Stochastic Modeling of the Interaction of Tool Wear and the Machining Affected Zone in Nickel-Based Superalloys and Application in Dynamic Stability

在许多工业部门，例如，能源或航空航天工业，镍基合金通常用于各种应用，由于其耐高温。不幸的是，这种优势导致材料的可加工性差，导致铣削过程中的高加工力和显着的刀具磨损。由于加工镍基合金时，工艺参数、工艺力、刀具磨损，特别是材料影响区之间存在复杂的依赖关系，为了优化加工工艺，提高制造零件的质量，需要基于仿真的工艺分析。在对这些依赖关系进行详细分析的基础上，本项目将开发用于预测工艺力、刀具磨损、工艺动力学和最终表面形貌的新模型。这些研究的一个特别重点是对工具磨损的随机性质的分析和描述。为了系统地分析磨损及其对工艺力的影响，将人工磨损刀片，以确保具有定义刀具磨损的可再现过程状态，这与实验中发生的磨损模式相对应。在五轴加工中心进行铣削实验之前，将这些人造刀具磨损刀片在可控工艺条件下的基本切屑形成机上进行正交切削试验，以分析产生的加工力并建立适当的模型。除加工力外，刀具磨损对加工动力学和加工表面形貌也有显著影响。为了预测刀具磨损的表面形貌，将开发一个基于三角形网格的磨损切削刃模型，并用于计算简化的扫描体积，从而有效地模拟切削过程。为了在优化加工过程时考虑到磨损相关的影响，例如，通过特定的齿面铣削路径设计，开发的模型将集成到基于几何物理的仿真系统中，该系统可用于分析复杂的加工过程。考虑到过程的随机性质，过程力和产生的刀具磨损的概率分布可以建模。基于所建立的模型，扩展的仿真系统将用于计算模糊稳定性图，以优化铣削工艺。该项目是美国南卡罗来纳州克莱姆森大学（由美国国家科学基金会资助）和多特蒙德大学之间的合作项目。

In many industrial sectors, e.g., the energy or aerospace industry, Nickel-based alloys are commonly used for various applications due to their high temperature resistance. Unfortunately, this advantage leads to a poor machinability of the material, resulting in high process forces and significant tool wear in milling processes. Due to the complex dependencies between process parameters, process forces, tool wear, and especially the material affected zone when machining Nickel-based alloys, a simulation-based analysis of the processes is required in order to optimize the machining process and to increase the quality of the manufactured parts. Based on a detailed analysis of these dependencies, new models for predicting process forces, tool wear, process dynamics, and the resulting surface topographies will be developed in this project.A special focus of these investigations is set on the analysis and description of the stochastic nature of the tool wear. To analyze the wear and its influence on the process forces systematically, inserts will be worn artificially in order to ensure reproducible process states with defined tool wear, which corresponds to the wear patterns occurring in experiments. These inserts with contrived tool wear will be used in orthogonal cutting tests on a fundamental chip formation machine with controllable process conditions in order to analysis the resulting process forces and to develop appropriate models, before conducting milling experiments on a 5-axis machining center.In addition to the process forces, the tool wear has a significant influence on the process dynamics and the machined surface topographies. In order to predict these surface topographies with respect to tool wear, a model of the worn cutting edges based on triangle meshes will be developed and used to calculate a simplified sweep volume for an efficient simulation of the cutting process. In order to take wear-dependent effects into account when optimizing machining processes, e.g., by a specific design of trochoidal milling paths, the developed models will be integrated into a geometric physics-based simulation system, which can be used to analyze complex machining processes. Taking the stochastic nature of the process into account, probability distributions of the process forces and resulting tool wear can be modeled. Based on the developed models, the extended simulation system will be used to calculate fuzzy stability charts in order optimize milling processes.This project is a collaboration between the Clemson University in South Carolina, USA (funded by the NSF) and the TU Dortmund University.