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International Journal on Interactive Design and Manufacturing (IJIDeM)

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21.08.2023 | Original Paper

Effect of different reinforcements in wire electric discharge machining of various geometrical profiles in metal matrix composites

verfasst von: Dhirendra Pratap Singh, Sanjay Mishra

Erschienen in: International Journal on Interactive Design and Manufacturing (IJIDeM) | Ausgabe 1/2024

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Abstract

In this study three different geometrical profiles with same perimeter were fabricated in aluminum metal matrix composite (AMMCs) using wire electric discharge machining (WEDM). AMMCs containing Al6061 as matrix and 10% alumina (Al₂O₃), 10% silicon carbide (SiC) and mixture of 5% Al₂O₃ and 5% SiC as reinforcements were fabricated by stir casting method. The basic objective of this study is to develop response surface methodology (RSM) based second order regression model to analyze the effect of various input parameters on cutting velocity (CV) and surface roughness (SR) during WEDM of triangular, circular, and square profiles of same perimeter. Effect of pulse-on time (T_on = 30–50 µs), pulse-off time (T_off = 6–12 µs), current (I = 1–5 A) and geometrical profiles on CV and SR have been investigated using response surface plots. Parametric analysis reveals that increase of current from 1 to 5 A at T_on = 40 µs, T_off = 12 µs increases the CV by 115% in all the three composites. Similarly, increase of T_off from 6 to 12 µs at T_on = 40 µs and I = 1 A reduces the SR by more than 35% in all composites. Multiobjective optimization using composite desirability (CD) approach shows that optimal results are obtained for triangular profiles and at optimal input parameters SR reduces by 21%, 24.19% and 33.39% respectively for alumina, silicon carbide and hybrid composite. Energy dispersive spectroscopy (EDS) analysis and SEM analysis were carried out to investigate the variation in elemental composition and surface morphology of machined surfaces respectively.

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Surappa, M.K.: Aluminium matrix composites: challenges and opportunities. Sadhana 28(1), 319–334 (2003). https://doi.org/10.1007/BF02717141CrossRef

Zolotova, D., Serpova, V., Prokofiev, M., Rabinskiy, L., Shavnev, A.: A study of the composition and microstructure of aluminum matrix composites reinforced with alumina fibers. IOP Conf. Ser. Mater. Sci. Eng. 124(1), 012135 (2016). https://doi.org/10.1088/1757-899X/124/1/012135CrossRef

Miracle, D.B.: Metal matrix composites–from science to technological significance. Compos. Sci. Technol. 65(15–16), 2526–2540 (2005). https://doi.org/10.1016/j.compscitech.2005.05.027CrossRef

Ahmad, Z.: Mechanical behavior and fabrication characteristics of aluminum metal matrix composite alloys. J. Reinf. Plast. Compos. 20(11), 921–944 (2001). https://doi.org/10.1177/073168401772678896CrossRef

Teng, X., Huo, D.: Conventional machining of metal matrix composites. In: Advances in machining of composite materials: conventional and non-conventional processes, pp. 159–181. Springer, Cham (2021)CrossRef

Darji, Y., Patel, D., Patel, D., Ramesh, R., Oza, A.D., Bhole, K.S., Shinde, S.M., Kumar, M.: Experimentation with the EDM parameter through a full factorial technique and optimization using regression analysis with carbon nanotubes. Int. J. Interact. Des. Manuf. (IJIDeM) (2023). https://doi.org/10.1007/s12008-023-01263-2CrossRef

Goyal, K.K., Sharma, N., Dev Gupta, R., Singh, G., Rani, D., Banga, H.K., Giasin, K.: A soft computing-based analysis of cutting rate and recast layer thickness for AZ31 alloy on WEDM using RSM-MOPSO. Materials 15(2), 635 (2022). https://doi.org/10.3390/ma15020635CrossRef

Bagal, D.K., Barua, A., Jeet, S., Satapathy, P., Patnaik, D.: MCDM optimization of parameters for wire-EDM machined stainless steel using hybrid RSM-TOPSIS, genetic algorithm and simulated annealing. Int. J. Eng. Adv. Technol. 9(1), 366–371 (2019). https://doi.org/10.35940/ijeat.A9349.109119CrossRef

Naidu, B.V.V., Varaprasad, K.C., Rao, K.P.: Development of regression models for wire electrical discharge machining of aluminium metal matrix composites. Mater. Today Proc. 39(1), 236–239 (2021). https://doi.org/10.1016/j.matpr.2020.06.586CrossRef

10.

Abhilash, P.M., Chakradhar, D.: Multi-response optimization of wire EDM of Inconel 718 using a hybrid entropy weighted GRA-TOPSIS method. Process Integr. Optim. Sustain. 6(1), 61–72 (2022). https://doi.org/10.1007/s41660-021-00202-6CrossRef

11.

Magesh, M., Jyothiraj, K., Janarthanan, G., Keerthivasan, C., Sivaraman, P.: Optimization of wire-EDM parameters to calculate MRR and measure surface finish on SS410. Int. J. Innov. Sci. Res. Technol. 2(3), 2456–2165 (2017)

12.

Sadhasivam, R.M., Ramanathan, K.: Investigating the parametric effects and analysis of stir cast aluminium matrix composite by Wirecut-EDM using Topsis method. Sadhana 46(3), 1–10 (2021). https://doi.org/10.1007/s12046-021-01674-5CrossRef

13.

Kumar, A., Grover, N., Manna, A., Chohan, J.S., Kumar, R., Singh, S., Pruncu, C.I.: Investigating the influence of WEDM process parameters in machining of hybrid aluminum composites. Adv. Compos. Lett. (2020). https://doi.org/10.1177/2633366X20963137CrossRef

14.

Paul, R.C., Joseph, R., Nadana Kumar, V., Booma Devi, P., Manigandan, S.: Experimental analysis of hybrid metal matrix composite reinforced with Al₂O₃ and graphite. Int. J. Amb. Energy 43(1), 648–652 (2022). https://doi.org/10.1080/01430750.2019.1653984CrossRef

15.

Sivananthan, S., Ravi, K., Samuel, C.S.: Effect of SiC particles reinforcement on mechanical properties of aluminium 6061 alloy processed using stir casting route. Mater. Today Proc. 21, 968–970 (2020). https://doi.org/10.1016/j.matpr.2019.09.068CrossRef

16.

Sivananthan, S., Reddy, V.R., Samuel, C.S.: Preparation and evaluation of mechanical properties of 6061Al-Al₂O₃ metal matrix composites by stir casting process. Mater. Today Proc. 21, 713–716 (2020). https://doi.org/10.1016/j.matpr.2019.06.744CrossRef

17.

Kumar, A., Grover, N., Manna, A., Kumar, R., Chohan, J.S., Singh, S., Pruncu, C.I.: Multi-objective optimization of WEDM of aluminum hybrid composites using AHP and genetic algorithm. Arab. J. Sci. Eng. 47(7), 8031–8043 (2022). https://doi.org/10.1007/s13369-021-05865-4CrossRef

18.

Lal, S., Kumar, S., Khan, Z.A., Siddiquee, A.N.: Multi-response optimization of wire electrical discharge machining process parameters for Al7075/Al₂O₃/SiC hybrid composite using Taguchi-based grey relational analysis. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 229(2), 229–237 (2015). https://doi.org/10.1177/0954405414526382CrossRef

19.

Raju, K., Balakrishnan, M., Priya, C.B., Sivachitra, M., Narasimha Rao, D.: Parametric optimization of wire electrical discharge machining in AA7075 metal matrix composite. Adv. Mater. Sci. Eng. (2022). https://doi.org/10.1155/2022/4438419CrossRef

20.

Tapadar, J., Thakur, R., Chetia, P., Tamang, S.K., Samanta, S.: Modeling of WEDM parameters while machining Mg-SiC metal matrix composite. Mech. Eng. (2017). https://doi.org/10.14716/ijtech.v8i5.870CrossRef

21.

Singh, H., Garg, R.: Effects of process parameters on material removal rate in WEDM. J. Achiev. Mater. Manuf. Eng. 32(1), 70–74 (2009)

22.

Khanna, R., Sharma, N., Kumar, N., Gupta, R.D., Sharma, A.: WEDM of Al/SiC/Ti composite: a hybrid approach of RSM-ARAS-TLBO algorithm. Int. J. Lightw. Mater. Manuf. 5(3), 315–325 (2022). https://doi.org/10.1016/j.ijlmm.2022.04.003CrossRef

23.

Beck, R.J., Aspinwall, D.K., Soo, S.L., Williams, P., Perez, R.: Fatigue performance of surface ground and wire electrical discharge machined TiNi shape memory alloy. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 236(4), 355–362 (2022). https://doi.org/10.1177/09544054211028844CrossRef

24.

Pramanik, A., Islam, M.N., Boswell, B., Basak, A.K., Dong, Y., Littlefair, G.: Accuracy and finish during wire electric discharge machining of metal matrix composites for different reinforcement size and machining conditions. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 232(6), 1068–1078 (2018). https://doi.org/10.1177/0954405416662079CrossRef

25.

Straka, L., Corny, I.: Adjustment of wire vibrations in order to improve geometric accuracy and surface roughness at WEDM. Appl. Sci. 11(11), 4734 (2021). https://doi.org/10.3390/app11114734CrossRef

26.

Sadeghi, M., Razavi, H., Esmaeilzadeh, A., Kolahan, F.: Optimization of cutting conditions in WEDM process using regression modelling and Tabu-search algorithm. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 225(10), 1825–1834 (2011). https://doi.org/10.1177/0954405411406639CrossRef

27.

Singh, D.P., Mishra, S., Yadav, S.K.S., Porwal, R.K., Singh, V.: Comparative analysis and optimization of thermoelectric machining of alumina and silicon carbide-reinforced aluminum metal matrix composites using different electrodes. J. Adv. Manuf. Syst. (2022). https://doi.org/10.1142/S0219686723500191CrossRef

28.

Joy, R., Manoj, I.V., Narendranath, S.: Investigation of cutting speed, recast layer and micro-hardness in angular machining using slant type taper fixture by WEDM of Hastelloy X. Mater. Today Proc. 27, 1943–1946 (2020). https://doi.org/10.1016/j.matpr.2019.09.021CrossRef

29.

Nayak, B.B., Mahapatra, S.S.: A utility concept approach for multi-objective optimization of taper cutting operation using WEDM. Procedia Eng. 97, 469–478 (2014). https://doi.org/10.1016/j.proeng.2014.12.271CrossRef

30.

Manoj, I.V., Narendranath, S.: Effect of profile geometry and cutting speed override parameter on profiling speed during tapering using wire electric discharge machining. In: Sustainable machining strategies for better performance, pp. 111–122. Springer (2022)CrossRef

31.

Manoj, I.V., Soni, H., Narendranath, S., Mashinini, P.M., Kara, F.: Examination of machining parameters and prediction of cutting velocity and surface roughness using RSM and ANN using WEDM of Altemp HX. Adv. Mater. Sci. Eng. (2022). https://doi.org/10.1155/2022/5192981CrossRef

32.

Selvakumar, G., BravilinJiju, K., Sarkar, S., Mitra, S.: Enhancing die corner accuracy through trim cut in WEDM. Int. J. Adv. Manuf. Technol. 83(5), 791–803 (2016). https://doi.org/10.1007/s00170-015-7606-0CrossRef

33.

Devarajaiah, D., Muthumari, C.: Evaluation of power consumption and MRR in WEDM of Ti–6Al–4V alloy and its simultaneous optimization for sustainable production. J. Braz. Soc. Mech. Sci. Eng. 40(8), 1–18 (2018). https://doi.org/10.1007/s40430-018-1318-yCrossRef

34.

Ilani, M.A., Khoshnevisan, M.: Powder mixed-electrical discharge machining (EDM) with the electrode is made by fused deposition modeling (FDM) at Ti-6Al-4V machining procedure. Multisc. Multidiscip. Model. Exp. Des. 3, 173–186 (2020). https://doi.org/10.1007/s41939-020-00070-6CrossRef

35.

Ilani, M.A., Khoshnevisan, M.: Mathematical and physical modeling of FE-SEM surface quality surrounded by the plasma channel within Al powder-mixed electrical discharge machining of Ti-6Al-4V. Int. J. Adv. Manuf. Technol. 112, 3263–3277 (2021). https://doi.org/10.1007/s00170-021-06626-1CrossRef

36.

Taherkhani, A., Ilani, M.A., Ebrahimi, F., Huu, P.N., Long, B.T., Van Dong, P., Tam, N.C., Minh, N.D., Van Duc, N.: Investigation of surface quality in cost of goods manufactured (COGM) method of μ-Al₂O₃ powder-mixed-EDM process on machining of Ti–6Al–4V. Int. J. Adv. Manuf. Technol. 116(5–6), 1783–1799 (2021). https://doi.org/10.1007/s00170-021-07573-7CrossRef

37.

Ilani, M.A., Khoshnevisan, M.: Study of surfactant effects on intermolecular forces (IMF) in powder-mixed electrical discharge machining (EDM) of Ti–6Al–4V. Int. J. Adv. Manuf. Technol. 116(5–6), 1763–1782 (2021). https://doi.org/10.1007/s00170-021-07569-3CrossRef

38.

Ilani, M.A., Khoshnevisan, M.: An evaluation of the surface integrity and corrosion behavior of Ti–6Al–4 V processed thermodynamically by PM-EDM criteria. Int. J. Adv. Manuf. Technol. 120(7–8), 5117–5129 (2022). https://doi.org/10.1007/s00170-022-09093-4CrossRef

39.

Phan, N.H., Pi, V.N., Tuan, N.Q., Shirguppikar, S., Patil, M.S., Ilani, M.A., Hung, L.X., Muthuramalingam, T., Hung, T.Q.: Tool wear rate analysis of uncoated and AlCrNi coated aluminum electrode in EDM for Ti-6Al-4 V titanium alloy. In: Advances in Engineering Research and Application Proceedings of the International Conference on Engineering Research and Applications, pp 832–838. Springer: Heidelberg (2021)

40.

Phan, N.H., Pi, V.N., Shirguppikar, S., Patil, M.S., Ilani, M.A., Hung, L.X., Muthuramalingam, T., Hung, T.Q.: Material removal rate in electric discharge machining with aluminum tool electrode for Ti-6Al-4V titanium alloy. In: Advances in Engineering Research and Application: Proceedings of the International Conference on Engineering Research and Applications, pp 527–533. Springer: Heidelberg (2021)

41.

Mahdavinejad, R.A., Ilani, M.A.: Superior advance research in the electro-discharge machining of Ti alloys. Int. J. Sci. Res. Mech. Mater. Eng. 3, 19–38 (2019)

42.

Boopathi, S.: An investigation on gas emission concentration and relative emission rate of the near-dry wire-cut electrical discharge machining process. Environ. Sci. Pollut. Res. 29(57), 86237–86246 (2022). https://doi.org/10.1007/s11356-021-17658-1CrossRef

43.

Gowri, N.V., Dwivedi, J.N., Krishnaveni, K., Boopathi, S., Palaniappan, M., Medikondu, N.R.: Experimental investigation and multi-objective optimization of eco-friendly near-dry electrical discharge machining of shape memory alloy using Cu/SiC/Gr composite electrode. Environ. Sci. Pollut. Res. 2023, 1–19 (2023). https://doi.org/10.1007/s11356-023-26983-6CrossRef

44.

Boopathi, S., Alqahtani, A.S., Mubarakali, A., Panchatcharam, P.: Sustainable developments in near-dry electrical discharge machining process using sunflower oil-mist dielectric fluid. Environ. Sci. Pollut. Res. 2023, 1–20 (2023). https://doi.org/10.1007/s11356-023-27494-0CrossRef

45.

Xie, W., Guo, C., Wang, X. and Zhang, J.: Experimental comparative study on Near-dry wire-cut electrical discharge machining process using moistened wire. (2023). https://doi.org/10.21203/rs.3.rs-2612583/v1

46.

Kuo, C.G., Hsu, C.Y., Chen, J.H., Lee, P.W.: Discharge current effect on machining characteristics and mechanical properties of aluminum alloy 6061 workpiece produced by electric discharging machining process. Adv. Mech. Eng. 9(11), 1687814017730756 (2017). https://doi.org/10.1177/1687814017730756CrossRef

47.

Montgomery, D.C., Myers, R.H.: Process and product optimization using designed experiments. Wiley, New York (2002)

48.

Box, G.E., Hunter, J.S., Hunter, W.G.: Statistics for experimenters. Wiley series in probability and statistics. Wiley, New York (2005)

49.

Montgomery, D.C.: Design and analysis of experiments. Wiley, New York (2006)

50.

Heinze, G., Dunkler, D.: Five myths about variable selection. Transpl. Int. 30, 6–10 (2017). https://doi.org/10.1111/tri.12895CrossRef

51.

Mishra, Y.K., Mishra, S., Jaiswal, S.C.: Comparative analysis of grey relational analysis integrated with the principal component analysis and analytic hierarchy process for multi-objective optimization of inclined laser percussion drilling in carbon fiber reinforced composites. J. Adv. Manuf. Syst. 21(1), 1–23 (2022). https://doi.org/10.1142/S0219686721500475CrossRef

52.

Mishra, Y.K., Mishra, S., Jaiswal, S.C.: Parametric analysis and optimization of inclined laser percussion drilling of carbon fiber reinforced plastic using solid state Nd: YAG laser. Lasers Manuf. Mater. Process. 8, 325–354 (2021). https://doi.org/10.1007/s40516-021-00151-5CrossRef

53.

Singh, D.P., Mishra, S., Porwal, R.K.: Parametric analysis through ANFIS modelling and optimization of micro-hole machining in super duplex stainless steel by die-sinking EDM. Adv. Mater. Process. Technol. (2022). https://doi.org/10.1080/2374068X.2022.2135733CrossRef

54.

Ezeddini, S., Boujelbene, M., Bayraktar, E., Ben Salem, S.: Optimization of the surface roughness parameters of Ti–Al intermetallic based composite machined by wire electrical discharge machining. Coatings 10(9), 900 (2020). https://doi.org/10.3390/coatings10090900CrossRef

Titel: Effect of different reinforcements in wire electric discharge machining of various geometrical profiles in metal matrix composites
verfasst von: Dhirendra Pratap Singh
Sanjay Mishra
Publikationsdatum: 21.08.2023
Verlag: Springer Paris
Erschienen in: International Journal on Interactive Design and Manufacturing (IJIDeM) / Ausgabe 1/2024
Print ISSN: 1955-2513
Elektronische ISSN: 1955-2505
DOI: https://doi.org/10.1007/s12008-023-01477-4

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