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Tool wear monitoring in ramp cuts in end milling using the wavelet transform

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Abstract

Tool wear identification and estimation present a fundamental problem in machining. With tool wear there is an increase in cutting forces, which leads to a deterioration in process stability, part accuracy and surface finish. In this paper, cutting force trends and tool wear effects in ramp cut machining are observed experimentally as machining progresses. In ramp cuts, the depth of cut is continuously changing. Cutting forces are compared with cutting forces obtained from a progressively worn tool as a result of machining. A wavelet transform is used for signal processing and is found to be useful for observing the resultant cutting force trends. The root mean square (RMS) value of the wavelet transformed signal and linear regression are used for tool wear estimation. Tool wear is also estimated by measuring the resulting slot thickness on a coordinate measuring machine.

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Acknowledgement

This research is supported by the National Science Foundation under grant no. DMI 9970083. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors gratefully acknowledge help from Jim Dautremont in Mechanical Engineering and Kevin Brownfield in Industrial and Manufacturing Systems Engineering for assistance with the machining experiments.

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Authors and Affiliations

  1. Industrial and Manufacturing Systems Engineering, Mechanical Engineering, Iowa State University, 2019 Black Engineering Building, Ames, IA 50011, USA

    Y. Choi, R. Narayanaswami & A. Chandra

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  1. Y. Choi
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  2. R. Narayanaswami
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  3. A. Chandra
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Correspondence to R. Narayanaswami.

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Choi, Y., Narayanaswami, R. & Chandra, A. Tool wear monitoring in ramp cuts in end milling using the wavelet transform. Int J Adv Manuf Technol 23, 419–428 (2004). https://doi.org/10.1007/s00170-003-1898-1

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  • DOI: https://doi.org/10.1007/s00170-003-1898-1

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