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Multi-response Optimization in Machining Inconel-625 by Abrasive Water Jet Machining Process Using WASPAS and MOORA

  • Research Article-Mechanical Engineering
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Abstract

Certain materials that are used in industries to manufacture parts, components and sub-assemblies are difficult to machine using traditional machining processes. Abrasive water jet machining is a viable solution to such a problem, and its use is sought where precision is the requirement. The process involves many input controllable parameters that influence the performance characteristics of the process such as MRR, surface finish and kerf width. Inconel-625 is one such hard-to-machine material that finds many applications in industries. The objective of the present work is set to ascertain experimentally the influence of three input parameters on the three responses mentioned above through ANOVA. WASPAS and MOORA are two powerful techniques that are used for multi-objective optimization, and the ranks of both the MCDM methods were observed to be same. Traverse speed and abrasive mass flow rate are proven to be statistically significant on MRR and surface finish, whereas standoff distance along with the above two parameters is also significant on the response kerf width. Machined surface morphology is studied using scanning electron microscopy. From the SEM morphology, it was confirmed that the higher abrasive flow rate obtained rough surface finish.

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References

  1. Veerappan, G., Ravichandran, M.: Experimental investigations on abrasive water jet machining of nickel-based superalloy. J. Braz. Soc. Mech. Sci. Eng. 41(11), 528 (2019)

    Article  Google Scholar 

  2. Dumbhare, P.A., Dubey, S., Deshpande, Y.V., Andhare, A.B., Barve, P.S.: Modelling and multi-objective optimization of surface roughness and kerf taper angle in abrasive water jet machining of steel. J. Braz. Soc. Mech. Sci. Eng. 40(5), 259 (2018)

    Article  Google Scholar 

  3. Liu, X.; Yu, T.; Wang, W.: Prediction of the cutting depth of abrasive suspension jet using a BP artificial neural network. In: International Conference on Programming Languages for Manufacturing, pp. 563–569. Springer, Boston (2006)

  4. Anwar, S., Abdullah, F.M., Alkahtani, M.S., Ahmad, S., Alatefi, M.: Bibliometric analysis of abrasive water jet machining research. J. King Saud Univ. Eng. Sci. 31(3), 262–270 (2019)

    Google Scholar 

  5. Çaydaş, U., Hascalık, A.: A study on surface roughness in abrasive waterjet machining process using artificial neural networks and regression analysis method. J. Mater. Process. Technol. 202(1–3), 574–582 (2008)

    Article  Google Scholar 

  6. Zain, A.M., Haron, H., Sharif, S.: Estimation of the minimum machining performance in the abrasive waterjet machining using integrated ANN-SA. Expert Syst. Appl. 38(7), 8316–8326 (2011)

    Article  Google Scholar 

  7. Jianming, W., Na, G., Wenjun, G.: Abrasive waterjet machining simulation by SPH method. Int. J. Adv. Manuf. Technol. 50(1–4), 227–234 (2010)

    Article  Google Scholar 

  8. Bhandarkar, V.V.; Jibhakate, R.A.; Gupta, T.V.K.: Influence of process parameters on abrasive water jet machined pockets on Inconel 718 alloy. In: Smart Technologies for Energy, Environment and Sustainable Development, pp. 619–624. Springer, Singapore (2019)

  9. Holmberg, J., Berglund, J., Wretland, A., Beno, T.: Evaluation of surface integrity after high energy machining with EDM, laser beam machining and abrasive water jet machining of alloy 718. Int. J. Adv. Manuf. Technol. 100(5–8), 1575–1591 (2019)

    Article  Google Scholar 

  10. Kumar, A., Singh, H., Kumar, V.: Study the parametric effect of abrasive water jet machining on surface roughness of Inconel 718 using RSM-BBD techniques. Mater. Manuf. Process. 33(13), 1483–1490 (2018)

    Article  Google Scholar 

  11. Uthayakumar, M., Khan, M.A., Kumaran, S.T., Slota, A., Zajac, J.: Machinability of nickel-based superalloy by abrasive water jet machining. Mater. Manuf. Process. 31(13), 1733–1739 (2016)

    Article  Google Scholar 

  12. Dhanabalan, S., Sivakumar, K., Sathiya Narayanan, C.: Analysis of form tolerances in electrical discharge machining process for Inconel 718 and 625. Mater. Manuf. Process. 29(3), 253–259 (2014)

    Article  Google Scholar 

  13. Parida, A.K., Maity, K.: Comparison the machinability of Inconel 718, Inconel 625 and Monel 400 in hot turning operation. Eng. Sci. Technol. Int. J. 21(3), 364–370 (2018)

    Google Scholar 

  14. Abhishek, K., Datta, S., Biswal, B.B., Mahapatra, S.S.: Machining performance optimization for electro-discharge machining of Inconel 601, 625, 718 and 825: an integrated optimization route combining satisfaction function, fuzzy inference system and Taguchi approach. J. Braz. Soc. Mech. Sci. Eng. 39(9), 3499–3527 (2017)

    Article  Google Scholar 

  15. Aruna, M., Dhanalakshmi, V.: Optimisation of turning parameters of Inconel 718 alloy using RSM. Int. J. Manuf. Technol. Manag. 25(1–3), 113–134 (2012)

    Article  Google Scholar 

  16. Datta, S., Biswal, B.B., Mahapatra, S.S.: A novel satisfaction function and distance-based approach for machining performance optimization during electro-discharge machining on super alloy Inconel 718. Arab. J. Sci. Eng. 42(5), 1999–2020 (2017)

    Article  Google Scholar 

  17. Chen, F.L., Siores, E.: The effect of cutting jet variation on surface striation formation in abrasive water jet cutting. J. Mater. Process. Technol. 135(1), 1–5 (2003)

    Article  Google Scholar 

  18. Hlaváč, L.M., Gembalová, L., Štěpán, P., Hlaváčová, I.M.: Improvement of abrasive water jet machining accuracy for titanium and TiNb alloy. Int. J. Adv. Manuf. Technol. 80(9–12), 1733–1740 (2015)

    Article  Google Scholar 

  19. Khan, A.A., Haque, M.M.: Performance of different abrasive materials during abrasive water jet machining of glass. J. Mater. Process. Technol. 191(1–3), 404–407 (2007)

    Article  Google Scholar 

  20. Zain, A.M., Haron, H., Sharif, S.: Optimization of process parameters in the abrasive waterjet machining using integrated SA–GA. Appl. Soft Comput. 11(8), 5350–5359 (2011)

    Article  Google Scholar 

  21. Kechagias, J., Petropoulos, G., Vaxevanidis, N.: Application of Taguchi design for quality characterization of abrasive water jet machining of TRIP sheet steels. Int. J. Adv. Manuf. Technol. 62(5–8), 635–643 (2012)

    Article  Google Scholar 

  22. Pathapalli, V.R., Basam, V.R., Gudimetta, S.K., Koppula, M.R.: Optimization of machining parameters using WASPAS and MOORA. World J. Eng. (2019). https://doi.org/10.1108/WJE-07-2019-0202

    Article  Google Scholar 

  23. Hafezalkotob, A., Hafezalkotob, A.: Fuzzy entropy-weighted MULTIMOORA method for materials selection. J. Intell. Fuzzy Syst. 31(3), 1211–1226 (2016)

    Article  Google Scholar 

  24. Mahmoudi, A., Sadi-Nezhad, S., Makui, A.: An extended fuzzy VIKOR for group decision making based on fuzzy distance to supplier selection. Sci. Iran. 23(4), 1879–1892 (2016)

    Google Scholar 

  25. Chakraborty, S., Zavadskas, E.K., Antucheviciene, J.: Applications of WASPAS method as a multi-criteria decision-making tool. Econ. Comput. Econ. Cybern. Stud. Res. 49(1), 5–22 (2015)

    Google Scholar 

  26. Mardani, A., Nilashi, M., Zakuan, N., Loganathan, N., Soheilirad, S., Saman, M.Z.M., Ibrahim, O.: A systematic review and meta-analysis of SWARA and WASPAS methods: theory and applications with recent fuzzy developments. Appl. Soft Comput. 57, 265–292 (2017)

    Article  Google Scholar 

  27. Mohammadi, H., Farahani, F.V., Noroozi, M., Lashgari, A.: Green supplier selection by developing a new group decision-making method under type 2 fuzzy uncertainty. Int. J. Adv. Manuf. Technol. 93(1–4), 1443–1462 (2017)

    Article  Google Scholar 

  28. Ighravwe, D.E., Oke, S.A.: A fuzzy-grey-weighted aggregate sum product assessment methodical approach for multi-criteria analysis of maintenance performance systems. Int. J. Syst. Assur. Eng. Manag. 8(2), 961–973 (2017)

    Article  Google Scholar 

  29. Karabašević, D., Stanujkić, D., Đorđević, B., Stanujkić, A.: The weighted sum preferred levels of performances approach to solving problems in human resources management. Serbian J. Manag. 13(1), 145–156 (2018)

    Article  Google Scholar 

  30. Zavadskas, E.K., Turskis, Z., Antucheviciene, J., Zakarevicius, A.: Optimization of weighted aggregated sum product assessment. Elektronika ir elektrotechnika 122(6), 3–6 (2012)

    Article  Google Scholar 

  31. Šaparauskas, J., Kazimieras Zavadskas, E., Turskis, Z.: Selection of facade's alternatives of commercial and public buildings based on multiple criteria. Int. J. Strateg. Prop. Manag. 15(2), 189–203 (2011)

    Article  Google Scholar 

  32. Ansari, A.I., Hashish, M.: Effect of abrasive waterjet parameters on volume removal trends in turning. Trans. ASME J. Eng. Ind. 117, 475–484 (1995)

    Article  Google Scholar 

  33. Naresh Babu, M., Muthukrishnan, N.: Investigation on surface roughness in abrasive water-jet machining by the response surface method. Mater. Manuf. Process. 29(11–12), 1422–1428 (2014)

    Article  Google Scholar 

  34. Kök, M., Kanca, E., Eyercioğlu, Ö.: Prediction of surface roughness in abrasive waterjet machining of particle reinforced MMCs using genetic expression programming. Int. J. Adv. Manuf. Technol. 55(9–12), 955–968 (2011)

    Article  Google Scholar 

  35. Akkurt, A., Kulekci, M.K., Seker, U., Ercan, F.: Effect of feed rate on surface roughness in abrasive waterjet cutting applications. J. Mater. Process. Technol. 147(3), 389–396 (2004)

    Article  Google Scholar 

  36. Selvam, R., Karunamoorthy, L., Arunkumar, N.: Investigation on performance of abrasive water jet in machining hybrid composites. Mater. Manuf. Process. 32(6), 700–706 (2017)

    Article  Google Scholar 

  37. Shanmugam, D.K., Wang, J., Liu, H.: Minimisation of kerf tapers in abrasive waterjet machining of alumina ceramics using a compensation technique. Int. J. Mach. Tools Manuf. 48(14), 1527–1534 (2008)

    Article  Google Scholar 

  38. Gupta, V., Pandey, P.M., Garg, M.P., Khanna, R., Batra, N.K.: Minimization of kerf taper angle and kerf width using Taguchi's method in abrasive water jet machining of marble. Procedia Mater. Sci. 6, 140–149 (2014)

    Article  Google Scholar 

  39. Reddy, P.V., Reddy, B.V., Rao, P.S.: A numerical study on tube hydroforming process to optimize the process parameters by Taguchi method. Mater. Today Proc. 5(11), 25376–25381 (2018)

    Article  Google Scholar 

  40. Reddy, P.V., Prasad, P.R., Krishnudu, D.M., Goud, E.V.: An investigation on mechanical and wear characteristics of Al 6063/TiC metal matrix composites using RSM. J. Bio Tribo-Corros. 5(4), 90 (2019)

    Article  Google Scholar 

  41. Reddy, J.J., Varaprasad, B.J.S., Reddy, P.V.: Application of grey Taguchi method to optimize the internal erosion parameters of stabilized soil. Multisc. Multidiscip. Model. Exp. Des. (2020). https://doi.org/10.1007/s41939-020-00077-z

    Article  Google Scholar 

  42. Prasad, P.R., Prakash, J.N., Manjunath, L.H., Reddy, P.V.: Physical and wear properties of UHMWPE fabric reinforced epoxy composites. Int. J. Automot. Mech. Eng. 17(1), 7577–7586 (2020)

    Article  Google Scholar 

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Acknowledgements

The authors would sincerely like to thank the management of G Pulla Reddy Engineering College (Autonomous), Kurnool, for providing the testing facilities and their constant support.

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Authors and Affiliations

  1. Department of Mechanical Engineering, JNTU Ananthapur (GPREC Research Centre), Ananthapuramu, Andra Pradesh, India

    P. Venkateshwar Reddy

  2. Department of Mechanical Engineering, G Pulla Reddy Engineering College, Kurnool, Andra Pradesh, India

    P. Venkateshwar Reddy, G. Suresh Kumar & V. Satish Kumar

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Correspondence to P. Venkateshwar Reddy.

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Venkateshwar Reddy, P., Suresh Kumar, G. & Satish Kumar, V. Multi-response Optimization in Machining Inconel-625 by Abrasive Water Jet Machining Process Using WASPAS and MOORA. Arab J Sci Eng 45, 9843–9857 (2020). https://doi.org/10.1007/s13369-020-04959-9

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