Application of grey-fuzzy approach in parametric optimization of EDM process in machining of MDN 300 steel

8th TSME-International Conference on Mechanical Engineering

Das, Partha Protim^1 ; Gupta, P.^1 ; Das, S.^1 ; Pradhan, B.B.^1 ; Chakraborty, S.^2

Mechanical Engineering Department, Sikkim Manipal Institute of Technology, Majitar

737136, India^1

Production Engineering Department, Jadavpur University, Jadavpur

700032, India^2

关键词: Difficult to machine materials;    Electro discharge machining;    Grey relation analyses (GRA);    Material removal rate;    Multi-objective optimization problem;    Parametric optimization;    Relative wear ratios;    Response parameters;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/297/1/012013/pdf
DOI  :  10.1088/1757-899X/297/1/012013

来源: IOP

【 摘 要 】

Maraging steel (MDN 300) find its application in many industries as it exhibits high hardness which are very difficult to machine material. Electro discharge machining (EDM) is an extensively popular machining process which can be used in machining of such materials. Optimization of response parameters are essential for effective machining of these materials. Past researchers have already used Taguchi for obtaining the optimal responses of EDM process for this material with responses such as material removal rate (MRR), tool wear rate (TWR), relative wear ratio (RWR), and surface roughness (SR) considering discharge current, pulse on time, pulse off time, arc gap, and duty cycle as process parameters. In this paper, grey relation analysis (GRA) with fuzzy logic is applied to this multi objective optimization problem to check the responses by an implementation of the derived parametric setting. It was found that the parametric setting derived by the proposed method results in better a response than those reported by the past researchers. Obtained results are also verified using the technique for order of preference by similarity to ideal solution (TOPSIS). The predicted result also shows that there is a significant improvement in comparison to the results of past researchers.