Optimization of Wire Electrical Discharge Machining Parameters for Invar 36 Material Using Regression Modeling

Wire Electrical Discharge Machining (WEDM) is a non-conventional machining technique that provides distinct benefits in machining materials with high hardness and intricate geometries. Invar 36, a nickel-iron alloy with a low coefficient of thermal expansion (CTE), is widely used in the aerospace, automotive, and electronic industries because of its excellent dimensional stability across a broad range of temperatures. The main objectives are to optimize the machining parameters and create regression models that can accurately predict the key performance indicators. Experimental trials were performed utilizing a Wire Electrical Discharge Machining (WEDM) setup to fabricate Invar 36 specimens under different cutting conditions, such as pulse-on time, pulse-off time, wire tension, and wire feed rate. The machining performance was evaluated by measuring the material removal rate (MRR), surface roughness (Ra). The methodology of design of experiments (DOE) was utilized to systematically investigate the parameter space and determine the most effective machining settings. Regression models were constructed utilizing statistical methodologies to establish a correlation between input parameters and output responses, enabling accurate prediction of machining performance. This study enhances the comprehension of Wire Electrical Discharge Machining (WEDM) of Invar 36 material and offers valuable insights into how machining parameters affect the results of the process. The regression models that have been developed provide a useful tool for optimizing the parameters of Wire Electrical Discharge Machining (WEDM) and improving the efficiency of the machining process, while also ensuring that the desired surface quality is achieved in components made of Invar 36. This research promotes the utilization of WEDM as a practical manufacturing method for Invar 36-based applications, thus contributing to progress in precision engineering and materials processing.