Abstract

In view of the difficult machining characteristics of titanium alloys and the limitations of sequential EDM/ECM machining, taking NaNO3 salt solution with low conductivity as the working fluid, the simultaneous machining of EDM and ECM (SEDCM) assisted by abrasive particles was carried out. Firstly, the effects of the electrical conductivity of the working fluid, the abrasive material, and particle size on material removal rate (MRR), tool wear rate (TWR), surface roughness (Ra), and surface morphology of SEDCM were investigated. Then, SiC abrasive with particle size of 50 μm was selected to add in the working fluid of SEDCM, owing to the unique properties of SiC in comparison with Al and Cu abrasive particles. The effect of process parameters, such as peak current, pulse on time, abrasive concentration, and gap voltage, was optimized using Taguchi-based grey relational analysis. The multi-objective optimization of MRR, TWR, and Ra was converted into the optimization of a single grey relational grade. Finally, based on the grey relational grade, the optimal combination of peak current, pulse on time, abrasive concentration, and gap voltage was predicted and verified by experiments. The results show that the comprehensive machining effect is better when the conductivity of working medium is 300 μS/cm, as long as other electrical parameters and experimental conditions are the same. Compared with Cu and Al abrasives, SiC abrasive has the lowest tool wear rate and the best surface quality, even with the worst material removal rate. Moreover, MRR, TWR, and Ra were obviously improved at the optimal parametric combination of peak current 1.5A, pulse on time 15 μs, abrasive concentration 5 g/L, and gap voltage 40 V by implementing Taguchi-based grey relational analysis.

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