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Strategies for springback compensation regarding process robustness

机译:关于过程稳健性的回弹补偿策略

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摘要

In this article, strategies which compensate geometrical deviations caused by springback are discussed using finite element simulations and statistical modelling techniques. First of all the ability to predict springback using a finite element simulation model is analysed. For that purpose numerical predictions and experiments are compared with each other regarding the amount of springback. In a next step, different strategies for compensating springback such as a modification of stress condition, component stiffness and tool geometry are introduced. On the basis of finite element simulations these different compensation strategies are illustrated for a stretch bending process and experimentally checked for an example. Finally springback simulations are compared regarding their robustness against noise variables such as friction and material properties. Thereby a method based on statistical prediction models is introduced which allows for an accurate approximation of the springback distribution with less numerical effort in comparison to a classical Monte-Carlo method.
机译:在本文中,使用有限元模拟和统计建模技术讨论了补偿由回弹引起的几何偏差的策略。首先,分析了使用有限元模拟模型预测回弹的能力。为此,将关于回弹量的数值预测和实验相互比较。下一步,介绍了用于补偿回弹的不同策略,例如应力条件,组件刚度和工具几何形状的修改。在有限元模拟的基础上,这些不同的补偿策略针对拉伸弯曲过程进行了说明,并通过实验进行了示例检验。最后,比较回弹模拟在抵抗噪声变量(如摩擦和材料特性)方面的鲁棒性。因此,引入了一种基于统计预测模型的方法,与传统的蒙特卡洛方法相比,该方法可以用较少的数值工作来精确地估算回弹分布。

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