Abstract
Inconel 625, Introduction: The aviation, naval, and petrochemical industry industries frequently utilize the superalloy Inconel 625 because of its exceptional corrosion resistance and great tensile strength. However, because of its high heat conductivity and tremendous hardness, it is challenging to machine using standard techniques. Conventional machining techniques like Various nano (Wire- Machining) may efficiently drill tiny holes in Inconel 625. In this study, the micro-EDM drilling conventional methods of Inconel 625 were optimized using the WPM (Weighted Multilayer Perceptron Genetic Algorithm) approach. The pulse-on and pulse-off times as well as the peak current and during the simulation, servo voltage was considered as an input parameter optimization procedure. Materials percentage removal (MRR) and increased wear ratio were the output metrics (EWR). A multi-objective machine learning model was used in the optimization process to find the ideal combination of various parameters that would maximize the MRR and decrease the EWR. According to the experimental findings, the WPM approach was successful in optimizing the Inconel 625 micro-EDM drilling process parameters, which increased MRR and decreased EWR. Inconel 625 micro-EDM drilling may be made more effective and high-quality by using the optimized process parameters. Research significance: Due to its extreme hardness and heat conductivity, Inconel 625 is a difficult alloy to manufacture. A hole is made in the material by eroding it with a sequence of electric sparks using the non-traditional machining technique known as Micro-EDM. When drilling tiny holes in Inconel 625 or other difficult-to-machine materials, this method is quite helpful. Several process parameters, including signal time, wave time, peak current, but also servo voltage, have a substantial impact on the success of a micro-EDM drilling procedure. When these variables are combined in an ideal way, drilling efficiency, electrode wear, and surface quality can all be enhanced. In this study, the Inconel 625 micro-EDM drilling process parameters were optimized using the WPM approach. The WPM approach is a multi-objective plan that finds the ideal set of process variables to concurrently increase material removal (MRR) and reduce electrode wear ratio using singular value decomposition and just a genetic algorithm (EWR). Methodology: A well-liked technique for multi-criteria decision analysis (MCDA) and multi-criteria decision making (MCDM) is the weighted product model (WPM). The weighted sum model is comparable to this (WSM). The primary distinction is that multiplication is used as the primary mathematical operation rather than addition. Alternative: Process parameters levels 1, Process parameters levels 2, Process parameters levels 3. Evaluation preference: Current (A), Pulse on time (μs), Pulse off time (μs), Gap Voltage (V), Capacitance (pF), EDM feedrate (μm/s) Results: From the result it is seen that Pulse off time (μs) is got the first rank whereas is the Capacitance (pF) is having the lowest rank.