Criteria for Predicting Skid Line by Simulation

Rapid feasibility assessment of components to be formed through hot stamping: A deep learning approach

“…As mentioned by Zhou, Li & Xu [17], scalar based models lack informativeness due to this data consolidation. This is particularly true in scenarios where the manufacturing feasibility is determined by distribution based indicators, such as post form thickness gradients [18], surface slip lines [19] and wrinkle distributions [20]. To provide richer data representations, other references predicted full field data on a FE mesh using deep neural networks (DNNs).…”

Heuristic Optimization for Skid Lines in Automobile Covering Parts

“…As shown in Figure 3, the heuristic optimization process is mainly divided into two steps: (1) invoke FEA code to simulate the stamping process and then calculate the motion trajectory of skid lines, (2) update the layout of drawbeads based on the skid information in Step1. These two steps are repeated until the skid lines are restricted to the area of feature line radii.…”

“…Skid lines are very common defects and may occur when material follows over the feature line radii on the stamping tools. Skid lines affect seriously the appearance of automobile covering parts, which will lead to dramatic reduction in the competitiveness of automobile products [1].…”