Multi-objective optimization of WEDM process parameters on titanium grade 9 using ANN and grey relational analysis

Wire Electrical Discharge Machining (WEDM) is a specialized electro-thermal, non-conventional machining process capable of machining complex shapes. This study aims to explore and optimize Wire Electro-Discharge Machining process parameters on Titanium Grade 9(Ti3Al2.5V). Titanium Grade 9, is mainly used for low weight, high strength applications. The objective of this research is to develop an Artificial Neural Network (ANN) to maximize Material Removal Rate(MRR) and minimize Avg. Surface Roughness (Ra) and Avg. of Peak Surface Roughness (Rz). Response Surface Methodology's Face Centered Composite Design was used to select experiments and used to study the influence of the combination of Ton, Toff and Gap Voltage. Further, the process parameters were studied to chosen optimized values of MRR, Ra and Rz using Grey analysis and average error for the ANN network is kept under 10%. By confirmation experiment for most optimum results by Grey Analysis, MRR is obtained as 65.32mm3/min, Ra and Rz as 8.45 µs and 59.32 µs respectively.