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Abstract Tool wear plays a decisive role in achieving the required surface quality and dimensional accuracy during the machining of Inconel 718-based products. The highly stochastic phenomenon of tool wear, particularly in later stages, results in difficulty in predicting the failure point of the tool. The present research work aims to study this late-stage wear of the tool by generating consistent wear conditions and thereby decoupling the late-stage wear from the wear history. To do so, a multi-axis grinding operation is employed to create artificial tool wear that replicates the topology of natural wear occurring in the process. In order to evaluate the imitating ability of the proposed methodology, microscopic images in different wear states of naturally and contrived worn tools were analyzed. The methodology was validated by comparing the resulting process forces measured during end milling with the natural and contrived worn tool for different path strategies. Finally, a qualitative finite element (FE) analysis was conducted, and specific force coefficients for worn tool segments were determined through simulation.
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Experimental and simulative analysis of an adapted methodology for decoupling tool wear in end milling
The machining of nickel-based superalloys such as Inconel 718 still poses a great challenge. The high strength and temperature resistance of these materials lead to poor machinability, resulting in high process forces and extensive tool wear. However, this wear is stochastic when reaching a certain point and is di cult to predict. To generate consistent wear conditions, the tool wear can be decoupled from the milling process by creating artificial wear using grinding. In this paper, a multi-axis approach for decoupling tool wear is presented and analyzed. Therefore, scanning electron microscope images of di erent wear states – worn and artificially worn – are analyzed. In addition, the occurring process forces of naturally and contrived worn inserts are compared in orthogonal cutting experiments as an analogy setup. Finally, a finite element analysis using a novel methodology for segmenting relevant cutting edge sections using digital microscope images provides qualitative insights on the influence of different wear conditions.
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- Award ID(s):
- 1760809
- PAR ID:
- 10435244
- Date Published:
- Journal Name:
- Manufacturing letters
- Volume:
- In Press
- Issue:
- In Press
- ISSN:
- 2213-8463
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.1016/j.mfglet.2022.07.050
