Application of TOPSIS to Taguchi method for multi-characteristic optimization of electrical discharge machining with titanium powder mixed into dielectric fluid

• Published in: International journal of advanced manufacturing technology 2018-09, Vol.98 (5-8), p.1179-1198
• Main Authors: Nguyen, Huu-Phan, Pham, Van-Dong, Ngo, Ngoc-Vu
• Format: Article
• Language: English
• Subjects: CAE) and Design; Computer-Aided Engineering (CAD; Die steels; Dielectrics; EDM electrodes; Electric discharge machining; Electrode materials; Electrodes; Engineering; Industrial and Production Engineering; Material removal rate (machining); Mechanical Engineering; Media Management; Microhardness; Multiple criterion; Optimization; Original Article; Polarity; Process parameters; Product design; Signal to noise ratio; Surface properties; Surface roughness; Taguchi methods; Titanium; Workpieces
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-018-2321-2

Mixing powder into dielectric fluid in electrical discharge machining (PMEDM) is a very interesting technological solution in current research. This method has the highest efficiency in simultaneously improving the productivity and quality of a machined surface. In this study, material removal rate (MRR), surface roughness (SR), and the micro-hardness of a machined surface (HV) in electrical discharge machining of die steels in dielectric fluid with mixed powder were optimized simultaneously using the Taguchi–TOPSIS method. The process parameters used in the study included workpiece materials (SKD61, SKD11, SKT4), electrode materials (copper, graphite), electrode polarity, pulse-on time, pulse-off time, current, and titanium powder concentration. Some interaction pairs among the process parameters were also used to evaluate the effect on the optimal results. The results showed that MRR and HV increased and SR decreased when Ti powder was mixed into the dielectric fluid in EDM. Factors such as powder concentration, electrode material, electrode polarity, and pulse-off time were found to be significant in the optimal indicator (C*) and the S/N ratio of C*. Powder concentration was also found to be the most significant factor; its contribution to C* was 50.90%, and S/N ratio of C* was 51.46%. The interactions of the powder concentration and certain process parameters for C* were found to be largest. The optimum quality characteristics were MRR = 38.79 mm 3 /min, SR = 2.71 μm, and HV = 771 HV. The optimal parameters were verified by experiment, and its accuracy was good (max error ≈13.38%). The finished machined surface under optimum conditions was also analyzed. The machined surface quality under optimum conditions was good. In addition, the results of the study showed the TOPSIS limitations of TOPSIS in a multi-criteria optimization problem.