Optimization and Prediction of Aluminum Alloy Stamping Forming Parameters Based on Gray Correlation

Abstract

The selection of stamping process parameters has very important influence on the mechanical properties, production cost and production efficiency of forming parts.This paper is based on the Simufact Forming simulation platform, using the grey system theory, to design the orthogonal experimental scheme, with automotive aluminum alloy stamping parts, performed stamping forming experiments under different parameters, taking the forming part and equal effect force, equivalent plastic strain, flushing pressure and outer diameter deviation as evaluation indexes, by analyzing its integrated gray correlation degree, Multi-objective parameter optimization for aluminum alloy stamping parts, the optimal combination of process parameters and the influence order on the evaluation index are obtained, using the grey system theory to establish the GM (0, N) prediction model, realize the rapid prediction of the evaluation index of automobile aluminum alloy stamping forming parts.The results show that the influence order of process parameters on the evaluation index is: heat treatment temperature > friction coefficient > stamping speed; when the stamping speed is 5mm / s, friction coefficient is 0.1 and heat treatment temperature is 350℃, the mechanical properties of aluminum alloy stamping parts reach the optimal 50; GM (0, N) gray prediction model can predict the performance of alloy stamping parts, with simple modeling and small error.