The rapid wear and premature failure of the cutting tool are prone to happen due to increased forces during machining difficult-to-cut materials such as Inconel 718. The application of alternative toolpath such as trochoidal milling has significantly improved tool life and reduced the overall cycle time of the process. The wear pattern of the tool has a direct impact on the cutting forces, which increases with tool deterioration. The cutting forces in milling are modeled through the mechanistic force model and can be designated through a set of force coefficients, i.e. cutting and edge representing the shearing and ploughing phenomenon of metal removal. It has been established in the literature that tool wear has a considerable effect on the value of edge force coefficients. This paper aims to determine the in-process edge force coefficients for the trochoidal toolpath and correlates them with the corresponding flank wear area. The proposed correlation will further assist in predicting the level of flank wear area based on the force values in trochoidal milling.
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This content will become publicly available on November 1, 2024
A novel approach for in-situ characterization and probabilistic prediction of cutting tool fatigue in machining of Ti-6Al-4V
The wear behavior of cutting tools is highly complex due to combined thermal, mechanical, and chemical loads. As a result, most current tool-wear prediction methodologies are either empirical or highly oversimplified analytical or numerical models of stable abrasive and diffusive wear mechanisms. To predict the complex physics of catastrophic tool edge chipping, which in practice bounds feasible process parameters, this manuscript presents a novel approach for in-situ characterization of tool edge fatigue loads and probabilistic prediction of the likelihood of time to fracture. The results of the analysis suggest encouraging possibilities for more physics-informed and data-driven process design.
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- Award ID(s):
- 2143806
- NSF-PAR ID:
- 10489104
- Publisher / Repository:
- Manufacturing Letters, Elsevier
- Date Published:
- Journal Name:
- Manufacturing Letters
- Volume:
- 38
- Issue:
- C
- ISSN:
- 2213-8463
- Page Range / eLocation ID:
- 79 to 82
- Subject(s) / Keyword(s):
- Machining Process modeling In-situ characterization
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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