Optimization of Flange Design for Engine Assembly Stand using RSM and NSGA-II Based on FEA Data

This article presents the results of a research study that focused on optimizing the flange design for engine assembly stands using the Response Surface Methodology (RSM) and Nondominated Sorting Genetic Algorithm II (NSGA-II) based on finite element analysis (FEA) simulation data. The study investigated the impact of three main dimensions (d1, d2, d3) of the flange as independent variables on the mass (m, kg), Von Mises stress (V, MPa), and displacement (D, mm) as dependent variables. The regression models developed using the RSM exhibited high R2 values of 0.9896, 0.998, and 0.9997 for m, V, and D, respectively. The multi-objective optimization results obtained through NSGA-II yielded 39 Pareto solutions, with d1 ranging from 10 to 27.43 mm, d2 ranging from 30 to 50 mm, and d3 ranging from 75 to 85 mm. These values corresponded to m values ranging from 2.93 to 7.58 kg, V values ranging from 54.8 to 342.6 MPa, and D values ranging from 0.006 to 0.270 mm. For verification purposes, Solution No.17 was selected. The results showed that the redesigned flange's mass, Von Mises stress, and displacement deviated by 0.95%, 2.28%, and 1.14%, respectively, from the optimal values obtained through the optimization process. These findings provide strong evidence for the high reliability of the optimization method employed in this study.