journal article·2022-01

Optimization of Process Parameters of Boron Carbide-Reinforced Al-Zn-Mg-Cu Matrix Composite Produced by Pressure-Assisted Sintering

Ankit Sharma, Barath Tirumuruhan, Guru Sudhan Muthuvel, Amit Kumar Gupta, Ravindran Sujith

Publisher page

Abstract

This study aims to determine the optimum process parameters for the fabrication of B4C-reinforced Al-Zn-Cu-Mg matrix composite by powder metallurgy route. Since casting could lead to problems in dispersion, pressure-assisted sintering was adopted for the fabrication of composites. The influence of various process parameters on the hardness and compressive strength were analyzed by using analysis of variance. Artificial neural network (ANN) and regression analysis were used to predict the hardness and compressive strength. ANN predicted better values than the regression analysis with mean squared error values of 0.27 and 4.72% for the hardness and compressive strength, respectively. Three cross-fold validation was used to check the accuracy of the model. Further, genetic algorithm was used to determine the optimum conditions for attaining maximum hardness and compression strength. The optimum conditions were a compaction pressure of 428 MPa, sintering temperature of 475 °C, sintering time of 75 min, and weight fraction of B4C 45%, giving compressive strength 552.06 MPa and hardness 186.12 HV. The validation experiments conducted on the optimal parameter setting, and the validation results were in good accord with the predicted results. Among all the samples, the 45% weight fraction of the B4C-reinforced sample was fractured during compression testing. Fractographic studies were performed using scanning electron microscopy, and cracking in B4C particles along with debonding in B4C-Al alloy interface was observed.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Aluminum Alloys Composites Properties · Powder Metallurgy Techniques and Materials · Advanced ceramic materials synthesis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (46)

Show source-provided references
1. N. Yumak, Y. Pekbey and K. Aslantaş, Investigation of Deformation Characteristics of CompositeMaterials Used in Armor Design, Electron. J. Mach. Technol., 2013, 10(4), p 1–21.
2. T. Demir, M. Übeyli and R.O. Yıldırım, Investigation on the Ballistic Impact Behavior of Various Alloys against 7.62 Mm Armor Piercing Projectile, Mater. Des., 2008, 29(10), p 2009–2016.10.1016/j.matdes.2008.04.010 ↗
3. P.K. Jena, S.G. Savio, K.S. Kumar, V. Madhu, R.K. Mandal and A.K. Singh, An Experimental Study on the Deformation Behavior of Aluminium Armour Plates Impacted by Two Different Non-Deformable Projectiles, Proc. Eng., 2017, 173, p 222–229.10.1016/j.proeng.2016.12.001 ↗
4. Z.L. Chao, L.T. Jiang, G.Q. Chen, J. Qiao, Z.H. Yu, Y.F. Cao and G.H. Wu, The Microstructure and Ballistic Performance of B4C/AA2024 Functionally Graded Composites with Wide Range B4C Volume Fraction, Compos. Part B Eng., 2019, 161, p 627–638.10.1016/j.compositesb.2018.12.147 ↗
5. N.K. Naik, S. Kumar, D. Ratnaveer, M. Joshi and K. Akella, An Energy-Based Model for Ballistic Impact Analysis of Ceramic-Composite Armors, Int. J. Damage Mech., 2013, 22(2), p 145–187.10.1177/1056789511435346 ↗
6. S. Kumar, K. Akella, M. Joshi, A. Tewari and N.K. Naik, Performance of Ceramic-Composite Armors under Ballistic Impact Loading, J. Mater. Eng. Perform., 2020, 29(9), p 5625–5637.10.1007/s11665-020-05041-z ↗
7. M. Übeyli, E. Balci, B. Sarikan, M.K. Öztaş, N. Camuşcu, R.O. Yildirim and Ö. Keleş, The Ballistic Performance of SiC-AA7075 Functionally Graded Composite Produced by Powder Metallurgy, Mater. Des., 2014, 56, p 31–36.10.1016/j.matdes.2013.10.092 ↗
8. N. Gupta, V.V. Prasad, V. Madhu and B. Basu, Ballistic Studies on TiB 2-Ti Functionally Graded Armor Ceramics, Defence Sci. J., 2012, 62(6), p 382.10.14429/dsj.62.2666 ↗
9. C.-Y. Huang and Y.-L. Chen, Effect of Mechanical Properties on the Ballistic Resistance Capability of Al2O3-ZrO2 Functionally Graded Materials, Ceram. Int., 2016, 42(11), p 12946–12955.10.1016/j.ceramint.2016.05.067 ↗
10. V. Domnich, S. Reynaud, R.A. Haber and M. Chhowalla, Boron Carbide: Structure, Properties, and Stability under Stress, J. Am. Ceram. Soc., 2011, 94(11), p 3605–3628.10.1111/j.1551-2916.2011.04865.x ↗
11. A.K. Suri, C. Subramanian, J.K. Sonber and T.C. Murthy, Synthesis and Consolidation of Boron Carbide: A Review, Int. Mater. Rev., 2010, 55(1), p 4–40.10.1179/095066009X12506721665211 ↗
12. A. Baradeswaran and A.E. Perumal, Influence of B4C on the Tribological and Mechanical Properties of Al 7075-B4C Composites, Compos. Part B Eng., 2013, 54, p 146–152.10.1016/j.compositesb.2013.05.012 ↗
13. A. Mazahery and M.O. Shabani, Mechanical Properties of Squeeze-Cast A356 Composites Reinforced with B 4 C Particulates, J. Mater. Eng. Perform., 2012, 21(2), p 247–252.10.1007/s11665-011-9867-6 ↗
14. Y. Xian, X. Pang, S. He, W. Wang, X. Wang and P. Zhang, Microstructure and Mechanical Properties of Al6061-31vol.% B 4 C Composites Prepared by Hot Isostatic Pressing, J. Mater. Eng. Perform., 2015, 24(10), p 4044–4053.10.1007/s11665-015-1675-y ↗
15. M. Imran and A.A. Khan, Characterization of Al-7075 Metal Matrix Composites: A Review, J. Mater. Res. Technol., 2019, 8(3), p 3347–3356.10.1016/j.jmrt.2017.10.012 ↗
16. A. Sharma, A. Priyadarshini, R. Sujith, M.S. Subrahmanyam, P.A. Thomas, and A.K. Gupta, “Effect of Graphene Nanoplatelets Incorporation on Microstructural and Tribological Properties of Aluminium Metal Matrix Composites,” ASME International Mechanical Engineering Congress and Exposition, American Society of Mechanical Engineers, 2019, p V012T10A021.10.1115/IMECE2019-10939 ↗
17. P. Garg, A. Jamwal, D. Kumar, K.K. Sadasivuni, C.M. Hussain and P. Gupta, Advance Research Progresses in Aluminium Matrix Composites: Manufacturing & Applications, J. Mater. Res. Technol., 2019, 8(5), p 4924–4939.10.1016/j.jmrt.2019.06.028 ↗
18. H. Karakoç, Ş Karabulut and R. Çıtak, Study on Mechanical and Ballistic Performances of Boron Carbide Reinforced Al 6061 Aluminum Alloy Produced by Powder Metallurgy, Compos. Part B Eng., 2018, 148, p 68–80.10.1016/j.compositesb.2018.04.043 ↗
19. G. Kırmızı, H. Arık and H. Çinici, Experimental Study on Mechanical and Ballistic Behaviours of Silicon Carbide Reinforced Functionally Graded Aluminum Foam Composites, Compos. Part B Eng., 2019, 164, p 345–357.10.1016/j.compositesb.2018.11.076 ↗
20. G.A. Sweet, M. Brochu, R.L. Hexemer Jr., I.W. Donaldson and D.P. Bishop, Consolidation of Aluminum-Based Metal Matrix Composites via Spark Plasma Sintering, Mater. Sci. Eng. A, 2015, 648, p 123–133.10.1016/j.msea.2015.09.027 ↗
21. E. Ghasali, M. Alizadeh, M. Niazmand and T. Ebadzadeh, Fabrication of Magnesium-Boron Carbide Metal Matrix Composite by Powder Metallurgy Route: Comparison between Microwave and Spark Plasma Sintering, J. Alloys Compnd., 2017, 697, p 200–207.10.1016/j.jallcom.2016.12.146 ↗
22. Ş Karabulut, Optimization of Surface Roughness and Cutting Force during AA7039/Al2O3 Metal Matrix Composites Milling Using Neural Networks and Taguchi Method, Measurement, 2015, 66, p 139–149.10.1016/j.measurement.2015.01.027 ↗
23. T. Varol, A. Canakci and S. Ozsahin, Artificial Neural Network Modeling to Effect of Reinforcement Properties on the Physical and Mechanical Properties of Al2024-B4C Composites Produced by Powder Metallurgy, Compos. Part B Eng., 2013, 54, p 224–233.10.1016/j.compositesb.2013.05.015 ↗
24. M. Amirjan, H. Khorsand, M.H. Siadati and R.E. Farsani, Artificial Neural Network Prediction of Cu-Al2O3 Composite Properties Prepared by Powder Metallurgy Method, J. Mater. Res. Technol., 2013, 2(4), p 351–355.10.1016/j.jmrt.2013.08.001 ↗
25. S.A.A. Daniel, R. Pugazhenthi, R. Kumar and S. Vijayananth, Multi Objective Prediction and Optimization of Control Parameters in the Milling of Aluminium Hybrid Metal Matrix Composites Using ANN and Taguchi -Grey Relational Analysis, Defence Technol., 2019, 15, p 545–556.10.1016/j.dt.2019.01.001 ↗
26. A.K. Gupta, Predictive Modelling of Turning Operations Using Response Surface Methodology, Artif. Neural Netw. Support Vector Regress. Int. J. Prod. Res., 2010, 48(3), p 763–778.
27. R. Esmaeili and M.R. Dashtbayazi, Modeling and Optimization for Microstructural Properties of Al/SiC Nanocomposite by Artificial Neural Network and Genetic Algorithm, Expert Syst. Appl., 2014, 41(13), p 5817–5831.10.1016/j.eswa.2014.03.038 ↗
28. T. Banerjee, S. Dey, A.P. Sekhar, S. Datta and D. Das, Design of Alumina Reinforced Aluminium Alloy Composites with Improved Tribo-Mechanical Properties: A Machine Learning Approach, Trans. Indian Inst. Metals, 2020, 73(12), p 3059–3069.10.1007/s12666-020-02108-2 ↗
29. R.M. German, Chapter Ten -Sintering With External Pressure, Sintering: from Empirical Observations to Scientific Principles. R.M. German Ed., Butterworth-Heinemann, Boston, 2014
30. N. Kumar, M.K. Manoj and R. Haldar, Effect of Re-Aging on Strength, Corrosion and Dry Sliding Wear Behavior of 7075 Aluminum Alloy, J. Mater. Sci. Nanotechnol., 2016, 4(2), p 202.
31. Z. Liu, X. Deng, J. Li, Y. Sun and S. Ran, Effects of B4C Particle Size on the Microstructures and Mechanical Properties of Hot-Pressed B4C-TiB2 Composites, Ceram. Int., 2018, 44(17), p 21415–21420.10.1016/j.ceramint.2018.08.200 ↗
32. Ş Karabulut, U. Gökmen and H. Çinici, Optimization of Machining Conditions for Surface Quality in Milling AA7039-Based Metal Matrix Composites, Arab. J. Sci. Eng., 2018, 43(3), p 1071–1082.10.1007/s13369-017-2691-z ↗
33. Stephanie, “Box Cox Transformation,” Statistics How To, 2015, https://www.statisticshowto.com/box-cox-transformation/. Accessed 28 July 2020.
34. M.H. Hassoun, Fundamentals of Artificial Neural Networks, MIT press, 1995.
35. A.K. Gupta, S.K. Singh, S. Reddy and G. Hariharan, Prediction of Flow Stress in Dynamic Strain Aging Regime of Austenitic Stainless Steel 316 Using Artificial Neural Network, Mater. Des., 2012, 35, p 589–595.10.1016/j.matdes.2011.09.060 ↗
36. H. Okut, Bayesian Regularized Neural Networks for Small n Big p Data, Artificial neural networks-models and applications, IntechOpen, 2016.10.5772/63256 ↗
37. D.E. Goldberg and J.H. Holland, Genetic Algorithms and Machine Learning, Kluwer Academic Publishers-Plenum Publishers, Kluwer Academic Publishers, 1988.
38. N.N. Aung, W. Zhou, C.S. Goh, S.M.L. Nai and J. Wei, Effect of Carbon Nanotubes on Corrosion of Mg-CNT Composites, Corros. Sci., 2010, 52(5), p 1551–1553.10.1016/j.corsci.2010.02.025 ↗
39. M.P. Reddy, F. Ubaid, R.A. Shakoor, G. Parande, V. Manakari, A.M.A. Mohamed and M. Gupta, Effect of Reinforcement Concentration on the Properties of Hot Extruded Al-Al2O3 Composites Synthesized through Microwave Sintering Process, Mater. Sci. Eng. A, 2017, 696, p 60–69.10.1016/j.msea.2017.04.064 ↗
40. Y. Zhang, G. Sun, G. Li, Z. Luo and Q. Li, Optimization of Foam-Filled Bitubal Structures for Crashworthiness Criteria, Mater. Des., 2012, 38, p 99–109.10.1016/j.matdes.2012.01.028 ↗
41. H. Lee, J.H. Choi, M.C. Jo, D. Lee, S. Shin, I. Jo, S.-K. Lee and S. Lee, Effects of SiC Particulate Size on Dynamic Compressive Properties in 7075-T6 Al-SiCp Composites, Mater. Sci. Eng. A, 2018, 738, p 412–419.10.1016/j.msea.2018.09.082 ↗
42. S. Liu, Y. Wang, T. Muthuramalingam and G. Anbuchezhiyan, Effect of B4C and MOS2 Reinforcement on Micro Structure and Wear Properties of Aluminum Hybrid Composite for Automotive Applications, Compos. Part B Eng., 2019, 176, p 107329.10.1016/j.compositesb.2019.107329 ↗
43. M.Z. Hussain, S. Khan and P. Sarmah, Optimization of Powder Metallurgy Processing Parameters of Al2O3/Cu Composite through Taguchi Method with Grey Relational Analysis, J. King Saud Univ. Eng. Sci., 2020, 32(4), p 274–286.
44. D. Srinivasan, M. Meignanamoorthy and M. Ravichandran, Optimization of Process Parameters of Boron Carbide Filled Aluminium Matrix Composites Using Grey Taguchi Method, Materials Research Express, IOP Pub., 2019, 6(7), p 076504.
45. J. Abenojar, P. Díaz, M.A. Martinez and F. Velasco, Influence of Forming on the Mechanical Properties of the Al+ 50% B4C System, Trans Tech Publ, Materials Science Forum, 2006, p 304–309
46. Ş Karabulut, H. Karakoç and R. Çıtak, Influence of B4C Particle Reinforcement on Mechanical and Machining Properties of Al6061/B4C Composites, Compos. Part B Eng., 2016, 101, p 87–98.10.1016/j.compositesb.2016.07.006 ↗