An Adaptive Neuro-Fuzzy Inference System (ANFIS) for Wire-EDM of Ballistic Grade Aluminium Alloy

Intricacy and complexity of ballistic missile and aerospace parts makes WEDM an essential machining process. The current study aims to formulate an ANFIS model for Wire-EDM of ballistic grade aluminium alloy. The experimentation has been conducted with four input variables namely pulse on time (T-on), pulse off time (T-off), peak current (I-p), and servo voltage (V-s). Material removal rate (MRR) is employed as process performance evaluator. The values predicted by the developed model are found closer to experimental outcome and thus ensures the model suitability for prediction purpose and intelligent manufacturing. Machined surfaces are also examined by the scanning electron microscope (SEM) to obtain better insight of the process.