Multi-criteria Decision-making of Vibration-aided Machining for High Silicon-carbon Tool Steelwith Taguchi–topsis Approach

Abstract

The frequency-aided electrical erosion machining process can enhance the process mechanism and efficacy. It is time consuming to choose the optimal vibration-oriented parameters in the electrical discharge machining (EDM) process. In the present study, the technique for order of preference by similarity to ideal solution (TOPSIS) based multi-attribute optimization was proposed in the process on machining high silicon-carbon tool steel under low vibrational frequency of the workpiece material. The surface roughness, material removal rate, micro-hardness, and white layer thickness were chosen as quality measures. The experimental investigation was performed by comparing TOPSIS engineering optimization with Deng’s approach, preference selection index, grey relational analysis, the Visekriterijumsko–Kompromisino–Rangiranje (VKR) approach, simple additive weighting, and complex proportional assessmentto analyse the accuracy of the TOPSIS approach. From the experimental analysis, it was inferred that the low-frequency vibration-associated workpiece can considerably improve the quality factors in EDM. The Taguchi–TOPSIS approach can provide a better computational approach to resolve the multi-objective optimal problem.