Optimization of Forming Processes with Different Sheet Metal Alloys

Over the past decades relatively heavy components made of steel alloys comprise the majority of many manufactured parts due to steel's low cost, high formability and good strength. The desire to produce lightweight parts has led to studies searching for lighter and stronger materials such as aluminum alloys. However, they exhibit lower elastic stiffness than steel resulting in higher elastic strains causing known distortions such as spring-back and so decreasing accuracy of manufactured net-shape components. This paper presents a developed computational method to optimize the design of sheet metal processes using genetic algorithms. An inverse approach is considered so that the final geometry of the bended blank closely follows a prescribed one. The developed computational method couples a finite element forming simulation and an evolutionary algorithm searching the optimal design parameters of the process. The developed method searches the optimal parameters that ensure a perfect net-shape part. Different aluminum alloys candidates for automotive structural applications are considered and the optimal solutions are analyzed