Development of a greybox model to predict tool wear of PVD coatings for finish turning - GreyProPVD

开发灰盒模型来预测精车 PVD ​​涂层的刀具磨损 - GreyProPVD

• 批准号: 521383048
• 负责人: Dr.-Ing. Benjamin Bergmann
• 金额: --
• 依托单位: Institut für Oberflächentechnik (IOT)
• 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/521383048?language=en
• 关键词: Development; greybox; model; predict; tool

Coated carbide tools are frequently used for machining with geometrically defined cutting edges. Depending on process conditions and material combinations, the tools are subject to crater, flank and notch wear generated by abrasion, adhesion, diffusion and tribooxidation. In addition, spalling can occur due to cohesive substrate failure. Despite the significant influence of tool wear on the cutting process, the real application behavior of coated tools cannot be adequately predicted according to the current state of research. While experimental approaches require a high amount of energy and materials resources, purely simulative, FE-based methods are unsuitable due to their high computational effort and time requirements. Both tools are therefore mainly useful for individual investigations that do not consider a wide variation of input variables. However, the extension or combination of simulation-based methods with data-driven black-box approaches offers the possibility to improve the performance and usability of models for tool development. The combined approaches also offer the possibility of integrating changes in tribological and thermophysical tool properties, as well as empirical data, into simulation models of tool and layer development. The mapping of property change is particularly highly relevant for time-resolved wear prediction of PVD coated cutting tools for finishing operations. Main aim of the proposed research project is the configuration of a greybox model to describe the time-resolved continuous tool wear and cohesive substrate failure of PVD coated carbide tools. By describing the wear behavior, an adaptation of different cutting material combinations and process parameters is possible, which leads to reduced tool wear and the avoidance of reject components and thus enables a reduction of resources in material consumption. For this purpose, data based black box models are combined with a simulation-based white box model. The blackbox models are used to derive wear-dependent, time-resolved layer properties and wear constants as well as the prediction of cohesive substrate failure based on the existing layer and substrate residual stresses. The whitebox model is used to calculate contact conditions and thermomechanical loads for time-dependent prediction of local state variables such as normal stress, sliding velocity and tool temperature. The experiments are carried out in continuous cutting conditions. In preparation for the second phase, an extension of the model to interrupted cutting conditions is planned as an intermediate step for milling.

涂层硬质合金刀具经常用于加工几何限定的切削刃。取决于工艺条件和材料组合，刀具会因磨损、粘附、扩散和摩擦氧化而产生凹坑、后刀面和缺口磨损。此外，由于内聚基底失效，可能发生剥落。尽管刀具磨损对切削过程有显着影响，但根据目前的研究状况，无法充分预测涂层刀具的真实的应用行为。虽然实验方法需要大量的能量和材料资源，但由于其高计算量和时间要求，纯模拟的基于FE的方法是不合适的。因此，这两种工具主要用于不考虑输入变量变化很大的个别调查。然而，基于模拟的方法与数据驱动的黑盒方法的扩展或组合提供了提高工具开发模型的性能和可用性的可能性。结合的方法还提供了整合的可能性，在摩擦学和热物理工具属性的变化，以及经验数据，到工具和层的发展的模拟模型。属性变化的映射对于用于精加工操作的PVD涂层切削工具的时间分辨磨损预测特别高度相关。建议的研究项目的主要目的是灰箱模型的配置来描述时间分辨的连续刀具磨损和内聚基体的PVD涂层硬质合金刀具的故障。通过描述磨损行为，可以适应不同的切削材料组合和工艺参数，这导致减少的刀具磨损和避免废品部件，从而能够减少材料消耗中的资源。为此，基于数据的黑盒模型与基于模拟的白色盒模型相结合。黑盒模型用于推导磨损相关的，时间分辨的层的属性和磨损常数，以及预测的基础上现有的层和基板的残余应力的内聚性基板故障。白盒模型用于计算接触条件和热机械载荷，以预测局部状态变量（如法向应力、滑动速度和刀具温度）随时间的变化。实验是在连续切削条件下进行的。在第二阶段的准备工作中，计划将模型扩展到中断切削条件，作为铣削的中间步骤。