Multi-Objective Optimization for Contemporary Drilling of Nimonic Alloy Using Taguchi-Grey Relational Analysis

<div class="section abstract"><div class="htmlview paragraph">The objective of this research is to develop an optimization strategy for the Electrochemical Drilling process on Nimonic alloy material, taking into account various performance factors. The optimization strategy relies on the integration of the Taguchi method with Grey Relational Analysis (GRA). Nimonic is extensively utilized in aerospace, nuclear, and marine industries, specifically in situations that are prone to corrosion. The experimental trials are structured based on Taguchi's principle and encompass three machining variables: feed rate, electrolyte flow rate, and electrolyte concentration. This inquiry examines performance indicators like the rate of material removal, surface roughness, as well as geometric parameters such as overcut, shape, and orientation tolerance. Based on the investigation, it is determined that the feed rate is the primary factor that directly affects the intended performance criteria. In order to enhance the accuracy of predictions, multiple regression models are created and performance metrics are constructed. A validation test was performed to corroborate the findings acquired using the GRA approach. The test results demonstrate that the proposed strategy is markedly superior to earlier approaches.</div></div>