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ABSTRACT
LM 26 is a category of cast aluminum alloy which is having exceptional characteristics that leads to use of this alloy as primary choice for making automobile components. Metal matrix composite (MMC) materials are having improved characteristics and believed as an alternate for plentiful engineering industries. Due to reinforcement added, the materials became harder and result in inferior machining performance by traditional approaches. Wire electrical discharge machining (WEDM) is one among the advanced and also a conversant approach engaged for making intricate forms. In this exploration, an investigation on machinability of WEDM of stir-casted hybrid MMC (LM26+ Graphite+Fly ash) and evolution of hybrid adaptive neuro fuzzy inference system (ANFIS) model for predicting the desired variables. The ascendance of variables named as pulse on (Ton), pulse off (Toff), dielectric fluid flushing pressure, wire feed, and servo voltage in contrast to preferred output measures like material removal rate, surface finish, dimensional deviation, and form/orientation tolerance errors were investigated. A hybrid approach combining grey and ANFIS model has been developed to foretell the desired measures, and comparison has been done on the experimental and predicted results. The performance of the model is investigated and proved that the model can predict the desired measures.