample of investigated study are chromite (FeCr2O3), Talc (Mg3 (Si2O5)2(OH) 2), and Magnetite (Fe3O4). Figure 1.Pilot plant shaking table separator. International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 66 (a) (b) Plate. 1. Microscopic studies result for a) thin section sample and b) polish section sample original sample 02-1398 (D) Chromite Cr2O3*CoO Y: 22.92 % d x by: 1. WL: 1.5406 Cubic I/Ic PDF 1. S-Q 10.4 % 25 -1376 (D) Magnetite - (Fe,Mg)(Al,Cr,Fe,Ti)2O4 Y: 33.33 % d x by: 1. WL: 1.5406 Cubic I/Ic PDF 1. S-Q 15.1 % 83 -1381 (C) Chlorite, chromian Mg5.0Al0.75Cr0.25Al1.00Si3.00O10(OH)8 Y: 50.00 % d x by: 1. WL: 1.5406 Triclinic I/Ic PDF 0.6 S-Q 39.0 % 73 -0147 (C) Talc Mg3(Si2O5)2(OH)2 Y: 50.00 % d x by: 1. WL: 1.5406 Triclinic I/Ic PDF 1. S-Q 21.6 % 73 -2376 (C) Chlorite Mg6Si4O10(OH)8 Y: 27.08 % d x by: 1. WL: 1.5406 Triclinic I/Ic PDF 0.9 S-Q 13.9 % Operations : Smooth 0.080 | Smooth 0.080 | Smooth 0.080 | Smooth 0.080 | Smooth 0.080 | Strip kAlpha2 0.000 | Background 0.000,1.000 | Impor D:\Abdalla\original sample.RAW File: original sample.RAW Type: 2Th/Th locked Start: 4.000 ° End: 70.000 ° Step: 0.020 ° Step time: 0.5 s Temp.: 25 °C (Room) Time Started: 0 s 2-Theta: 4.000 ° Theta: 2.0 L in ( C o u n ts ) 0 10 20 30 40 50 60 2-Theta Scale 4 10 20 30 40 50 60 70 d = 1 4 .2 0 8 9 8 d = 9 .3 2 8 0 5 d = 7 .1 6 4 7 7 d = 4 .7 6 8 1 1 d = 3 .5 7 4 2 2 d = 3 .1 1 1 1 8 d = 2 .9 3 0 0 6 d = 2 .4 9 9 5 7 d = 2 .0 6 8 2 7 d = 1 .5 9 4 2 9 d = 1 .4 6 6 2 4 Figure 2.X-ray diffraction (XRD) pattern of chromite sample. International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 67 3.2 Statistical analysis: Twelve experiments were calculated via Central Composite Design (CCD). Table.2 shows the actual factors values and respective values for two responses, it reveals that the recovery and grade values of chromite concentrate distributed in wide range. Table.3 shows the basic statistical analysis of the two responses, grade and recovery. Table 2.Experimental runs for Central Composite Design with factor values in actual form and respective responses Experimental Factor 1 Factor 2 Factor 3 Recovery Grade Run Number A: Feed rate B: water flow rate C: Title angle % Cr2O3 % 1 150.00 17.50 4.00 25.68 45.8 2 150.00 17.50 3.00 67.34 43.94 3 150.00 17.50 2.00 80.9 47.32 4 100.00 20.00 4.00 36.2 47.75 5 200.00 17.50 3.00 74.45 40.76 6 200.00 20.00 2.00 36.47 46.25 7 150.00 17.50 3.00 73.6 45.48 8 100.00 15.00 2.00 50.48 39.81 9 100.00 17.50 3.00 80.72 41.079 10 200.00 15.00 4.00 24.23 47.96 11 150.00 20.00 3.00 48.46 46.051 12 150.00 15.00 3.00 45.61 47.1 Table 3.Statistical Analysis for Responses. Name Unit Type Std.Dev. Low High Feed rate g/min Factor 0 100 200 Water Flow rate l/min Factor 0 15 20 Tilt angle Dgree Factor 0 2 4 Rrecovery of Concentrate % Response 3.13033 24.23 80.9 Grade (Cr2O3) % Response 0.824525 39.81 47.96 Fisher's test (F test) with corresponding (P) values were used to study the effect of different parameters on two responses i.e. grade and recovery in the result analysis via ANOVA analysis model. 3.2.1 ANOVA analysis for concentrate grade. Table 4. Shows the ANOVA analysis for grade of concentrate. It demonstrates the effect of factors with their interactions which are A , B,C,A 2 ,B 2 ,C 2 ,AB,AC, and BC.where the A,B,and C are feed rate (g/min), water flow rate (l/min), and tilt angle respectively. Values of "Prob > F" less than 0.0500 indicate model terms are significant factors.As such, A 2 and AB are significant factors for this model , this indicates that, the grade of concentrate is more sensetive for feed rate (g/min) compered to water flow rate (l/min). International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 68 Table 4. ANOVA analysis for grade of concentrate. Sum of Mean F Source Squares DF Square Value Prob > F Model 89.67 9 9.96 14.65 0.0655 A 0.051 1 0.051 0.075 0.8101 B 0.55 1 0.55 0.81 0.4633 C 1.16 1 1.16 1.70 0.3222 A2 30.06 1 30.06 44.21 0.0219 B2 11.97 1 11.97 17.61 0.0524 C2 11.80 1 11.80 17.36 0.0530 AB 13.42 1 13.42 19.74 0.0471 AC 5.78 1 5.78 8.50 0.1002 BC 4.43 1 4.43 6.51 0.1254 Residual 1.36 2 0.68 Lack of Fit 0.17 1 0.17 0.15 0.7672 Pure Error 1.19 1 1.19 Cor Total 91.02 11 Fig.3. shows the comparison between actual and predicted grade values. It expalins that actual value of grade closed to predicted value of grade The final equation of this modele for grade of concentate is given in Equation(1) based on Coded Factors. Grade (Cr2O3) of concentrate = +44.49-0.16 * A-0.52 * B-0.76* C-3.47* A 2 +2.19* B 2 +2.17* C 2 -3.17* A * B-2.08 * A * C-1.82* B * C Equation(1) Where, A= Feed rate (g/min) B= Water flow rate (l/min) C= Tilt angle Fig.4 shows the 3D response surface plots for effects of different interactions parameters (feed rate, water flow rate, and tilt angle) on grade of concentrate. Fig.4 (a)1 reveals that the increasing of feed rate with decreasing of water flow rate cases decreasing on DESIGN-EXPERT Plot Grade (Cr2O3) X: Actual Y: Predicted Predicted vs. Actual 39.76 41.81 43.86 45.91 47.96 39.76 41.81 43.86 45.91 47.96 Figure 3. Comparison between actual and predicted grade values. International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 69 grade of concentrate. Whereas Fig.4 (a)2 explains that the decreasing of feed rate with increasing of tilt angle cases increasing on grade of concentrate. Fig.4 (a)3 demonstrates that the grade of concentrate increases when the tilt angle decreasing with increasing of water flow rate. 39.3066 41.4455 43.5844 45.7233 47.8622 G ra d e ( C r2 O 3 ) 100.00 125.00 150.00 175.00 200.00 15.00 16.25 17.50 18.75 20.00 A: Feed rate B: Water Flow rate (a) 1 39.3066 41.4455 43.5844 45.7233 47.8622 G ra de ( C r2 O 3) 100.00 125.00 150.00 175.00 200.00 2.00 2.50 3.00 3.50 4.00 A: Feed rate C: Tilt angle (a) 2 39.3066 41.4455 43.5844 45.7233 47.8622 G ra de ( C r2 O 3) 15.00 16.25 17.50 18.75 20.00 2.00 2.50 3.00 3.50 4.00 B: Water Flow rate C: Tilt angle (a) 3 Figure 4. 3D response surface plots for effects of different interactions on grade of concentrate. International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 70 3.2.2 ANOVA analysis for chromite recovery in concentrate: Table 5.shows the ANOVA analysis for the chromite recovery in concentrate, it observes the effect of factors with their interactions which are A , B,C,A 2 ,B 2 ,C 2 ,AB,AC, and BC.where the A,B,and C are Feed rate (g/min), water flow rate (l/min),and tilt angle respectively. Values of "Prob > F" less than 0.0500 indicate model terms are significant factors.Therefor , in this case C, B 2 , C 2 ,and AB are significant model terms , this indicates to, the recovery of concentrate is more sensetive for tilt angle compered to water flow rate (l/min) and feed rate (g/min). Fig.5 shows the actual value of recovery with predicted value of grade, it reveals that the actual value of recovery is quite well to predicted value of recovery. Table 5. ANOVA analysis for the chromite recovery in concentrate. Sum of Mean F Source Squares DF Square Value Prob > F Model 4822.94 9 535.88 54.69 0.0181 A 19.66 1 19.66 2.01 0.2924 B 4.06 1 4.06 0.41 0.5857 C 1524.62 1 1524.62 155.59 0.0064 A2 124.79 1 124.79 12.73 0.0703 B2 1378.86 1 1378.86 140.71 0.0070 C2 742.18 1 742.18 75.74 0.0129 AB 586.88 1 586.88 59.89 0.0163 AC 4.99 1 4.99 0.51 0.5494 BC 15.05 1 15.05 1.54 0.3409 Residual 19.60 2 9.80 Lack of Fit 4.167E-003 1 4.167E-003 2.127E-004 0.9907 Pure Error 19.59 1 19.59 Cor Total 4842.54 11 DESIGN-EXPERT Plot Rrecovery of Concentrate X: Actual Y : Predicted Predicted vs. Actual 24.23 38.40 52.56 66.73 80.90 24.23 38.40 52.56 66.73 80.90 Figure 5.Comparison between actual and predicted recovery values. International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 71 The final equation of this modele for recovery of concentate is given in Equation(2) based on Coded Factors. Rrecovery of Concentrate = +70.50 -3.13* A +1.43* B -27.61* C +7.06* A 2 -23.49* B 2 -17.23* C 2 -20.98*A* B +1.93*A* C +3.36*B *C ....................................... Equation(2) Where, A= Feed rate (g/min) B= Water flow rate (l/min) C= Tilt angle Fig.6 shows the 3D response surface plots for effects of different interactions parameters (feed rate, water flow rate, and tilt angle) on recovery of concentrate.Fig.6 b(1) reveals that the recovery of concentrate increases with decreasing of water flow rate and increasing of feed rate .whereas , the decreasing of tilt angle with increasing of feed rate cases increasing on recovery of concentrate Fig.6 b(2).Fig.6 b(3) explains that the decrasing of water flow rate with decreasing of tilt angle cases increasing on recovery of concentrate. International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 72 3.3 Parameters Optimization: Table 6 and Table 7 show the constraints of parameters and optimized Solutions for optimization the separation process parameters which is considered multi objective by obtaining maximum grade and recovery of concentrate. It reveals that the maximum grade (48.52 Cr2O3, (%)) and recovery (83.09%) with high production for chromite concentrate can be obtained at water flow rate 15.33 l/min, tilt angle 2.16 ≈ 2.00 degree, and feed rate195.38 g/min. Table 6. Constraints for optimization of gravity separation parameters via pilot plant shaking table Name Goal Lower Upper Limit Limit Feed rate is in range 100 200 Water Flow rate is in range 15 20 Tilt angle is in range 2 4 Rrecovery of Concentrate maximize 24.23 80.9 Gade (Cr2O3) maximize 39.81 47.96 Table 7. Optimized Solutions of beneficiation. Number Feed rate g/min Water Flow rate l/min Tilt angle,Degree Rrecovery of Concentrate (%) Grade Cr2O3, (%) 1 114.56 19.49 2.06 83.8335 48.247 2 131.07 18.75 2.00 80.9899 47.9808 3 107.74 19.85 2.07 84.8459 48.6378 4 195.38 15.33 2.16 83.0903 48.5212 5 116.34 19.56 2.07 82.1133 48.5238 6 126.95 19.04 2.07 81.0477 47.9961 7 121.43 19.10 2.01 82.9558 48.0487 8 188.29 15.83 2.01 82.715 48.5688 9 125.78 19.06 2.05 81.3513 48.062 10 163.19 17.22 2.00 80.579 47.6694 4. Conclusion: High grade chromite ore has been decreased constantly due to the importance of chromium element in industrial uses such as metallurgical, chemical, and refractory industries. Therefore, beneficiation of low grade has been more significant (Put the above statements at abstract). The investigated chromite ore is low grade containing 30.21 % Cr2O3. XRD results revealed that the minerals phases of sample were Magnetite and Chromite. Central Composite Design (CCD) of Response Surface Methodology (RSM) was applied for modeling and optimizing the beneficiation process of low-grade chromite ore via pilot plant shaking table. Feed rate, water flow rate, and tilt angle were considered as the operating variables. ANOVA analysis model for recovery and grade reveals that the grade of concentrate is more sensetive for feed rate (g/min) compered to water flow rate (l/min),whereas , the recovery of chromite in concentrate is more sensetive for tilt angle compered to water flow rate (l/min) and feed rate (g/min). Optimized responses for beneficiation process was found to be: 48.52% grade of Cr2O3 in concentrate with 83.09% recovery, achieved at water flow rate 15.33 l/min, tilt angle 2.16 ≈ 2.00 degree, and feed rate 195.38 g/min. Acknowledgement: The authors are thankful to Central Metallurgical Research and Development Institute (CMRDI) in Egypt for valuable support in experimental work and samples analysis. International Journal of Academic Multidisciplinary Research (IJAMR) ISSN: 2643-9670 Vol. 4, Issue 5, May – 2020, Pages: 63-73 www.ijeais.org/ijamr 73 References 1. Jacques Guertin , J.A.J., Cynthia P. Avakian, Chromium(VI) Handbook. Independent Environmental Technical Evaluation Group (IETEG), 2005. 2. Sunil Kumar Tripathy , Y.R.M., Veerendra Singh, Characterisation and separation studies of Indian chromite beneficiation plant tailing. International Journal of Mineral Processing, 2013. 122(0301-7516): p. 47–53. 3. Ahmed A. Seifeinasr , T.T., Abdel-Zaher M. ABOUZEID, GRAVITY CONCENTRATION OF SUDANESE CHROMITE ORE USING LABORATORY SHAKING TABLE. Physicochemical Problems of Mineral Processing, 2012. 48(1643-1049): p. 271-280. 4. Rama Murthy.Y. , S.K.T., C. Raghu Kumar , Chrome ore beneficiation challenges & opportunities – A review. Minerals Engineering, 2011. 24: p. 375–380. 5. Raquel F. Souza , P.R.G.B., João B.A. Paulo Effect of chemical composition on the f-potential of chromite. Minerals Engineering, 2018. 36: p. 65–74. 6. Ranjeet Kumar Singh, S.D., Manoj Kumar Mohanta, and Avimanyu Das, Enhancing the Utilization Potential of a Low Grade Chromite Ore through Extensive Physical Separation. Separation Science and Technology, 2014. 49: p. 937–1945. 7. GENCE, N., Beneciation of Elazg-Kefdag Chromite by Multi Gravity Separator. Tr. J. of Engineering and Environmental Science, 1999. 23: p. 473 475. 8. Aslan.N , H.K., BENEFICIATION OF CHROMITE CONCENTRATION WASTE BY MULTI-GRAVITY SEPARATOR AND HIGH-INTENSITY INDUCED-ROLL MAGNETIC SEPARATOR. The Arabian Journal for Science and Engineering, 2009. 34: p. 285-297. 9. Sunil Kumar Tripathy, Y.R.M., Vilas Tathavadkar andMark Bernad Denys, EFFICACY OF MULTI GRAVITY SEPARATOR FOR CONCENTRATING FERRUGINOUS CHROMITE FINES. Journal of Mining and Metallurgy, 2012. 49: p. 39 49. 10. Özgen, S., Clean Chromite Production from Fine Chromite Tailings by Combination of Multi Gravity Separator and Hydrocyclone. Separation Science and Technology, 2012. 47: p. 1948–1956. 11. Özcan Yıldırım GÜLSOY, E.G., A new method for gravity separation: Vibrating table gravity concentrator. Separation and Purification Technology, 2018(1383-5866). 12. Abubakre.O.K, M.R.A.a.N.P.N., CHARACTERIZATION AND BENEFICIATION OF ANKA CHROMITE ORE USING MAGNETIC SEPARATION PROCESS. Journal of Minerals & Materials Characterization & Engineering, 2007. 6(2): p. 143-150. 13. Sunil Kumar Tripathy, S., Ramamurthy, Improvement in Cr:Fe Ratio of Indian Chromite Ore for Ferro Chrome Production. International Journal of Mining Engineering and Mineral Processing, 2012. 1(3): p. 101-106. 14. Sunil Kumar Tripathy, R.M., Veerendra Singh and Nikkam Suresh, Processing of Ferruginous Chromite Ore by Dry High-Intensity Magnetic Separation. Mineral Processing and Extractive Metallurgy Review, 2016. 37(3): p. 196–210. 15. Baris Beklioglu, A.I.A., SelectiveFlocculation Behavior of Chromite and Serpentine. Physicochemical Problems of Mineral Processing, 2004. 38: p. 103-112. 16. Dwaria.R.K, A.S.I., b, . Tripathyb.S.K, Studies on flocculation characteristics of chromite's ore process tailing:Effect of flocculants ionicity and molecular mass. Colloids and Surfaces 2018: p. 467–477. 17. Murthy, S.K.T.Y.R., Modeling and optimization of spiral concentrator for separation of ultrafine chromite. Powder Technology, 2012: p. 387–394. 18. Aslan.N, Application of response surface methodology and central composite rotatable design for modeling the influence of some operating variables of a Multi-Gravity Separator for coal cleaning. Fuel, 2007. 86: p. 769–776. 19. Sen, G.A., Application of Full Factorial Experimental Design and Response Surface Methodology for Chromite Beneficiation by Knelson Concentrator. Minerals 2016. 6. 20. Lopamudra Panda, P.K.B., S.K. Biswal, R. Venugopal, N.R. Mandre, Modelling and optimization of process parameters for beneficiation of ultrafine chromite particles by selective flocculation. Separation and Purification Technology, 2014. 14. 21. Al-Tigani MMH, M.A., Seifelnasr AA, Mineralogical and Chemical Characterization of Disseminated Low-Grade Sudanese Chromite Ore in Gedarif State at Umm Saqata-Qala Elnahal. J Environ Anal Chem, 2019. 6(3). 22. Al-Tigani MMH, M.A., Seifelnasr AA, Beneficiation of Disseminated Low-Grade Sudanese Chromite Ore in Gedarif State at Umm Saqata-Qala Elnahal. J Environ Anal Chem, 2019. 6(4).