Data-driven process modeling in stamping technology

冲压技术中的数据驱动工艺建模

• 批准号: 520459543
• 负责人: Professor Dr.-Ing. Matthias Althoff
• 金额: --
• 依托单位: Lehrstuhl für Umformtechnik und Gießereiwesen
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/520459543?language=en
• 关键词: Data; driven; process; modeling; stamping

In the context of digitalization and miniaturization, the demand for complex electronic components is increasing. These are often produced in stamping and bending processes, which are characterized by many forming operations and associated interactions. The complex interactions cannot be fully represented by simulations, so implicit knowledge remains essential. Therefore, the development and use of novel models is necessary to be able to generate additional process understanding. Especially data-driven modeling offers promising potentials in this respect to extract additional knowledge from existing data and thus to formalize implicit knowledge. Therefore, in this project a stamping-bending process will be modeled based on different numerical and real data. Of particular interest here are the defined quality criteria, which can be of both geometric and physical nature. Through the targeted introduction and measurement of disturbance variables, a comprehensive view of the process is made possible. For this purpose, modules are developed that allow to influence the process. A special feature of the proposed modeling approach is the use of a set-based reachability analysis. That is, the problem is formulated such that reachable states are guaranteed to be within a certain set. For forming processes, this means guarantees, e.g., regarding the compliance with certain tolerances. At the same time, the size of the set and distribution of achievable states allows an evaluation of the process stability. Another advantage in contrast to stochastic methods is that clear cause-effect chains can be identified. Thus, this approach promises new possibilities to increase the process understanding. However, this requires the development of new algorithms that allow the problem to be solved. After the model has been built, checked for conformance and formally verified, the validation of the model can take place. For this purpose, components are manufactured again on the basis of defined process parameters and compared with the predictions of the model. This is followed by process optimization based on the model. Subsequent production using the optimized process finally allows a comparison between the processes and a comprehensive evaluation of the predictive capability of the developed model.

在数字化和小型化的背景下，对复杂电子元件的需求越来越大。这些通常在冲压和弯曲过程中产生，其特征在于许多成形操作和相关的相互作用。复杂的相互作用不能完全通过模拟来表示，因此隐含的知识仍然是必不可少的。因此，开发和使用新的模型是必要的，能够产生额外的过程理解。特别是数据驱动的建模提供了很有前途的潜力，在这方面，从现有的数据中提取额外的知识，从而形式化隐含的知识。因此，在本项目中，冲压弯曲过程将根据不同的数值和真实的数据进行建模。这里特别感兴趣的是定义的质量标准，它可以是几何和物理性质的。通过有针对性地引入和测量干扰变量，可以全面了解过程。为此，开发了允许影响该过程的模块。所提出的建模方法的一个特点是使用基于集合的可达性分析。也就是说，问题被公式化，使得可达状态被保证在某个集合内。对于成形工艺，这意味着保证，例如，关于符合某些公差。同时，可实现状态的集合和分布的大小允许对过程稳定性进行评估。与随机方法相比，另一个优点是可以确定明确的因果链。因此，这种方法承诺新的可能性，以增加过程的理解。然而，这需要开发新的算法来解决问题。在模型被构建、一致性检查和正式验证之后，就可以进行模型的验证了。为此，根据定义的工艺参数再次制造部件，并与模型的预测进行比较。其次是基于模型的工艺优化。随后的生产使用的优化过程中，最终允许的过程之间的比较和开发的模型的预测能力的综合评价。