Tool Condition Monitoring in the Milling of Low- to High-Yield-Strength Materials

The preservation and continuous monitoring of cutting tools in a computer numerical control (CNC) machine is essential for ensuring seamless transitions in the manufacturing workflow, as well as maintaining adequate part quality. The implementation of tool condition monitoring (TCM) when milling can provide the user with necessary data regarding tool life, wear, and part quality. However, it is important to broaden the application of the TCM process across a much broader class of workpiece materials to understand the effects of material properties on the condition of the tool. The aim of this paper is to investigate the efficacy of tool condition monitoring techniques while milling low- and high-yield-strength materials across varied process parameters. A Fast Fourier Transform (FFT) analysis was conducted in this research. Vibration data were acquired from both uniaxial and triaxial accelerometers to investigate irregularities in vibrational amplitudes between new and worn milling tools. The experimental results show that there is a significant increase in vibrational amplitudes for the worn tool when compared to the new tool across various frequencies, which affirms the expected increase in vibrations and cutting forces at the tool–workpiece interface from using a worn tool. The F-values and p-values calculated using an F-test with a 95% confidence interval indicated statistically significant differences in vibration data between new and worn tools across various materials, including polyurethane foam, aluminum 6061, mild steel, and stainless steel, under different cutting conditions (low, medium, and high). These results further validate the findings obtained from the FFT analysis and highlight the effectiveness of vibration-based monitoring in distinguishing tool wear under varying material characteristics and machining conditions.

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Institutions

Publication Details

Journal
Machines
Published
2025-03-27
DOI
https://doi.org/10.3390/machines13040276
Citations
2
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
1.43

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article

Tool Condition Monitoring in the Milling of Low- to High-Yield-Strength Materials

Sohan Nagaraj, Nancy Diaz-Elsayed
2 citations
Machines
Advanced machining processes and optimization
1.43
article

Tool Condition Monitoring in the Milling of Low- to High-Yield-Strength Materials

Sohan Nagaraj, Nancy Diaz-Elsayed
article en
2 citations

Abstract

The preservation and continuous monitoring of cutting tools in a computer numerical control (CNC) machine is essential for ensuring seamless transitions in the manufacturing workflow, as well as maintaining adequate part quality. The implementation of tool condition monitoring (TCM) when milling can provide the user with necessary data regarding tool life, wear, and part quality. However, it is important to broaden the application of the TCM process across a much broader class of workpiece materials to understand the effects of material properties on the condition of the tool. The aim of this paper is to investigate the efficacy of tool condition monitoring techniques while milling low- and high-yield-strength materials across varied process parameters. A Fast Fourier Transform (FFT) analysis was conducted in this research. Vibration data were acquired from both uniaxial and triaxial accelerometers to investigate irregularities in vibrational amplitudes between new and worn milling tools. The experimental results show that there is a significant increase in vibrational amplitudes for the worn tool when compared to the new tool across various frequencies, which affirms the expected increase in vibrations and cutting forces at the tool–workpiece interface from using a worn tool. The F-values and p-values calculated using an F-test with a 95% confidence interval indicated statistically significant differences in vibration data between new and worn tools across various materials, including polyurethane foam, aluminum 6061, mild steel, and stainless steel, under different cutting conditions (low, medium, and high). These results further validate the findings obtained from the FFT analysis and highlight the effectiveness of vibration-based monitoring in distinguishing tool wear under varying material characteristics and machining conditions.

MachinesVol. 13(4)
University of South Florida (US)
Alfred P. Sloan Foundation
Openalex Percentile: Top 21%
Advanced machining processes and optimization
1.43
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Tool Condition Monitoring in the Milling of Low- to High-Yield-Strength Materials — Sohan Nagaraj, Nancy Diaz-Elsayed · Machines (2025) | TGRS Research Map | TGRS