Modelling and optimizing performance parameters in the wire-electro discharge machining of Al5083/B4C composite by multi-objective response surface methodology

Composite is an artificial multiphase material that constituent phases which are chemically dissimilar and separated by a distinct interface. As a result of such anisotropic and non-homogeneous formation machining of composites is a strenuous task. Therefore, the need arose for formulating a stable predictive model. The comprehensive intention of this study is to develop a highly robust and stable predictive soft-computing model for forecasting the machining performance of Al-5083 alloy reinforced with B4C particles (Al5083/B4C). The study mostly emphasize on selecting the best machining parameters among the conducted experiments and evaluating the optimal machining parameters for Al5083/B4C composite in wire-electro discharge machin. The paper is an integration of equally weighted experimental as well as computational study. In the experimental part of the study, 5 different specimen of Al5083/B4C is prepared by the ex situ technique through stir casting process. The experimental part includes design of experiment by Taguchi’s method. The computational part of the study comprised of three different stages. The first stage involves the mathematical modelling of the performance measures and statistical scrutiny of the models. In the second stage, the best machining parameters are selected based on the fuzzy IF–then rules. The final stage of the manuscript is the trade-off analysis conducted to obtain the optimal machining parameters. In order to test the robustness of the formulated model an experimental validation is carried out at the optimal machining combination. The error calculated from the comparison is within the range of 2–5% which justifies the objective of the study.