Abstract
Abstract Wirecut-Electrical Discharge Machining (WEDM) is a non-traditional machining process, usually adopted to cut hard-to-machine materials, to achieve complex and intricate profiles with higher precision and dimensional accuracy, which are mostly desirable in present industrial scenario. This present study deals with the performance identification of three different types of wires in WEDM used for machining D3 steel, a high-carbon, high-chromium tool steel, by adopting a novel metaheuristic Cuckoo Search (CS) algorithm, which mimics the brood parasitic behaviour of cuckoo birds. Experimental investigation was planned, based on Taguchi’s Design of Experiments (DoE), for 8 parameters (cutting speed, Pulse-ON time, Pulse-OFF time, current, wire feed, wire tension, servo voltage and servo feed) varied through different level values, a L18 orthogonal array was selected. The output responses to be optimized was: surface roughness and Material Removal Rate (MRR). Empirical models were developed for three different wire materials such as plain brass, zinc coated and molybdenum coated through regression modelling. The objective was formulated considering maximization of MRR with surface roughness as constraint. It was observed that, molybdenum wire outperforms the other two wires, producing higher MRR and lower surface roughness, which proves the efficiency of the simple CS algorithm in optimization.
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