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An advanced FE-modeling approach to improve the prediction in machining difficult-to-cut material

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Abstract

Since the 1960s, the Inconel Alloy 718 has been a standard nickel-based superalloy due to its high strength, balanced mechanical properties, and strong corrosion resistance at relatively low costs and has been widely used in critical aircraft engine components. With the aim of improving productivity and product quality by implementing advanced tools and new process designs, models such as the FE model are utilized to predict the machining performance such as the cutting forces, the tool life, and the surface integrity. In the research area of FEM chip formation simulation, the influence of flank wear on predictions has not been investigated, especially not on the underestimation of the cutting normal force. In this paper, a 2D FEM chip formation model with the coupled Eulerian-Lagrangian (CEL) method has been built to predict cutting forces as well as other material loadings (Brinksmeier et al. Procedia CIRP 13:429–434, 2014; Buchkremer and Klocke Wear 376-377:1156–1163, 2017) in the machining of Direct Aged 718. In order to validate the performance of the FE model, fundamental investigations have been performed in orthogonal cutting with different cutting parameters. Two kinds of cemented carbide cutting tools with different cobalt contents have been applied to achieve different tool wear behaviors. Moreover, the underestimation of the cutting normal force by FEM chip formation simulation has been investigated and solved in consideration of the flank wear. The introduced FE-modeling approach shows precise predictions in terms of the cutting forces and the chip formation.

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Funding

The authors would like to thank the German Research Foundation (DFG) for the funding of the depicted research within the project ”Modelling of broaching processes by multi-scale discretization” (KL 500/159-1).

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Authors and Affiliations

  1. Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany

    Bingxiao Peng, Thomas Bergs, Fritz Klocke & Benjamin Döbbeler

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  1. Bingxiao Peng
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  2. Thomas Bergs
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  3. Fritz Klocke
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  4. Benjamin Döbbeler
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Correspondence to Bingxiao Peng.

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Peng, B., Bergs, T., Klocke, F. et al. An advanced FE-modeling approach to improve the prediction in machining difficult-to-cut material. Int J Adv Manuf Technol 103, 2183–2196 (2019). https://doi.org/10.1007/s00170-019-03456-0

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