Multi-objective optimization in titanium powder mixed electrical discharge machining process parameters for die steels

Abstract

In this paper, we propose a viable optimal solution for achieving multi-objective optimization in powder mixed electrical discharge machining (PMEDM) process parameters, using titanium powder. Taguchi–AHP–Deng’s method is used to solve the multi-criteria decision making (MCDM) problem for this technology. The process parameters selected are workpiece material, electrode material, electrode polarity, pulse on time (Ton), pulse off time (Tof), current (I), and powder concentration. The material removal rate (MRR), tool wear rate (TWR), surface roughness (SR), hardness surface (HV), and white layer thickness (WLT) were determined simultaneously. The results showed that the optimal material for the workpiece is SKD11 die steel; the optimal material for the electrode is Gr; and the polarity of the electrode should be positive. The optimal values for the other process parameters were determined to be Ton = 20 μs, Tof = 57 μs, and I = 8 A, and that for the powder concentration was 10 g/l. The quality criteria for the optimal process parameters were determined to be MRR = 59.669 mm3/min, TWR = 14.073 mm3/min, SR = 4.45 μm, HV = 907.64 HV and WLT = 8.56 μm. The results were verified through experiments, which revealed a good accuracy (error ≈ 11.67%). The white-layer formation on the machined surface was reduced using titanium powder-based PMEDM for die steel at the optimal conditions. The results showed that Deng’s similarity method is the most suitable for MCDM in PMEDM using titanium powder.

Effects of process parameters on mechanical and metallurgical properties of AA5083 weld bead and optimization by using Taguchi based grey relational analysis and ANOVA of submerged friction stir welding.

“…The different optimization techniques are used to analyze the optimum process parameters and improve the quality measures. Initially, the Taguchi-Data Envelopment Analysis based Ranking(DEAR) based multi-criteria decision making has been proposed to obtain the optimal combination process parameters (Huu Phan et al, 2020). The MRR is analyzed using Taguchi methods to identify the main significant factors influencing the MRR (Huu Phan et al, 2021).…”

“…When the TOPSIS method is combined with the Taguchi method, they obtain several optimized process parameters, reduce the experiment's cost and time, and solve the multi-objective optimization problem (Huu Phan et al, 2016). When the optimization techniques, Deng's computation as the most appropriate MCDM approach in PMEDM, compared with TOPSIS, GRA, and PSI (Huu, 2020).. are investigated, An attempt has been made to implement TOPSIS based multi-response optimization to investigate the effects of low-frequency vibration on MRR and Surface Roughness in EDM (Phan Nguyen et al, 2018). In dissimilar FSW capability of AA7075 and AA6013-T6 in applying the Taguchi-based GRA, the welded joint's optimum process condition was determined by considering the % of contribution effect orderly TRS, TPP, and TTS (Kasman et al, 2019).…”