Multi-objective sheet metal forming simulations using a software agnostic platform

The development of new technologies for forming lightweight sheet metals into vehicle components has resulted in a rapid growth of advanced predictive models to analyze such processes. Simulations of the warm and hot forming of aluminium alloys in particular have been conducted on numerous finite element (FE) software packages with various specific phenomena being captured through the implementation of subroutines, to ensure that parts formed are free of defects and meet the required post-form strength. However, access to such models is lacking, with each having to be adapted to the software being used, and are computationally expensive to run, limiting the capabilities of simulations and increasing the challenges of utilizing new forming technologies effectively. Smart Forming is a knowledge-based cloud platform that was developed to overcome these challenges. It is composed of functional modules based on predictive models made accessible on the cloud that can be run individually or simultaneously. A conventional forming simulation is first run locally in any FE software of choice, and the required results uploaded to the modules on the platform for remote computation to investigate the phenomena of interest. In this work, simulation data from two different software packages, PAM-STAMP and Autoform, were processed for the same U-shaped component in the Smart Forming modules 'Formability' and 'Tailor', to demonstrate the multi-objective simulation and software agnostic capabilities of the platform. (paper)