Modeling the machining process by means of simulation techniques became more and more popular within the last decades. The increasing use of simulation techniques can be attributed to the enhancing computational performance. To accurately model the machining process, different input models are required. Among them, the material model has a crucial impact on the quality of the simulated results. To determine the underlying material model parameters, an inverse procedure has been established, where the material model parameters are adjusted within a chip formation simulation until a reasonable match between simulations and experiments is achieved. However, the procedure of the inverse determination requires high computational efforts and is not robust. This paper presents a novel approach to determine material model parameters inversely from FE-machining simulations by means of the Downhill-Simplex-Algorithm. An effect study was conducted to investigate the influence of the initial simplex, the boundary conditions, and the underlying parameters of the Downhill-Simplex-Algorithm. Further, the validated procedure has been extended to consider multiple cutting conditions and an adaptive step-size has been implemented into the algorithm. The results of the procedure were validated by re-identification of process observables from the target simulations and it was aimed to re-identify the material model parameters of the target simulations. Based on the algorithm, a robust and systematical method has been developed to determine material model parameters inversely from the machining process.

在过去的几十年中，通过仿真技术对加工过程进行建模变得越来越流行。越来越多地使用模拟技术可以归因于增强的计算性能。为了准确地对加工过程建模，需要使用不同的输入模型。其中，材料模型对模拟结果的质量具有至关重要的影响。为了确定基本的材料模型参数，建立了一个逆过程，其中在切屑形成模拟中调整材料模型参数，直到实现模拟和实验之间的合理匹配。但是，逆确定的过程需要大量的计算工作并且不够鲁棒。本文提出了一种新颖的方法，通过下坡-单纯形算法，从有限元加工模拟中反过来确定材料模型参数。进行了一项效果研究，以研究初始单纯形，边界条件和下坡-单纯形算法的基本参数的影响。此外，已将经过验证的程序扩展为考虑多种切削条件，并且在算法中实现了自适应步长。通过从目标模拟中重新识别可观察到的过程可验证过程的结果，其目的是重新识别目标模拟中的材料模型参数。基于该算法，已开发出一种鲁棒且系统的方法来从加工过程中逆向确定材料模型参数。