WEDM of Al/SiC/Ti composite: A hybrid approach of RSM-ARAS-TLBO algorithm

Abstract

Aluminum-based hybrid composites are the lightweight materials used for many industrial applications. These applications include brake parts, automotive engine, high speed rotating shafts, high speed machinery and robots. The machining of aluminum was normally done by conventional machining processes. However, after the addition of ceramic particles, it became difficult to process the hybrid composite by conventional processes. Thus, non-conventional machining processes are used for the machining of aluminum-based hybrid composite. In the present work, the aluminum-based hybrid composite was developed using stir casting method, where Al6063 was used as matrix material and SiC along with Ti were used as reinforcement material. After the development of hybrid composite, the material is processed on wire electric discharge machining (WEDM). The varying control factors while machining was pulse on-time (Ton), pulse off-time (Toff), servo voltage (SV) and wire feed (WF). However, the response variable to measure the machining characteristics were cutting speed (CS) and kerf width (KW). The experiments were planned according to Response Surface Methodology (RSM) based Box Behnken Design (BBD). The response variables were converted into optimality function using Additive Ratio Assessment (ARAS) and then the developed empirical model was solved by Teaching Learning Based Optimization (TLBO). The optimized setting suggested by hybrid approach is Ton: 128 μs; Toff: 48 μs; SV: 48 V; WF: 7 m/min. After the optimization an improvement of 12% in optimality function, 18.24% in CS and 17.11% in KW was observed as compared to the best experimental run. The morphological investigation shows that at the optimized setting the presence of micro-cracks, sub-surface, globules and recast layer reduced significantly.