Quality control and prediction of drawing forming of automotive back door inner panel based on NSGA-II algorithm

In order to avoid forming defects such as wrinkling and cracking during the stamping of automobile cover parts, a non-ranking genetic algorithm (NSGA-II) based on elite strategy was proposed to optimize the stamping process parameters and realize the control and prediction of stamping forming quality. The forming process parameters such as blank holder force, friction coefficient, forming force and die clearance were taken as test factors, and the maximum thickening rate and the maximum thinning rate during drawing deformation were taken as quality control objectives. Latin hypercube sampling method and combining with CAE analysis technology to establish the test sample, build between stamping process parameters and forming quality control target of the response surface model, based on the NSGA - II algorithm was obtained in constructing the response surface model of a set of optimal process parameters meet the forming quality combination, at the same time, the forming quality of forecast is given. The actual stamping die test results prove the effectiveness of the method proposed in this paper, which provides a set of reference methods for the quality control and prediction of automobile cover parts.