SAE 2009-01-0980 : 2009

Many uncertainties exist in the sheet metal stamping such as the variation of incoming material properties, die and press setup conditions, long-term tool wear and degradations. They are interacting in a way to make the process less robust, thus contributing to increased scrap rates and more unscheduled downtime. This paper presents a new approach for the die design optimization where these uncertainties are taken into account. A Tailor-Welded B-pillar consisting of 1.65mm DP600 and 0.9mm DDQ is selected as the focal part to demonstrate the new design process. The study is divided into two phases. The focus of the first phase is to understand the complexity of the formability window and determine effective optimization techniques under deterministic conditions. It is found that the formability window is highly nonlinear, or even discontinuous if a global objective function such as the Maximum Failure Factor is used. It is therefore more advantageous to adopt a regional approach where the split-prone zones and wrinkle-prone zones are identified. Optimization can then take place for each region with a multi-objective approach using the Non-dominated Sorting Genetic Algorithm (NSGA-II). The second phase takes into account the stamping uncertainties, and both the formability values and their deviations are optimized simultaneously for robustness. It is demonstrated that the robust optimization under uncertainties is able to reduce output variability while maintaining the same level of “optimal” performance as compared with deterministic optimization.

Cross Reference: