Browsing by Author "Reeber, Tim"

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Open Access
A data-driven approach for cutting force prediction in FEM machining simulations using gradient boosted machines
(2024) Reeber, Tim; Wolf, Jan; Möhring, Hans-Christian
Cutting simulations via the Finite Element Method (FEM) have recently gained more significance due to ever increasing computational performance and thus better resulting accuracy. However, these simulations are still time consuming and therefore cannot be deployed for an in situ evaluation of the machining processes in an industrial environment. This is due to the high non-linear nature of FEM simulations of machining processes, which require considerable computational resources. On the other hand, machine learning methods are known to capture complex non-linear behaviors. One of the most widely applied material models in cutting simulations is the Johnson-Cook material model, which has a great influence on the output of the cutting simulations and contributes to the non-linear behavior of the models, but its influence on cutting forces is sometimes difficult to assess beforehand. Therefore, this research aims to capture the highly non-linear behavior of the material model by using a dataset of multiple short-duration cutting simulations from Abaqus to learn the relationship of the Johnson-Cook material model parameters and the resulting cutting forces for a constant set of cutting conditions. The goal is to shorten the time to simulate cutting forces by encapsulating complex cutting conditions in dependence of material parameters in a single model. A total of five different models are trained and the performance is evaluated. The results show that Gradient Boosted Machines capture the influence of varying material model parameters the best and enable good predictions of cutting forces as well as deliver insights into the relevance of the material parameters for the cutting and thrust forces in orthogonal cutting.
Open Access
Influence of the manufacturing parameters of an AlMg5 wire-based hybrid production process on quality and mechanical properties
(2021) Möhring, Hans-Christian; Becker, Dina; Eisseler, Rocco; Stehle, Thomas; Reeber, Tim
Hybrid manufacturing processes are known for combining the advantages of additive manufacturing and more traditional manufacturing processes such as machining to create components of complex geometry while minimising material waste. The trend towards lightweight design, especially in view of e-mobility, gives aluminium materials an important role to play. This study examines the use of aluminium alloys in laser metal wire deposition (LMWD) processes with subsequent subtractive machining, which is considerably more difficult due to the different process-related influences. The investigations are focussed on the influence of the differently controlled laser power on the shape accuracy, the microstructure, and the hardness of the AlMg5 test components after the LMWD process with subsequent subtractive machining by turning. The long-term goal of the investigations is to increase the stability of the hybrid production process of AlMg5 components with defined dimensional accuracy and mechanical properties.