Abstract
The present investigation highlights an experimental study and optimization of machining outcomes characteristics (such as MRR and Ra) during WEDM process of Inconel 625. The present work examined the effects of wire electrode materials, such as Zn-coated brass electrode (ZCBE) and uncoated brass electrode (UBE) on work material during WEDM process. Based on L16 orthogonal array, the experiment was performed in consideration with four process factor: spark-on time (Son), flushing pressure (Pf), wire-tension (Tw), and discharge current (Dc), within selected experimental domain. The additional objective of present investigation is to develop a multi-response optimization tool for selection of satisfactory process parameter setting during WEDM of Inconel 625. Nonlinear regression model was applied to formulate statistical models for multi-objective optimization using, fuzzy inference system (FIS) combination with TLBO for fulfill this objective. Finally, the satisfactory process parameter obtained by TLBO was compared with the genetic algorithm (GA) individually and found out that, the TLBO algorithm was found to be simpler, effective, and time-saving approach while solving multi-objective problems.
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References
Tarng, Y., Ma, S., Chung, L.: Determination of optimal cutting parameters in wire electrical discharge machining. Int. J. Mach. Tools Manuf. 35(12), 1693–1701 (1995)
Spedding, T.A., Wang, Z.: Parametric optimization and surface characterization of wire electrical discharge machining process. Precision Eng. 20(1), 5–15 (1997)
Kumar, A., Majumder, H., Vivekananda, K., Maity, K.: NSGA-II approach for multi-objective optimization of wire electrical discharge machining process parameter on inconel 718. Mater. Today Proc. 4(2), 2194–2202 (2017)
Scott, D., Boyina, S., Rajurkar, K.: Analysis and optimization of parameter combinations in wire electrical discharge machining. Int. J. Prod. Res. 29(11), 2189–2207 (1991)
Kumar, A., Abhishek, K.: Influence of process parameters on MRR, kerf width and surface roughness during WEDM on Inconel 718: performance analysis of electrode tool material. Int. J. Ind. Syst. Eng. 30(3), 298–315 (2018)
Bobbili, R., Madhu, V., Gogia, A.: Effect of wire-EDM machining parameters on surface roughness and material removal rate of high strength armor steel. Mater. Manuf. Process. 28(4), 364–368 (2013)
Prohaszka, J., Mamalis, A., Vaxevanidis, N.: The effect of electrode material on machinability in wire electro-discharge machining. J. Mater. Process. Technol. 69(1), 233–237 (1997)
Antar, M., Soo, S., Aspinwall, D., Jones, D., Perez, R.: Productivity and workpiece surface integrity when WEDM aerospace alloys using coated wires. Procedia Eng. 19, 3–8 (2011)
Kumar, A., Abhishek, K., Vivekananda, K., Maity, K.: Effect of wire electrode materials on die-corner accuracy for Wire Electrical Discharge Machining (WEDM) of Inconel 718. Mater. Today Proc. 5(5), 12641–12648 (2018)
Kumar, A., Abhishek, K., Vivekananda, K., Upadhyay, C.: Experimental study and optimization of process parameters during WEDM taper cutting. In: Soft Computing for Problem Solving, pp. 721–736. Springer (2019)
Varun, A., Venkaiah, N.: Simultaneous optimization of WEDM responses using grey relational analysis coupled with genetic algorithm while machining EN 353. Int. J. Adv. Manuf. Technol. 76(1–4), 675–690 (2015)
Zadeh, L.A.: A fuzzy-algorithmic approach to the definition of complex or imprecise concepts. Int. J. Man Mach. Stud. 8(3), 249–291 (1976)
Verma, R.K., Abhishek, K., Datta, S., Mahapatra, S.S.: Fuzzy rule based optimization in machining of FRP composites. Turk. J. Fuzzy Syst. 2(2), 99–121 (2011)
Rao, R.V., Savsani, V.J., Vakharia, D.: Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput. Aided Des. 43(3), 303–315 (2011)
Rao, R.V., Savsani, V.J., Vakharia, D.: Teaching–learning-based optimization: an optimization method for continuous non-linear large scale problems. Inf. Sci. 183(1), 1–15 (2012)
Rao, R.V.: Parameter optimization of machining processes using TLBO algorithm. In: Teaching Learning Based Optimization Algorithm, pp. 181–190. Springer (2016)
Golshan, A., Ghodsiyeh, D., Izman, S.: Multi-objective optimization of wire electrical discharge machining process using evolutionary computation method: effect of cutting variation. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 0954405414523593 (2014)
Palanikumar, K.: Surface roughness model for machining glass fiber reinforced plastics by PCD tool using fuzzy logics. J. Reinf. Plast. Compos. 28(18), 2273–2286 (2009)
Kaveh, A., Talatahari, S.: Optimum design of skeletal structures using imperialist competitive algorithm. Comput. Struct. 88(21–22), 1220–1229 (2010)
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Kumar, A., Mohanty, C.P., Bhuyan, R.K., Shaik, A.M. (2020). Performance Analysis and Optimization of Process Parameters in WEDM for Inconel 625 Using TLBO Couple with FIS. In: Das, K., Bansal, J., Deep, K., Nagar, A., Pathipooranam, P., Naidu, R. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 1048. Springer, Singapore. https://doi.org/10.1007/978-981-15-0035-0_72
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