Simulation-based optimization for preform’s dimensions of an automotive bevel gear

Abstract

The objective of this paper is to optimize preform’s dimensions of the
bevel gear in the forging process. The considered design parameters
include whole height (H), large diameter (D), and chamfer length (B).
Firstly, numerical simulations were applied in conjunction with the
Box-Behnken design (BBD) method and response surface methodology
(RSM) on the DEFORM 3D software to render the relationships of the
preform parameters with the forging load (F) and filling ratio (FR). A
non-dominated sorting genetic algorithm-II (NSGA-II) was used to
solve multi-objective optimization problems and search for Pareto
optimal solutions. Finally, the Technique for Order Preference by
Similarity to Ideal Solution (TOPSIS) was adopted to determine the
best solution compromised from the Pareto set. The results indicated
that the optimized preform with multi-criterion has shown better
performance in improving the material flow and ensuring filling cavity.
Therefore, this research is intended to contribute toward making
forging processes of bevel gears more efficient.