Multi-objective optimization in wire-electro-discharge machining of TiC reinforced composite through Neuro-Genetic technique

This paper proposed a Neuro-Genetic technique to optimize the multi-response of wire electro-discharge machining (WEDM) process. The technique was developed through hybridization of a radial basis function network (RBFN) and non-dominated sorting genetic algorithm (NSGA-II). The machining was done on 5 vol% titanium carbide (TiC) reinforced austenitic manganese steel metal matrix composite (MMC). The proposed Neuro-Genetic technique was found to be potential in finding several optimal input machining conditions which can satisfy wide requirements of a process engineer and help in efficient utilization of WEDM in industry.

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► We propose a neuro-genetic technique to optimize WEDM machining parameters.
► This technique is developed through hybridization of RBFN and NSGA-II.
► The machining is done on 5 vol% titanium carbide reinforced metal matrix composite.
► The proposed technique is found to be potential in finding Pareto-optimal solutions.
► This method is better than the weighted-sum method coupled with single objective GA.